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How to prevent deep fakes in the era of generative AI?

Cybersecurity consultants
cyber security consultant

The fight against misinformation has always been challenging. In recent years, there has been a sharp rise in the manipulation of content using AI, resulting in several deep fakes and misinformation cases. As a worrying scenario, AI has been largely misused to create fake news at a much faster pace. It has been more so with the ever-growing advancements in the AI field, causing financial as well as reputational damages.

The consequences of AI-generated fake content could be vindictive. It could lead to a well-planned dissemination of misinformation. It could also promote cyberattacks. The AI-generated content could be used by the hackers to create personalized spam messages or images with encapsulated dangerous code(s). This problem has been recognized globally by cyber security consultants and is the cause of major concern.

Furthermore, the deep fakes could also lead to an alarming increase in unethical practices such as plagiarism and intellectual property misuse.AI technologies such as deep learning and computer vision are the main driving forces responsible for spreading deep fakes and image manipulation algorithms.

Although preventing deep fakes can be a challenging task, some measures are definitely required to reduce the risk. At the elementary level, fake content can be detected and flagged for review by creating better detection systems. The researchers are helping the engineers create advanced algorithms to detect deep fakes with accuracy. The efforts are also made to involve machine learning models in training. These models will enable effective recognition between a real and a fake video.

Yet another effort to curb this menace could be to increase awareness. The potential risks must be addressed to avoid such content creation. This can be achieved through cybersecurity workshops, social media awareness, and related media campaigns. Next, various trustworthy sources, like identity verification systems, could be developed to promote and encourage the use of reliable sources. For example, news and other media-related information. As a progressive solution, identifying and endorsing reputable media outlets must be established, ensuring a thorough fact-check of the information.

The use of watermarks and digital signatures provides a unique attribute to the content, thereby enabling and verifying content authenticity and preventing data tampering. Also, efforts are being made to build ethical AI models. These models are not only transparent but explainable and unbiased too, preventing the malicious use of AI technology.

As a security measure, blockchain (a distributed ledger) can also be an effective enabler to store data online. This can be done without involving the centralized server(s). Unlike centralized servers, blockchains are supposedly tougher against various security threats due to hashes and digital signatures. For example, individuals could digitally sign and affirm the authenticity of a video or audio document. As the number of individuals acknowledges and add the digital signature, the probability of the video being real also increases. But additional processes must accompany the blockchain to authenticate the individuals acknowledging the video.

Last but not least, legal measures must be made stricter and significant enough to handle these cases. The seriousness of the issue must be identified, and effective measures must be taken against deep faking and/or forged voice recordings. This can be achieved by penalizing and imposing substantial fines to ensure that the information as well as individual security are not compromised.

Self-regulatory measures by organizations in accordance with the global regulation processes are the need of the hour. There has to be a coordinated effort by the cyber security consulting firms to maintain a continuous pace with the advances in AI and curb the issue. Thus, a combination of technological solutions and user awareness can ensure the prevention of deep fakes in the era of generative AI.

 


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