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| 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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