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Ai Cyberthreats using : Deepfake technology
1. What is Deepfake Ai?
Deepfake ai is fake media (images, videos, audios) created using generative adversarial Networks (GAN) Ai models. These models can create realistic person’s face,voice,expressions.Cyber offenders often misuse them.

Statistics:
Deepfake frauds have increased by over 600% in 2024. Synthetic identity fraud is among the fastest growing financial crime category. Deepfake has caused fraud losses of 200 million dollars. Some single corporates have reported a loss of 25 million dollars. Many business report upto 50% damage and still exposure to deepfake attack.
A women in India lost 33 lakhs after watching deepfake video of Nirmal Sitaram endorsing fake trading platform.
2. Types of deepfake Ai Threats
A: Deep phishing/vishing attacks
– Hackers can clone company manager’s or CEO’s voice and conduct vishing attacks. They can conduct unauthorized bank transfers.
B- political manipulation:
– videos can be used to spread false information, interfere with political agendas or spread false information on social media.
C: Identity theft:
– Cyber Offenders can create fake videos and use for KYC related frauds. Fake KYC videos can be used to open synthetic bank accounts.
– Fake images and videos can be used to bypass facial recognition systems.
D: Cyber extortion
– Fake videos of victims in compromising positions are created. Offenders balckmail victims for money and reputation damage. Many celebrities, women are victims of this.
3. Industries at risk:
– e-commerce
– Banking and financial institutes
– Governments
– corporate enterprises
– Media and entertainment
4. Technical angle of how attack works?
– Victim’s data is collected using social media and profiling.
– Ai models are trained using collected data.
– attacks are conducted using social media, Im apps such as whats app, telegram.

5. How to identify deepfake content?
– unusual shadows or lightining around face
– Distortion in face or image
– Robotics unnatural voice tone
– lip sync mismatch

6. Prevention:
– Dont trust urgent financial calls
– use Multi factor authentication
– Have a secondary channel for video or audio verification
– Use Ai detection tools
– periodically conduct employee awareness trainings
Ethical and legal concerns:
– There should be strong Deepfake regulation countries
– It is very challenging to prove authenticity in the court
– It has caused privacy violation, defamation and harrassment
In future we may face threats such as fraud automation powered using Ai. It also may become harder to detect frauds. It will create a state of Ai vs Ai cybersecurity battle. Deepfake Ai is a double edge sword. Ai detection systems,strong security policies are essential to combat the growing threat.