Deepfakes: One of the Cybersecurity threats driven by AI

Deepfakes when powered by AI can change images, audios as well as videos to create fabrications that cannot be differentiated from the original ones. According to various research, generative adversarial networks (GANs) as well as AI algorithms are used to create these fake versions of the original. Deepfakes are a serious cybersecurity threat and everyone should be concerned by its evolution as it is capable of damaging individual reputation as well as reducing consumer trust in media as well as digital content. This damaged reputation can lead to job loss or lead to legal implications.

Asides from the reduction of trust in digital content which is vastly caused by the emergence of AI and evolution of deepfakes; deepfake technology can also be leveraged on by cybercriminals to gain access to confidential information and sensitive data alongside damaging an individuals reputation. Other than this, deepfakes powered by AI can be used by criminals to create fake videos for example of government officials- showing such officials as engaging in inappropriate behaviour which can attract disciplinary action. They can also be used to impersonate the voice as well as the image of high profile individuals - to commit crime.  Powered by AI, deepfakes have become more sophisticated and has the capability to undermine the media and reduce its credibility. They can fast become a tool for blackmail, impersonation and identity theft leading to the loss of information integrity, the spread of misleading information, the tarnishing of individual image and the manipulation of data.

Tools will be needed to help trace the origin of deepfakes as they are a fast evolving cybersecurity threat. Identifying and analysing the patterns with deepfakes, detecting wrong patterns with facial expressions as well as detecting patterns with voice are a few of the complexities these tools need to be able to solve. Already existing tools such as phishing detection tools for example have been proven not to be sophisticated and robust enough to combat the problems created by deepfakes since deepfakes usually appear highly convincing.

In order to be able to combat the rapid advancement of deepfakes; organisations, machine learning experts, cybersecurity experts as well as policy and lawmakers need to collaborate and work together to ensure that the integrity of the medias and digital content is preserved. Users also need to be aware, vigilant as well as educated about the evolvement of deepfakes and the damage it can cause.