Be warned: Deepfakes are on increase in attacking financial institutions

GENERATIVE Artificial Intelligence or GenAI has been a useful tool for people to create new content, such as text, images, and or music, by learning the patterns from vast datasets.

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The creation of deepfakes by using GenAI-assisted tools has been easy, cheap, and accessible to everyone

Quite different from the traditional AI that analyses or categorises existing data, GenAI models produce novel and original output in response to prompts of users. This is achieved through complex algorithms that predict what the next word, sound or pixel should be, and that prediction is based on the past patterns. Therefore, it still cannot accommodate the unexpected or events that happens at random. However, it has applications ranging from content creation for easy learning or effective marketing to medical research where it can be used for drug discovery, clinical trials, or biomarker identification for diseases. Thus, users have been able to create new texts, images, audios, and videos which can be used for productive purposes. However, its free availability has helped misusers to create content for ulterior purposes like penetrating the security measures of financial institutions and robbing the moneys of bank customers. One such use has been the creation of fabricated images, videos, or audios of a person saying or doing something which he never did. In the parlance of industry, this is known as ‘deepfake’ creations. These forged creations can be used for malicious purposes like spreading misinformation, creating contents involving disinformation, committing financial frauds, or simply defaming the character of known personalities.

Third, fraud is getting more sophisticated and more accessible to potential scammers. The sophistication has come from the use of GenAI, proliferation of deepfake videos, and techniques like injection attacks. In injection attacks, the scammer sends malicious data to an application, causing it to execute commands or reveal aunauthorised data. This happens when an application fails to properly validate or sanitise user input, allowing specially crafted data to be interpreted as code.