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How Internet Computer is Transforming Blockchain Technology

Com l'ordinador d'Internet està transformant la tecnologia Blockchain

Cómo la informática de Internet está transformando la tecnología blockchain

چگونه کامپیوتر اینترنت فناوری بلاک چین را متحول می کند

インターネットコンピュータがブロックチェーン技術をどのように変革しているか

როგორ ცვლის ინტერნეტ კომპიუტერი ბლოკჩეინის ტექნოლოგიას

របៀបដែលកុំព្យូទ័រអ៊ីនធឺណិតកំពុងផ្លាស់ប្តូរបច្ចេកវិទ្យា Blockchain

Интернет-Компьютер Blockchain технологиясын кантип өзгөртүп жатат

අන්තර්ජාල පරිගණකය Blockchain තාක්ෂණය පරිවර්තනය කරන්නේ කෙසේද?

Internet kompýuteriniň “Blockchain” tehnologiýasyny nädip üýtgedýändigi

Paano Binabago ng Internet Computer ang Blockchain Technology

انٹرنیٹ کمپیوٹر بلاک چین ٹیکنالوجی کو کس طرح تبدیل کر رہا ہے۔

Ikhompyutha Ye-inthanethi Iguqula Kanjani Ubuchwepheshe Be-Blockchain

How we Achieved 11% Growth by Leveraging Personalization and Segment-based Product Flows

Here's a new problem, and a new set of jobs for humans, that will be caused as more and more Robotaxis show up (think of an Uber that works without a human in the car). What is the problem? Transportation behavior will change as we get more and more vehicles on the road with no humans inside. Something that's already happening in San Francisco, where you see many autonomous vehicles driving around with no humans inside from companies like Waymo, Zoox, and others. Expected are many others, including Tesla, and GM's Cruise which we hear will be back on the road later this year. The problem? Football stadiums, concerts, basketball stadiums, conferences, events like the Olympics, all will see radically different usage patterns. For instance, today, if you attend a football game, you park in one of dozens of parking lots around the stadium and you walk in, or take a shuttle to one of the entrances. This adds some "randomness" to the flow of crowds in and out and lets city officials who plan out traffic flows bring traffic to those parking lots with a few different routes. Even today it's often a mess with traffic taking an hour to get into many venues with large numbers of people but officials, and others, who work in these industries tell me autonomous vehicles will make traffic far worse. Why? Well, let's assume in five years you are in a Cybertruck taking your family to a football game and that by then the Cybertruck can drive with no humans in the car. Will you want your Cybertruck to take you to a far off parking lot and make you walk to the stadium? No. You'll want it to drop you off near the football stadium. And here's the rub: so will everyone else. Which means you'll have thousands of Waymos, Cruises, Teslas, all trying to get to the same drop-off point. This new human expectation will lead to traffic nightmares. Worse, I've been talking with executives at these kinds of venues and they say the coordination between sports teams, city officials/police, and ride-sharing companies is nearly non-existent.One told me they tried to get Uber and Lyft to come meet with them to design new traffic flows for their vehicles and they just don't get very little help or interest from the ride-sharing companies. One, who works with the 49ers, tells me city officials often put up signs for Uber/Lyft drivers that lead them into dead-end roads where they need to waste time turning around and figuring out where they need to go. Signage, cones, road closures, all could be done in a much better way around venues. And that's before you consider the humans. Often crowds of humans getting out of venues are drunk, don't follow traffic rules, and, sometimes, even turn riotous. Has the autonomous vehicle industry worked with venues to understand how traffic systems change around event venues? No, is the answer I keep hearing, and getting Waymo or Tesla interested in studying the problem together and designing new traffic facilities around big-crowd venues is difficult. Oh, it can happen. At Coachella, for instance, Uber built a huge parking lot with waiting areas for humans that were covered (it's hot often waiting for your ride to show up). Uber also built contextual systems to work with drivers around the Western United States to convince drivers to come to Palm Springs for a month and drive people around (Coachella is two weekends, where 150,000 people visit each weekend, followed by a country music festival that has slightly smaller crowds, but Uber, alone, brings thousands of cars to handle the crowds of people who want to use it to get to and from the venue). Along with the parking lot city officials block off lanes and have clear signs for Uber/Lyft/Taxis to use and have police at every intersection directing traffic and making sure things flow smoothly. Even with all that work it often takes one to three hours of standing in line to get a Taxi or an Uber out of the venue. Now imagine if thousands of people were arriving in autonomous vehicles. If the vehicles weren't programmed into where to go, and if Tesla doesn't have its own drop off and pickup lot things could get nasty, and fast. Last week at NVIDIA's big event my Tesla was programmed to pick up a friend at the Marriott. Problem was it took me down a route that is usually just fine, but during that event NVIDIA and city officials had the street in front of the conference center closed due to the large crowds that were attending that event. My Tesla didn't know about the closed street so it tried to take me down that closed street, figured it out too late, and then got stuck in traffic going on a detour around, wasting 15 minutes. Now 15 minutes doesn't seem like a big deal, but it is if I was driving an Uber passenger. Why? Well, first of all now I have a passenger who isn't happy with the navigation choices the car made, maybe giving me a lower score than I otherwise would get, but, worse, if I was picking up a passenger that person might see that I'm now 15 minutes away instead of two and decide to hop in a cab or cancel my ride. Wasted time, which means if I'm driving an Uber I don't get paid. There also is a difference between permanent venues, like a football stadium, which have the same problems every weekend (while football isn't being played these stadiums are often used for other things, like concerts) and music festivals that only happen one or two weekends a year, like Coachella. There aren't enough vehicles to support these temporary crowds so vehicles have to be moved into that area. There are dozens of such festivals all over the world, and that's counting just the ones with 50,000 attendees or more, like EDC in Vegas, Glastonbury in UK, etc. So, a company, like a Tesla, which is expected to have humanless vehicles driving in most Western Countries, would need to work with dozens of venues to setup drop off and pick up zones, and with local police to understand how to work with them so that they understand how to work with autonomous vehicles. Once in a while one of those will get stuck, for instance, maybe with a blown tire or an equipment malfunction, or, worse, an accident. At SXSW a drunk driver plowed through crowds of people one year, killing many, and causing a major first-responder response. In such a situation all the constituencies would need to work together to change traffic flows to make sure more vehicles aren't drawn to the area, or interfere with first responders. Is there a relationship lead between all these constituencies? I hear there is not, except in the best of cases. So, this leads to a new job for humans. AI's can't attend city council or meetings with police. AI's can't often figure out why all traffic has stopped. Once, at Half Moon Bay's pumpkin festival it started to rain. Everyone headed for their cars at the same time, but both Waze and Apple Maps continued to give incorrect data for an hour, both on recommendations for what street to head down, and on time it will take to get out of the area. These systems are built for normal traffic flows, and often can't understand that police have even reversed traffic, so that cars are going down the wrong way on a road. Which leads to the AI. Uber's founder, Travis Kalanick, told me his goal is to have one car near someone who is calling for a ride. That way the ride will arrive in less than five minutes and everyone is happy. Uber built a complex "traffic control system" that hooks drivers and passengers up together. That system usually works great, but when high-crowd events show up these systems often mislead drivers and passengers alike. Waymo is, so far, punting, and refuses to go near these events, and has a very small number of passengers today. Even if you live in San Francisco you can't just get a Waymo, you have to wait to be added to the system and they are adding new passengers slowly so that the whole system remains healthy and doesn't hit these large-crowd issues yet. That will change as they scale up the system to be in many more cities over the next few years and open up the system to everyone, not just a limited number of beta testers. So, to wrap it up, soon entrepreneurs, like Elon Musk, who is making plans for bringing its millions of vehicles online to do human-less driving, will need to do new AI modeling work for how cars should behave around high-crowd events, leading to new traffic-control systems to bring thousands of cars in and out of these venues, and will need teams of humans working with venues and cities to build new drop-off-areas for autonomous vehicles to drop off and pick up people. That is a human job, not one that an AI or robot can do. And a company that has aspirations for building a global network of autonomous vehicles, will need many such workers to work with local customs/officials/venues/teams/events. I see very little modeling work, although I saw MIT Media Lab doing some early work to understand how cities would change due to autonomous vehicles, and I don't see anyone in the AI/Autonomous Vehicle industry talking about research/work in this areas. (And yes, I do have a list of those people here on X: https://x.com/scobleizer/lists) I'm doing this post to try to spur industry interest in working on these issues and to connect people who may already be working on them. Are you positioned for these new jobs? If you are, these are fun things to work on and you might even get free tickets to go see concerts or football games for you and your family. I got taken to a Taylor Swift concert by an entrepreneur who built technology systems for the local stadium, so I know it's possible. :-) Technology solves old problems and causes new problems. Which is why I'm still on team human. AI's aren't good at figuring this stuff out and I don't see them getting good at figuring them out, either, for years. Sounds like a good job to have for a while. Here's a new problem, and a new set of jobs for humans, that will be caused as more and more Robotaxis show up (think of an Uber that works without a human in the car). What is the problem? Transportation behavior will change as we get more and more vehicles on the road with no humans inside. Something that's already happening in San Francisco, where you see many autonomous vehicles driving around with no humans inside from companies like Waymo, Zoox, and others. Expected are many others, including Tesla, and GM's Cruise which we hear will be back on the road later this year. The problem? Football stadiums, concerts, basketball stadiums, conferences, events like the Olympics, all will see radically different usage patterns. For instance, today, if you attend a football game, you park in one of dozens of parking lots around the stadium and you walk in, or take a shuttle to one of the entrances. This adds some "randomness" to the flow of crowds in and out and lets city officials who plan out traffic flows bring traffic to those parking lots with a few different routes. Even today it's often a mess with traffic taking an hour to get into many venues with large numbers of people but officials, and others, who work in these industries tell me autonomous vehicles will make traffic far worse. Why? Well, let's assume in five years you are in a Cybertruck taking your family to a football game and that by then the Cybertruck can drive with no humans in the car. Will you want your Cybertruck to take you to a far off parking lot and make you walk to the stadium? No. You'll want it to drop you off near the football stadium. And here's the rub: so will everyone else. Which means you'll have thousands of Waymos, Cruises, Teslas, all trying to get to the same drop-off point. This new human expectation will lead to traffic nightmares. Worse, I've been talking with executives at these kinds of venues and they say the coordination between sports teams, city officials/police, and ride-sharing companies is nearly non-existent.One told me they tried to get Uber and Lyft to come meet with them to design new traffic flows for their vehicles and they just don't get very little help or interest from the ride-sharing companies. One, who works with the 49ers, tells me city officials often put up signs for Uber/Lyft drivers that lead them into dead-end roads where they need to waste time turning around and figuring out where they need to go. Signage, cones, road closures, all could be done in a much better way around venues. And that's before you consider the humans. Often crowds of humans getting out of venues are drunk, don't follow traffic rules, and, sometimes, even turn riotous. Has the autonomous vehicle industry worked with venues to understand how traffic systems change around event venues? No, is the answer I keep hearing, and getting Waymo or Tesla interested in studying the problem together and designing new traffic facilities around big-crowd venues is difficult. Oh, it can happen. At Coachella, for instance, Uber built a huge parking lot with waiting areas for humans that were covered (it's hot often waiting for your ride to show up). Uber also built contextual systems to work with drivers around the Western United States to convince drivers to come to Palm Springs for a month and drive people around (Coachella is two weekends, where 150,000 people visit each weekend, followed by a country music festival that has slightly smaller crowds, but Uber, alone, brings thousands of cars to handle the crowds of people who want to use it to get to and from the venue). Along with the parking lot city officials block off lanes and have clear signs for Uber/Lyft/Taxis to use and have police at every intersection directing traffic and making sure things flow smoothly. Even with all that work it often takes one to three hours of standing in line to get a Taxi or an Uber out of the venue. Now imagine if thousands of people were arriving in autonomous vehicles. If the vehicles weren't programmed into where to go, and if Tesla doesn't have its own drop off and pickup lot things could get nasty, and fast. Last week at NVIDIA's big event my Tesla was programmed to pick up a friend at the Marriott. Problem was it took me down a route that is usually just fine, but during that event NVIDIA and city officials had the street in front of the conference center closed due to the large crowds that were attending that event. My Tesla didn't know about the closed street so it tried to take me down that closed street, figured it out too late, and then got stuck in traffic going on a detour around, wasting 15 minutes. Now 15 minutes doesn't seem like a big deal, but it is if I was driving an Uber passenger. Why? Well, first of all now I have a passenger who isn't happy with the navigation choices the car made, maybe giving me a lower score than I otherwise would get, but, worse, if I was picking up a passenger that person might see that I'm now 15 minutes away instead of two and decide to hop in a cab or cancel my ride. Wasted time, which means if I'm driving an Uber I don't get paid. There also is a difference between permanent venues, like a football stadium, which have the same problems every weekend (while football isn't being played these stadiums are often used for other things, like concerts) and music festivals that only happen one or two weekends a year, like Coachella. There aren't enough vehicles to support these temporary crowds so vehicles have to be moved into that area. There are dozens of such festivals all over the world, and that's counting just the ones with 50,000 attendees or more, like EDC in Vegas, Glastonbury in UK, etc. So, a company, like a Tesla, which is expected to have humanless vehicles driving in most Western Countries, would need to work with dozens of venues to setup drop off and pick up zones, and with local police to understand how to work with them so that they understand how to work with autonomous vehicles. Once in a while one of those will get stuck, for instance, maybe with a blown tire or an equipment malfunction, or, worse, an accident. At SXSW a drunk driver plowed through crowds of people one year, killing many, and causing a major first-responder response. In such a situation all the constituencies would need to work together to change traffic flows to make sure more vehicles aren't drawn to the area, or interfere with first responders. Is there a relationship lead between all these constituencies? I hear there is not, except in the best of cases. So, this leads to a new job for humans. AI's can't attend city council or meetings with police. AI's can't often figure out why all traffic has stopped. Once, at Half Moon Bay's pumpkin festival it started to rain. Everyone headed for their cars at the same time, but both Waze and Apple Maps continued to give incorrect data for an hour, both on recommendations for what street to head down, and on time it will take to get out of the area. These systems are built for normal traffic flows, and often can't understand that police have even reversed traffic, so that cars are going down the wrong way on a road. Which leads to the AI. Uber's founder, Travis Kalanick, told me his goal is to have one car near someone who is calling for a ride. That way the ride will arrive in less than five minutes and everyone is happy. Uber built a complex "traffic control system" that hooks drivers and passengers up together. That system usually works great, but when high-crowd events show up these systems often mislead drivers and passengers alike. Waymo is, so far, punting, and refuses to go near these events, and has a very small number of passengers today. Even if you live in San Francisco you can't just get a Waymo, you have to wait to be added to the system and they are adding new passengers slowly so that the whole system remains healthy and doesn't hit these large-crowd issues yet. That will change as they scale up the system to be in many more cities over the next few years and open up the system to everyone, not just a limited number of beta testers. So, to wrap it up, soon entrepreneurs, like Elon Musk, who is making plans for bringing its millions of vehicles online to do human-less driving, will need to do new AI modeling work for how cars should behave around high-crowd events, leading to new traffic-control systems to bring thousands of cars in and out of these venues, and will need teams of humans working with venues and cities to build new drop-off-areas for autonomous vehicles to drop off and pick up people. That is a human job, not one that an AI or robot can do. And a company that has aspirations for building a global network of autonomous vehicles, will need many such workers to work with local customs/officials/venues/teams/events. I see very little modeling work, although I saw MIT Media Lab doing some early work to understand how cities would change due to autonomous vehicles, and I don't see anyone in the AI/Autonomous Vehicle industry talking about research/work in this areas. (And yes, I do have a list of those people here on X: https://x.com/scobleizer/lists ) https://x.com/scobleizer/lists I'm doing this post to try to spur industry interest in working on these issues and to connect people who may already be working on them. Are you positioned for these new jobs? If you are, these are fun things to work on and you might even get free tickets to go see concerts or football games for you and your family. I got taken to a Taylor Swift concert by an entrepreneur who built technology systems for the local stadium, so I know it's possible. :-) Technology solves old problems and causes new problems. Which is why I'm still on team human. AI's aren't good at figuring this stuff out and I don't see them getting good at figuring them out, either, for years. Sounds like a good job to have for a while.

On The Drop Off and Pick Up Problem for Robotaxis at Crowded Events like Football Games and Concerts

ফুটবল গেমস এবং কনসার্টের মতো ভিড়পূর্ণ ইভেন্টগুলিতে রোবোটক্সির জন্য ড্রপ অফ এবং পিক আপ সমস্যা

Zum Bring- und Abholproblem für Robotertaxis bei überfüllten Veranstaltungen wie Fußballspielen und Konzerten

Πρόβλημα κατά την παράδοση και την παραλαβή για ρομποταξία σε πολυσύχναστες εκδηλώσεις όπως αγώνες ποδοσφαίρου και συναυλίες

Sobre el problema de dejar y recoger a los robotaxis en eventos multitudinarios como partidos de fútbol y conciertos

Բազմամարդ իրադարձությունների ժամանակ, ինչպիսիք են ֆուտբոլային խաղերը և համերգները, ռոբոտաշինգի խնդիրը թողնելու և վերցնելու մասին

Sul problema del ritiro e della consegna dei robotaxi durante eventi affollati come partite di calcio e concerti

サッカーの試合やコンサートなどの混雑したイベントでのロボタクシーの降車・乗車問題について

Robotaxis izlaišanas un uzņemšanas problēma pārpildītos pasākumos, piemēram, futbola spēlēs un koncertos

Problemă de livrare și ridicare pentru Robotaxis la evenimente aglomerate precum jocuri de fotbal și concerte

Dejinta oo u soo qaado dhibta Robotaxis ee Munaasabadaha dadka badan sida Ciyaaraha Kubadda Cagta iyo Riwaayadaha

Kwenye Kuacha na Kuchukua Tatizo kwa Roboteksi kwenye Matukio yenye Watu wengi kama vile Michezo ya Kandanda na Tamasha

Eka The Drop Off and Pick Up Problem for Robotaxis eka Swiendlakalo leswi Taleke ku fana na Mintlangu ya Bolo ya Milenge na Tikhonsati

How to Create a Decentralized Marketplace for Agricultural Products on the Rootstock (RSK)

كيفية إنشاء سوق لامركزي للمنتجات الزراعية على شبكة RSK التجريبية

So erstellen Sie einen dezentralen Marktplatz für Agrarprodukte im RSK-Testnetz

Cómo crear un mercado descentralizado para productos agrícolas en la red de pruebas RSK

Nola sortu Nekazaritza Produktuen Merkatu Deszentralizatua RSK Testnet-en

Comment créer un marché décentralisé pour les produits agricoles sur le réseau de test RSK

RSK テストネット上で農産物の分散型マーケットプレイスを構築する方法

RSK 테스트넷에서 농산물을 위한 분산형 시장을 만드는 방법

Kaip sukurti decentralizuotą žemės ūkio produktų rinką RSK Testnet tinkle

Cum să creați o piață descentralizată pentru produse agricole pe RSK Testnet

Как создать децентрализованную торговую площадку для сельскохозяйственной продукции в тестовой сети RSK

Sida loo Abuuro Goob Suuq ah oo Baahsan oo loogu talagalay Alaabooyinka Beeraha ee RSK Testnet

ከመይ ጌርና ኣብ RSK Testnet ንፍርያት ሕርሻ ዘይተማእከለ ዕዳጋ ንፈጥር

38 Lifehacks From "Tools of Titans" by Tim Ferriss

Creating a Ride-a-request Application Using TomTom Maps API

How to Waste $5000 on Personal Growth

In the realm of cybersecurity, the phrase "the devil is in the details" rings especially true. One of the most compelling examples of this is the capture of the notorious BTK killer, a serial murderer who eluded law enforcement for decades. His eventual downfall was not due to a dramatic confrontation or an eyewitness tip, but rather through the seemingly mundane details found in metadata. This article explores the critical role of metadata in the BTK case and highlights how tools like Metagoofil can be leveraged in modern cybersecurity efforts. The BTK Killer and the Power of Metadata For more than three decades, the police couldn't manage to arrest the BTK killer. However, authorities finally caught Dennis Rader in 2005 while he was driving near his home in Park City. After the killer's arrest, the nation learned about the heinous crimes he had committed over the years. Dennis Rader, known as the BTK killer (Bind, Torture, Kill), terrorized Wichita, Kansas, from 1974 to 1991, committing a series of brutal murders. For years, he managed to evade capture, taunting law enforcement with letters and clues. His confidence grew, leading him to make a critical error that would ultimately expose him. I will not be talking about the BTK killers’ victims. I will be discussing the methodology used to unmask him. In January 2005, Rader left a package for Wichita’s KAKE-TV inside a cereal box, which he placed in the back of a pickup truck in the parking lot of a local Home Depot store. The owner, however, thought it was garbage and threw it out. Rader then contacted the station, asking if they had received the package. It was later found in the trash, and police were able to review security camera footage that showed a person driving a black Jeep Cherokee dropping off the package. In a subsequent message to police, Rader asked them, “Can I communicate with Floppy [disk] and not be traced to a computer? Be honest.” If so, he told police to place an ad in The Wichita Eagle with the message, “Rex, it will be OK." Two weeks later, a disk arrived in a package sent to KSAS-TV with a file that contained instructions to detectives about further communications. What Rader didn’t realize was the disk also contained encrypted metadata that would lead police straight to him. In 2004, Rader resumed communication with the media and the police, sending a floppy disk to a local news station. He believed that erasing files from the disk would cover his tracks. However, investigators were able to extract metadata from the disk, which included a deleted Microsoft Word document. This document contained metadata revealing it had been last edited by a user named "Dennis" on a computer registered to "Christ Lutheran Church." The disk was handed over to Officer Randy Stone of the Wichita Police Department, who was skilled in computer technology. According to The Wichita Eagle, he used a forensic software program to call up deleted files and other hidden data that showed where and when the disk had been last modified. It revealed the disk had been used on a computer at Wichita’s Christ Lutheran Church by a user named “Dennis.” Upon looking up the church's website, they found "Dennis Rader" listed as the president of the congregation. After locating his home address, police drove by and saw a black Jeep Cherokee in his driveway. After matching Dennis Rader’s DNA to evidence found at several of the crime scenes, police arrested him on February 25, 2005. During his interrogation, Rader expressed his anger at police for lying to him about his floppy disk being traceable. “I need to ask you, how come you lied to me? How come you lied to me?” Rader admonished Lieutenant Ken Landwehr, commander of the Wichita Police Department’s homicide unit. “Because I was trying to catch you,” Landwehr replied. This small piece of information provided a crucial lead. Law enforcement cross-referenced this data with local records, leading them to Dennis Rader, a respected member of the community and church president. DNA evidence subsequently confirmed his identity as the BTK killer, ending his reign of terror. What is Metadata? Metadata means "data about data". Metadata is defined as the data providing information about one or more aspects of the data; it is used to summarize basic information about data that can make tracking and working with specific data easier. Some examples include: the Means of creation of the data.
purpose of the data. What information can be revealed with Metadata? The BTK case underscores the significant role metadata can play in forensic investigations. In the digital age, extracting and analyzing metadata is a cornerstone of cybersecurity. Tools like Metagoofil have become invaluable in this effort. Metagoofil is an open-source tool designed to extract metadata from public documents. By scanning files such as PDFs, Word documents, and images, Metagoofil can reveal hidden information about the document’s creation, modification, and authorship. This can include usernames, software versions, file paths, and other details that can be critical in both offensive and defensive cybersecurity operations. Applications of Metagoofil: Penetration Testing: Cybersecurity professionals can use Metagoofil to gather intelligence about a target organization. By analyzing metadata from publicly available documents, they can identify potential vulnerabilities, software in use, and internal file structures.


Incident Response: During a security breach investigation, Metagoofil can help trace the origin of malicious documents or emails. Metadata can reveal the author’s identity, creation dates, and even geographic locations.


Data Leak Prevention: Organizations can use Metagoofil to audit their own documents before they are released to the public. This helps ensure that sensitive information is not inadvertently shared through metadata.


Compliance and Auditing: Regulatory requirements often mandate the tracking of document handling and modification. Metagoofil can assist in compliance efforts by providing detailed metadata reports. The capture of the BTK killer through metadata analysis serves as a powerful reminder of the hidden value in digital footprints. As cybersecurity threats continue to evolve, the ability to unearth and interpret metadata becomes increasingly vital. Tools like Metagoofil equip professionals with the means to uncover these invisible details, bolstering defenses and enhancing investigative capabilities. In a world where every byte can tell a story, mastering the art of metadata analysis is an essential skill for any cybersecurity arsenal. In the realm of cybersecurity , the phrase "the devil is in the details" rings especially true. One of the most compelling examples of this is the capture of the notorious BTK killer, a serial murderer who eluded law enforcement for decades. His eventual downfall was not due to a dramatic confrontation or an eyewitness tip, but rather through the seemingly mundane details found in metadata. This article explores the critical role of metadata in the BTK case and highlights how tools like Metagoofil can be leveraged in modern cybersecurity efforts. cybersecurity The BTK Killer and the Power of Metadata For more than three decades, the police couldn't manage to arrest the BTK killer. However, authorities finally caught Dennis Rader in 2005 while he was driving near his home in Park City. After the killer's arrest, the nation learned about the heinous crimes he had committed over the years. Dennis Rader, known as the BTK killer (Bind, Torture, Kill), terrorized Wichita, Kansas, from 1974 to 1991, committing a series of brutal murders. For years, he managed to evade capture, taunting law enforcement with letters and clues. His confidence grew, leading him to make a critical error that would ultimately expose him. I will not be talking about the BTK killers’ victims. I will be discussing the methodology used to unmask him. I will not be talking about the BTK killers’ victims. I will be discussing the methodology used to unmask him. In January 2005, Rader left a package for Wichita’s KAKE-TV inside a cereal box, which he placed in the back of a pickup truck in the parking lot of a local Home Depot store. The owner, however, thought it was garbage and threw it out. Rader then contacted the station , asking if they had received the package. It was later found in the trash, and police were able to review security camera footage that showed a person driving a black Jeep Cherokee dropping off the package. In Rader then contacted the station showed a person driving a black Jeep Cherokee In a subsequent message to police, Rader asked them , “Can I communicate with Floppy [disk] and not be traced to a computer? Be honest.” If so, he told police to place an ad in The Wichita Eagle with the message, “Rex, it will be OK." Two weeks later, a disk arrived in a package sent to KSAS-TV with a file that contained instructions to detectives about further communications. What Rader didn’t realize was the disk also contained encrypted metadata that would lead police straight to him. Rader asked them In 2004, Rader resumed communication with the media and the police, sending a floppy disk to a local news station. He believed that erasing files from the disk would cover his tracks. However, investigators were able to extract metadata from the disk, which included a deleted Microsoft Word document. This document contained metadata revealing it had been last edited by a user named "Dennis" on a computer registered to "Christ Lutheran Church." The disk was handed over to Officer Randy Stone of the Wichita Police Department, who was skilled in computer technology. According to The Wichita Eagle , he used a forensic software program to call up deleted files and other hidden data that showed where and when the disk had been last modified. It revealed the disk had been used on a computer at Wichita’s Christ Lutheran Church by a user named “Dennis.” Upon looking up the church's website , they found "Dennis Rader" listed as the president of the congregation. After locating his home address, police drove by and saw a black Jeep Cherokee in his driveway. According to The Wichita Eagle the church's website saw a black Jeep Cherokee After matching Dennis Rader’s DNA to evidence found at several of the crime scenes , police arrested him on February 25, 2005. During his interrogation, Rader expressed his anger at police for lying to him about his floppy disk being traceable. “I need to ask you, how come you lied to me? How come you lied to me?” Rader admonished Lieutenant Ken Landwehr , commander of the Wichita Police Department’s homicide unit. “Because I was trying to catch you,” Landwehr replied. This small piece of information provided a crucial lead. Law enforcement cross-referenced this data with local records, leading them to Dennis Rader, a respected member of the community and church president. DNA evidence subsequently confirmed his identity as the BTK killer, ending his reign of terror. several of the crime scenes arrested him Rader admonished Lieutenant Ken Landwehr What is Metadata? Metadata means " data about data ". Metadata is defined as the data providing information about one or more aspects of the data; it is used to summarize basic information about data that can make tracking and working with specific data easier. data about data Some examples include: the Means of creation of the data. purpose of the data. the Means of creation of the data. purpose of the data. What information can be revealed with Metadata? The BTK case underscores the significant role metadata can play in forensic investigations. In the digital age, extracting and analyzing metadata is a cornerstone of cybersecurity. Tools like Metagoofil have become invaluable in this effort. Metagoofil is an open-source tool designed to extract metadata from public documents. By scanning files such as PDFs, Word documents, and images, Metagoofil can reveal hidden information about the document’s creation, modification, and authorship. This can include usernames, software versions, file paths, and other details that can be critical in both offensive and defensive cybersecurity operations. Applications of Metagoofil: Applications of Metagoofil: Penetration Testing: Cybersecurity professionals can use Metagoofil to gather intelligence about a target organization. By analyzing metadata from publicly available documents, they can identify potential vulnerabilities, software in use, and internal file structures. Incident Response: During a security breach investigation, Metagoofil can help trace the origin of malicious documents or emails. Metadata can reveal the author’s identity, creation dates, and even geographic locations. Data Leak Prevention: Organizations can use Metagoofil to audit their own documents before they are released to the public. This helps ensure that sensitive information is not inadvertently shared through metadata. Compliance and Auditing: Regulatory requirements often mandate the tracking of document handling and modification. Metagoofil can assist in compliance efforts by providing detailed metadata reports. Penetration Testing: Cybersecurity professionals can use Metagoofil to gather intelligence about a target organization. By analyzing metadata from publicly available documents, they can identify potential vulnerabilities, software in use, and internal file structures. Penetration Testing: Cybersecurity professionals can use Metagoofil to gather intelligence about a target organization. By analyzing metadata from publicly available documents, they can identify potential vulnerabilities, software in use, and internal file structures. Penetration Testing: Incident Response: During a security breach investigation, Metagoofil can help trace the origin of malicious documents or emails. Metadata can reveal the author’s identity, creation dates, and even geographic locations. Incident Response: During a security breach investigation, Metagoofil can help trace the origin of malicious documents or emails. Metadata can reveal the author’s identity, creation dates, and even geographic locations. Incident Response: Data Leak Prevention: Organizations can use Metagoofil to audit their own documents before they are released to the public. This helps ensure that sensitive information is not inadvertently shared through metadata. Data Leak Prevention: Organizations can use Metagoofil to audit their own documents before they are released to the public. This helps ensure that sensitive information is not inadvertently shared through metadata. Data Leak Prevention: Compliance and Auditing: Regulatory requirements often mandate the tracking of document handling and modification. Metagoofil can assist in compliance efforts by providing detailed metadata reports. Compliance and Auditing: Regulatory requirements often mandate the tracking of document handling and modification. Metagoofil can assist in compliance efforts by providing detailed metadata reports. Compliance and Auditing: The capture of the BTK killer through metadata analysis serves as a powerful reminder of the hidden value in digital footprints. As cybersecurity threats continue to evolve, the ability to unearth and interpret metadata becomes increasingly vital. Tools like Metagoofil equip professionals with the means to uncover these invisible details, bolstering defenses and enhancing investigative capabilities. In a world where every byte can tell a story, mastering the art of metadata analysis is an essential skill for any cybersecurity arsenal.

Solving Crimes with Data: The BTK Killer and the Power of Metadata Analysis

Distributed Ledger Technology (DLT) is often paired with the Internet of Things (IoT) to get some interesting and automatic features in the real world, also registered and handled digitally. IoT devices are physical objects designed to connect to the Internet and can also perform effectively on a distributed network. Blockchains weren’t really built to face challenges like high energy costs or lack of needed speed. A Directed Acyclic Graph (DAG) like Obyte could be a better alternative, allowing inexpensive, fast, secure, and highly decentralized transactions or immutable data recording. In this vein, let’s look into some potential use cases for the powerful combination of IoT and Obyte. Track and Verify Assets The journey of any commodity or asset from its origin (manufacturers) to its final destination (common users) is long and complex, and it could be full of issues in the middle. This is especially true when the safety or authenticity of the product is essential for final consumers, and it could be tampered with before it reaches them. Luckily, decentralized networks can be paired with IoT devices to track and verify any product across the supply chain, assuring its final quality. Sensors and IoT devices can report the status of shipments in real time to a DLT, ensuring that all parties have access to accurate and tamper-proof records. This could be particularly useful for monitoring the transport conditions of perishable goods or high-value items, improving accountability, and reducing losses due to theft, fraud, or damage. Consider, for instance, a pharmaceutical product originating from a manufacturing plant. Each product could have an embedded IoT sensor, generating real-time data about its location, temperature, and humidity levels. As the product leaves the factory, the IoT device logs its status onto the Obyte DAG, ensuring an immutable and transparent record every step of the way. If any anomalies occur, such as temperature fluctuations that could compromise the product's integrity, stakeholders are instantly alerted, allowing for swift corrective actions. Upon arrival at the final destination, perhaps a pharmacy, the product's entire journey is readily accessible on the Obyte DAG, and all its journey could be consulted by accessing a simple QR code printed on its tags. Smart Vehicle Leasing and Sharing It’s also possible to implement a system where vehicles, such as electric scooters, bikes, or cars, can be leased or rented using tokens on a decentralized network like Obyte. Users could unlock and operate these vehicles by scanning a QR code and paying with any compatible tokens, or even creating new ones for this purpose. The vehicle's usage data (e.g., duration, distance traveled) would be recorded on the DAG, ensuring transparency and trust. Human-readable smart contracts and Autonomous Agents (acting like digital vending machines) could manage leases, maintenance schedules, and payments. All of this from the same wallet, maybe even with the help of a chatbot, but with no need for extra middlemen being involved. For example, imagine John wants to rent an electric scooter for a quick ride across town. He opens his Obyte wallet, locates a nearby scooter, and scans its QR code. Instantly, the app prompts him to pay the rental fee using Obyte-based tokens. After confirming the payment, the scooter unlocks, and John starts his journey. As he rides, the scooter's IoT sensors continuously track and record data such as distance traveled and time used onto the Obyte DAG. Upon reaching his destination, John parks the scooter and ends the rental via the same app. The smart contract processes the final payment based on the usage data. Additionally, it could automatically update the scooter’s maintenance schedule based on the recorded usage, ensuring it remains in optimal condition. Decentralized Health Monitoring IoT is widely used in healthcare already, and it includes common devices like wearable fitness trackers and medical sensors. If we pair them with a DAG like Obyte, all of our important medical information could be safely registered digitally, ready to be shared with health providers and researchers only if we decide to do so, when we decide to do so. Let’s consider a scenario like that one. Imagine Sarah is using a wearable fitness tracker to monitor her heart rate and daily activity. This device continuously collects health data and securely records it onto the Obyte DAG. One day, Sarah feels unwell and decides to consult a doctor via a telehealth service. Through her digital wallet, Sarah not only can pay for the consultation, but grant her doctor temporary access to her health records stored on the DAG. Then, the doctor reviews the data in real-time, including heart rate trends and activity levels, aiding in an accurate diagnosis. After the consultation, Sarah revokes access, ensuring her information remains private. This system could provide secure, efficient, and controlled sharing of vital health data. Waste Management System Immense waste and inefficient techniques to handle it are another of our big challenges to improve our environment these days. By using IoT sensors and the Obyte ledger, we could create a new decentralized system to address this issue. Sensors placed in waste bins and recycling containers could monitor fill levels and send data to the DAG. Smart contracts could automate the scheduling of waste collection services based on real-time data, ensuring efficient and timely pickups. Additionally, a new customized token could be created to reward users for proper recycling practices, incentivizing environmentally friendly behavior and improving overall waste management efficiency. In a city aiming to boost recycling efforts, a customized token named ‘RecycleCoin’ (RCC) could be created on Obyte. Residents could be provided with IoT-enabled recycling bins that track the amount and type of waste deposited. When someone recycles his plastic bottles, the bin records the data and automatically logs it onto the Obyte DAG. For every kilogram of recyclables, users would earn RCC, credited to their digital wallet automatically. These tokens could be redeemed for rewards, such as discounts at local stores, or they could acquire real value through free market supply and demand. This system would not only incentivize recycling but also ensure transparent tracking of waste management, fostering a more sustainable community. P2P Clean Energy Another way to help the environment through IoT and Obyte, and reduce our electrical bills in the process, could be peer-to-peer (P2P) energy trading. Households or businesses with surplus energy generated from renewable sources like solar panels could sell excess energy directly to other consumers in their local grid. IoT devices would measure the amount of energy produced and consumed, recording this data on the DAG. Smart contracts can facilitate automatic and transparent transactions based on real-time energy usage, ensuring that producers are paid promptly and consumers are charged fairly. This way, we could optimize energy distribution, reduce reliance on traditional energy suppliers, and promote the use of renewable energy sources. **  **If we went to put it into practice, let’s say that Alice’s home, equipped with IoT devices, measures her solar energy production and usage, recording this data on the Obyte ledger. One sunny afternoon, Alice's panels produce more energy than her household consumes. The IoT platform would automatically log the surplus energy onto the DAG and make it available for sale. Down the street, if Mike needs extra energy for his home office, his own IoT system and Obyte wallet could detect the availability and purchase Alice's excess energy via smart contract. The provider would be promptly paid and Mike would be fairly charged. All these examples highlight just a fraction of the immense possibilities that emerge when combining Obyte with connected devices, paving the way for innovative solutions across numerous sectors where they could enhance efficiency, security, and user experience in unprecedented ways. Featured Vector Image by vectorjuice / Freepik Distributed Ledger Technology (DLT) is often paired with the Internet of Things (IoT) to get some interesting and automatic features in the real world, also registered and handled digitally. IoT devices are physical objects designed to connect to the Internet and can also perform effectively on a distributed network. Distributed Ledger Technology (DLT) Blockchains weren’t really built to face challenges like high energy costs or lack of needed speed. A Directed Acyclic Graph (DAG) like Obyte could be a better alternative , allowing inexpensive, fast, secure, and highly decentralized transactions or immutable data recording. Obyte could be a better alternative Obyte could be a better alternative In this vein, let’s look into some potential use cases for the powerful combination of IoT and Obyte. Track and Verify Assets The journey of any commodity or asset from its origin (manufacturers) to its final destination (common users) is long and complex, and it could be full of issues in the middle. This is especially true when the safety or authenticity of the product is essential for final consumers, and it could be tampered with before it reaches them. Luckily, decentralized networks can be paired with IoT devices to track and verify any product across the supply chain, assuring its final quality. Luckily, decentralized networks can be paired with IoT devices to track and verify any product across the supply chain, assuring its final quality. Sensors and IoT devices can report the status of shipments in real time to a DLT, ensuring that all parties have access to accurate and tamper-proof records. This could be particularly useful for monitoring the transport conditions of perishable goods or high-value items, improving accountability, and reducing losses due to theft, fraud, or damage. Consider, for instance, a pharmaceutical product originating from a manufacturing plant. Each product could have an embedded IoT sensor, generating real-time data about its location, temperature, and humidity levels . As the product leaves the factory, the IoT device logs its status onto the Obyte DAG , ensuring an immutable and transparent record every step of the way. Each product could have an embedded IoT sensor, generating real-time data about its location, temperature, and humidity levels Obyte DAG Obyte DAG If any anomalies occur, such as temperature fluctuations that could compromise the product's integrity, stakeholders are instantly alerted, allowing for swift corrective actions. Upon arrival at the final destination, perhaps a pharmacy, the product's entire journey is readily accessible on the Obyte DAG, and all its journey could be consulted by accessing a simple QR code printed on its tags. Smart Vehicle Leasing and Sharing It’s also possible to implement a system where vehicles, such as electric scooters, bikes, or cars, can be leased or rented using tokens on a decentralized network like Obyte. Users could unlock and operate these vehicles by scanning a QR code and paying with any compatible tokens, or even creating new ones for this purpose. The vehicle's usage data (e.g., duration, distance traveled) would be recorded on the DAG, ensuring transparency and trust . Human-readable smart contracts and Autonomous Agents (acting like digital vending machines ) could manage leases, maintenance schedules, and payments. All of this from the same wallet, maybe even with the help of a chatbot, but with no need for extra middlemen being involved. The vehicle's usage data (e.g., duration, distance traveled) would be recorded on the DAG, ensuring transparency and trust Human-readable smart contracts Human-readable smart contracts vending machines vending machines For example, imagine John wants to rent an electric scooter for a quick ride across town. He opens his Obyte wallet, locates a nearby scooter, and scans its QR code. Instantly, the app prompts him to pay the rental fee using Obyte-based tokens. After confirming the payment, the scooter unlocks, and John starts his journey. As he rides, the scooter's IoT sensors continuously track and record data such as distance traveled and time used onto the Obyte DAG. Upon reaching his destination, John parks the scooter and ends the rental via the same app. The smart contract processes the final payment based on the usage data. Additionally, it could automatically update the scooter’s maintenance schedule based on the recorded usage, ensuring it remains in optimal condition. As he rides, the scooter's IoT sensors continuously track and record data such as distance traveled and time used onto the Obyte DAG. Decentralized Health Monitoring Decentralized Health Monitoring IoT is widely used in healthcare already, and it includes common devices like wearable fitness trackers and medical sensors. If we pair them with a DAG like Obyte, all of our important medical information could be safely registered digitally, ready to be shared with health providers and researchers only if we decide to do so, when we decide to do so. all of our important medical information could be safely registered digitally, ready to be shared with health providers and researchers only if we decide to do so, when we decide to do so. Let’s consider a scenario like that one. Imagine Sarah is using a wearable fitness tracker to monitor her heart rate and daily activity. This device continuously collects health data and securely records it onto the Obyte DAG. One day, Sarah feels unwell and decides to consult a doctor via a telehealth service. Through her digital wallet , Sarah not only can pay for the consultation, but grant her doctor temporary access to her health records stored on the DAG. digital wallet digital wallet Then, the doctor reviews the data in real-time, including heart rate trends and activity levels, aiding in an accurate diagnosis. After the consultation, Sarah revokes access, ensuring her information remains private. This system could provide secure, efficient, and controlled sharing of vital health data. Waste Management System Waste Management System Immense waste and inefficient techniques to handle it are another of our big challenges to improve our environment these days. By using IoT sensors and the Obyte ledger, we could create a new decentralized system to address this issue. Sensors placed in waste bins and recycling containers could monitor fill levels and send data to the DAG. Sensors placed in waste bins and recycling containers could monitor fill levels and send data to the DAG. Smart contracts could automate the scheduling of waste collection services based on real-time data, ensuring efficient and timely pickups. Additionally, a new customized token could be created to reward users for proper recycling practices, incentivizing environmentally friendly behavior and improving overall waste management efficiency. In a city aiming to boost recycling efforts, a customized token named ‘RecycleCoin’ (RCC) could be created on Obyte. Residents could be provided with IoT-enabled recycling bins that track the amount and type of waste deposited. When someone recycles his plastic bottles, the bin records the data and automatically logs it onto the Obyte DAG. In a city aiming to boost recycling efforts, a customized token named ‘RecycleCoin’ (RCC) could be created on Obyte. a customized token a customized token For every kilogram of recyclables, users would earn RCC, credited to their digital wallet automatically. These tokens could be redeemed for rewards, such as discounts at local stores, or they could acquire real value through free market supply and demand. This system would not only incentivize recycling but also ensure transparent tracking of waste management, fostering a more sustainable community. P2P Clean Energy P2P Clean Energy Another way to help the environment through IoT and Obyte, and reduce our electrical bills in the process, could be peer-to-peer (P2P) energy trading. Households or businesses with surplus energy generated from renewable sources like solar panels could sell excess energy directly to other consumers in their local grid. IoT devices would measure the amount of energy produced and consumed, recording this data on the DAG. help the environment help the environment Smart contracts can facilitate automatic and transparent transactions based on real-time energy usage, ensuring that producers are paid promptly and consumers are charged fairly . This way, we could optimize energy distribution, reduce reliance on traditional energy suppliers, and promote the use of renewable energy sources. Smart contracts can facilitate automatic and transparent transactions based on real-time energy usage, ensuring that producers are paid promptly and consumers are charged fairly ** **If we went to put it into practice, let’s say that Alice’s home, equipped with IoT devices, measures her solar energy production and usage, recording this data on the Obyte ledger. One sunny afternoon, Alice's panels produce more energy than her household consumes. The IoT platform would automatically log the surplus energy onto the DAG and make it available for sale. Down the street, if Mike needs extra energy for his home office, his own IoT system and Obyte wallet could detect the availability and purchase Alice's excess energy via smart contract. The provider would be promptly paid and Mike would be fairly charged. The IoT platform The IoT platform All these examples highlight just a fraction of the immense possibilities that emerge when combining Obyte with connected devices , paving the way for innovative solutions across numerous sectors where they could enhance efficiency, security, and user experience in unprecedented ways. All these examples highlight just a fraction of the immense possibilities that emerge when combining Obyte with connected devices Featured Vector Image by vectorjuice / Freepik Featured Vector Image by vectorjuice / Freepik Freepik Freepik

5 Ways to Leverage Obyte and IoT Technology for Innovative Solutions

HackerNoon launches our long-awaited offering: Technology Press Releases with HackerNoon! You can now leverage HackerNoon’s distribution engine to share your press releases! Leveraging prominent onsite and newsletter distribution, owned and paid social media, traditional media press release pickup, and machine learning-generated translations, HackerNoon now averages 5k readers per press release. Visit our Technology Press Releases home page to learn more. The introductory prices start at $750 per release, and bulk discounts are available. There is no expiration date for your Press Release credits. Avail the Introductory Pricing for Your Press Release Now. Why Publish Your Company’s Technology Press Releases with HackerNoon? Great question. Here are not one but 8 reasons why: Technical Achievements Are Best Hosted with a Technical Audience HackerNoon is the go-to tech news and learning platform for millions of technologists. Our library of 100k+ technology stories attracts 3M+ monthly visitors. See below the data gathered from 1k+ job titles entered via HackerNoon.com in Q1 2024. Accessibility: Translated into 12 Languages, 2 Audio Files, and Backed Up on the Blockchain HackerNoon makes content more accessible to increase audience size. Via machine learning models from OpenAI, Google, & others, we translate your story into 12+ languages, 2 audio files and back it up on the Arweave blockchain for good measure. Distribution Across HackerNoon and Around the Web Via owned and paid social media, traditional media like press releases, machine learning generated translations, and the creation and distribution of the audio story, HackerNoon maximizes technology readership. Creating an Average of 5k Readers Per Press Release We’ve used the traditional press release services, and they usually get just a couple hundred readers per story. Sometimes even less. When you publish your technology press release on HackerNoon, you should expect ~5k readers. Republished on the Wire to 100+ Traditional Media Sites Just like the traditional press release wire services, we put your story on the wire. You should expect your technology press release to be re-published to ~100 more sites, such as Benzinga, Digital Journal, Yahoo Finance, and The AP. Prominent Distribution Across the HackerNoon Site, App, and Newsletter Technology Press Releases on HackerNoon are featured on the Homepage, the Category Page, 8 Tagged Pages, 12 Translation Homepages, the Mobile App, the Terminal App, the Lite Version, and the Noonification Newsletters (250k+ subscribers). Easy Content Uploading and Formatting with Staff Support We hate how difficult it is to upload content to archaic press release distribution services. The HackerNoon uploader and story editor are smooth AF. We also accept your submissions via unlisted link like Google doc or even a URL like your pressroom. 1 Business Day Turnaround Time (TAT) and Professional Editorial Support Technology press releases are timely content. Our editorial and support staff guarantee one business day turnaround time. HackerNoon is here to make sure your story gets distributed on time. Book a meeting with us to learn how Octopus Network, KuCoin Community Chain, Avalanche, ICON Foundation, and other tech companies publish their press releases with HackerNoon. HackerNoon launches our long-awaited offering: Technology Press Releases with HackerNoon! You can now leverage HackerNoon’s distribution engine to share your press releases! Leveraging prominent onsite and newsletter distribution, owned and paid social media, traditional media press release pickup, and machine learning-generated translations, HackerNoon now averages 5k readers per press release. Visit our Technology Press Releases home page to learn more. Technology Press Releases home page The introductory prices start at $750 per release , and bulk discounts are available. There is no expiration date for your Press Release credits. $750 per release Avail the Introductory Pricing for Your Press Release Now. Avail the Introductory Pricing for Your Press Release Now. Avail the Introductory Pricing for Your Press Release Now. Why Publish Your Company’s Technology Press Releases with HackerNoon? Great question. Here are not one but 8 reasons why: Technical Achievements Are Best Hosted with a Technical Audience HackerNoon is the go-to tech news and learning platform for millions of technologists. Our library of 100k+ technology stories attracts 3M+ monthly visitors. See below the data gathered from 1k+ job titles entered via HackerNoon.com in Q1 2024. HackerNoon.com Accessibility: Translated into 12 Languages, 2 Audio Files, and Backed Up on the Blockchain HackerNoon makes content more accessible to increase audience size. Via machine learning models from OpenAI, Google, & others, we translate your story into 12+ languages, 2 audio files and back it up on the Arweave blockchain for good measure. Distribution Across HackerNoon and Around the Web Via owned and paid social media, traditional media like press releases, machine learning generated translations, and the creation and distribution of the audio story, HackerNoon maximizes technology readership. Creating an Average of 5k Readers Per Press Release We’ve used the traditional press release services, and they usually get just a couple hundred readers per story. Sometimes even less. When you publish your technology press release on HackerNoon, you should expect ~5k readers. Republished on the Wire to 100+ Traditional Media Sites Just like the traditional press release wire services, we put your story on the wire. You should expect your technology press release to be re-published to ~100 more sites, such as Benzinga, Digital Journal, Yahoo Finance, and The AP. Prominent Distribution Across the HackerNoon Site, App, and Newsletter Technology Press Releases on HackerNoon are featured on the Homepage, the Category Page, 8 Tagged Pages, 12 Translation Homepages, the Mobile App, the Terminal App, the Lite Version, and the Noonification Newsletters (250k+ subscribers). Easy Content Uploading and Formatting with Staff Support We hate how difficult it is to upload content to archaic press release distribution services. The HackerNoon uploader and story editor are smooth AF. We also accept your submissions via unlisted link like Google doc or even a URL like your pressroom. 1 Business Day Turnaround Time (TAT) and Professional Editorial Support Technology press releases are timely content. Our editorial and support staff guarantee one business day turnaround time. HackerNoon is here to make sure your story gets distributed on time. Book a meeting with us to learn how Octopus Network , KuCoin Community Chain , Avalanche, ICON Foundation , and other tech companies publish their press releases with HackerNoon. Book a meeting with us Book a meeting with us Octopus Network Octopus Network KuCoin Community Chain KuCoin Community Chain ICON Foundation ICON Foundation

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