In this era transformed by AI, questions about what is real and how to protect ourselves from the fake have never been more complex. Today, a single phone app can produce deepfakes in a matter of seconds, a process that once required powerful computers and lengthy processing times. Deepfakes are no longer limited to large machines, nor is the threat confined to politicians; it is now permeating our daily lives. In addition, visual voice cloning, face cloning, fake videos, and identity-based fraud have become real security concerns for both individuals and companies. So how do we defend ourselves in this new reality? 1) The reality crisis from the consumer's perspective: ‘Am I the real me, or am I a digital copy? 1) The reality crisis from the consumer's perspective: ‘Am I the real me, or am I a digital copy? Deepfake technology has its greatest impact on people through identity theft, and it is becoming increasingly commonplace. It is no longer just fake videos on social media; even a few seconds of voice recording can create a convincing scam under the pretext of an emergency. Moreover, the real challenge for consumers is not so much the deepfake itself, but the fatigue of trying to verify it. The constant pressure to verify weakens the defence reflex, creating an ideal environment for attackers. 2) Expanding attack surface for companies 2) Expanding attack surface for companies As deepfake technology advances, companies must defend themselves not only against external attacks but also against manipulations targeting their internal operations. Scenarios where managers' voices are imitated to demand ‘urgent payments’ are no longer surprising. Fake product announcements, manipulative videos, and even innocent content shared by employees can provide data for face/voice cloning, increasing the reputation risk for brands. As security teams, we now have to monitor not only data leaks but also reality manipulation. 3) Why are voice imitation and video cloning now more dangerous? 3) Why are voice imitation and video cloning now more dangerous? New generation AI models don't just copy faces. They also incorporate facial expressions, micro-expressions, speech rhythm, breathing, and even voice vibrations. This makes fake content not just ‘difficult to distinguish’ but sometimes impossible to detect. As a result, attacks become faster, more effective, and more convincing. 4) Phishing attacks are at a new level: So what are we going to do? 4) Phishing attacks are at a new level: So what are we going to do? The era of classic ‘click the link’ traps is over; now there are multi-layered phishing attacks that mimic your voice, create panic, and direct you via video. The defence reflex for individuals now consists of a few simple but critical steps. Establishing a security word to be used among family and close friends easily thwarts the panic scenarios created by attackers through voice imitation. In addition, the approach of ‘wait two minutes and verify from a different source’ for any urgent request involving money, passwords, or personal information is one of the simplest yet most effective security measures in the age of deepfakes. Switching to a video call when a voice request is received immediately exposes most attackers, as the tools used do not yet support real-time video manipulation at the same speed. Verifying suspicious messages through a second channel is one of the strongest safeguards for individual security. For companies, the issue requires more structural resilience. Not using voice authentication alone, introducing dual signature and video verification mechanisms for administrative processes significantly reduces fraud risk. It is critically important for employees to receive regular deepfake awareness training using real examples (especially in finance, human resources, and operations teams). Against internal threats, anomaly detection systems that monitor behaviour and access patterns are essential. For companies, the issue requires more structural resilience. Not using voice authentication alone, introducing dual signature and video verification mechanisms for administrative processes significantly reduces fraud risk. It is critically important for employees to receive regular deepfake awareness training using real examples (especially in finance, human resources, and operations teams). Against internal threats, anomaly detection systems that monitor behaviour and access patterns are essential. 5) Post-quantum era: How will the threat evolve? 5) Post-quantum era: How will the threat evolve? The proliferation of quantum computers will make deepfake production both faster and more realistic. At the same time, since many encryption methods we consider secure today will not be resistant to quantum computers, identity verification systems will also need to be fundamentally redesigned. Preparing for this era is no longer a technology choice; it is a mandatory part of security strategy. So what should be done for a quantum-secure infrastructure? Prepare for post-quantum cryptography: Organisations need to create a roadmap today for transitioning to quantum-resistant algorithms recommended by NIST. Due to the ‘catch today, break tomorrow’ model, even data stored today will be at risk in the future.
Strengthen critical systems: VPN, TLS, electronic signatures, certificates, and identity management solutions must be updated with quantum-resistant protocols.
Using hybrid cryptography: During the transition, classical + quantum-resistant cryptography should be used together; this will reduce operational risk.
Adding new layers to authentication: As voice or face alone will not be sufficient, stronger methods such as hardware keys, device-based authentication, and behavioural biometrics will come into play.
Simplify data management: The greatest risk in the quantum era is storing unnecessary data. Shortening data lifecycles reduces the attack surface for both individuals and organisations. Prepare for post-quantum cryptography: Organisations need to create a roadmap today for transitioning to quantum-resistant algorithms recommended by NIST. Due to the ‘catch today, break tomorrow’ model, even data stored today will be at risk in the future. Strengthen critical systems: VPN, TLS, electronic signatures, certificates, and identity management solutions must be updated with quantum-resistant protocols. Using hybrid cryptography: During the transition, classical + quantum-resistant cryptography should be used together; this will reduce operational risk. Adding new layers to authentication: As voice or face alone will not be sufficient, stronger methods such as hardware keys, device-based authentication, and behavioural biometrics will come into play. Simplify data management: The greatest risk in the quantum era is storing unnecessary data. Shortening data lifecycles reduces the attack surface for both individuals and organisations. In the post-quantum era, the deepfake threat will grow not only through more sophisticated fake content but also through the increasing vulnerability of fundamental security infrastructures. Therefore, the steps taken today will form the basis for tomorrow's reality and identity security. In the post-quantum era, the deepfake threat will grow not only through more sophisticated fake content but also through the increasing vulnerability of fundamental security infrastructures. Therefore, the steps taken today will form the basis for tomorrow's reality and identity security. 6) How can we distinguish the real from the fake? 6) How can we distinguish the real from the fake? In the age of deepfakes, there is still no definitive solution. However, a three-tiered approach is increasingly becoming the standard for protecting the truth: technology, behaviour and structure. 1. Technological layer: Proving the source of content 1. Technological layer: Proving the source of content New-generation security technologies focus on verifying where content comes from and who produced it, rather than the content itself. On-device authenticity detection
Digital signatures and provenance tags in content production
Content chain verification between platforms On-device authenticity detection Digital signatures and provenance tags in content production Content chain verification between platforms These systems are not flawless, but they add a security layer that solves the verification process at the infrastructure level, without leaving it to the consumer. 2. Behavioural layer: Verification reflex 2. Behavioural layer: Verification reflex Today, the most effective defence is not technology; it is our behaviour. Today, the most effective defence is not technology; it is our behaviour. If a piece of content triggers your emotions (anger, panic, urgency), stop and think.
Do not trust a single source; get into the habit of verifying through a second channel.
Choose a fixed method with your family and friends to verify when a suspicious call or message arrives: a code word, a question the other party must answer, or a second communication channel. If a piece of content triggers your emotions (anger, panic, urgency), stop and think. Do not trust a single source; get into the habit of verifying through a second channel. Choose a fixed method with your family and friends to verify when a suspicious call or message arrives: a code word, a question the other party must answer, or a second communication channel. The goal is not to identify the truth immediately, but to be able to stop before being misled. The goal is not to identify the truth immediately, but to be able to stop before being misled. 3. Structural layer: Corporate and legal awareness 3. Structural layer: Corporate and legal awareness Corporate defence is not just the job of security teams; it requires a framework of awareness throughout the organisation. Companies should conduct regular deepfake scenarios and drills for employees.
Regulations should focus on adapting existing criminal definitions to the digital context and making them enforceable, rather than creating new prohibitions.
States should move towards storing less and more secure data, rather than collecting more data. Companies should conduct regular deepfake scenarios and drills for employees. Regulations should focus on adapting existing criminal definitions to the digital context and making them enforceable, rather than creating new prohibitions. States should move towards storing less and more secure data, rather than collecting more data. In the age of deepfakes, our strongest defence is not technology; it is the reflex to ask the right question at the right time: ‘Did this really happen, or is it just meant to appear that way?’
In an era where reality can be easily manipulated, security is becoming a combination of behaviour, awareness and institutional intelligence, rather than algorithms or software. In short: Deepfakes are new, but the way to overcome them is familiar: stay calm, verify and apply multiple checks. In the age of deepfakes, our strongest defence is not technology; it is the reflex to ask the right question at the right time: ‘Did this really happen, or is it just meant to appear that way?’ In an era where reality can be easily manipulated, security is becoming a combination of behaviour, awareness and institutional intelligence, rather than algorithms or software. In short: Deepfakes are new, but the way to overcome them is familiar: stay calm, verify and apply multiple checks.

This story contains new, firsthand information uncovered by the writer.

The is an opinion piece based on the author’s POV and does not necessarily reflect the views of HackerNoon.

How Will We Distinguish Truth From Fiction?

About Author

Comments

TOPICS

THIS ARTICLE WAS FEATURED IN

Related Stories

OpenAI Aardvark and The New Wave of Autonomous Security Research

The Noonification: Use This 7-Step McKinsey Framework to Solve Any Problem (1/10/2023)

The Noonification: A Taxonomy of Inclusiveness (1/11/2024)

The Noonification: What is the InfiniteNature-Zero AI Model? (11/19/2022)

10 Ways AI Has Changed Our Lives

100 Days of AI, Day 8: Experimenting With Microsoft's Semantic Kernel Using GPT-4

OpenAI Aardvark and The New Wave of Autonomous Security Research

The Noonification: Use This 7-Step McKinsey Framework to Solve Any Problem (1/10/2023)

The Noonification: A Taxonomy of Inclusiveness (1/11/2024)

The Noonification: What is the InfiniteNature-Zero AI Model? (11/19/2022)

10 Ways AI Has Changed Our Lives

100 Days of AI, Day 8: Experimenting With Microsoft's Semantic Kernel Using GPT-4

Light-Mode

Classic

Newspaper

Minty

Dark-Mode

Neon Noir

Minty

HN StartUps