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It is no hidden fact that cyberattacks are getting more nuanced day in and day out. One of the latest technology-based cyber threats looming over is deepfakes. The word “deepfake” can be broken down into “deep,” meaning it uses deep learning, and “fake” because the content of the picture, audio, or video generated is computerized by specialized algorithms and is not real. The most common deepfake content generated is when a person’s facial image has been swapped with someone else.





Deepfakes differ from altered videos or photoshopped images because they can be created with minimal effort using GAN (Generative Adversarial Networks). Based on the data provided, GANs produce image replicas using machine learning. Deepfakes are generated in two phases - the training phase, in which the initial image manipulation is dealt with, and the testing phase, in which an image is warped over something, creating an image the cybercriminal is looking for.


Deepfakes are becoming a significant threat to companies even though the technology isn’t refined or perfected yet. As this is an emerging threat, there is no foolproof countermeasure for data security against it. However, there are certain protective measures a company can implement to protect itself by reducing the threat of a deepfake disruption.


How To Prevent Deepfake Disruption

Deepfakes can try to extort information, such as sensitive data or money, by deceiving the user using AI-generated content. Companies need to stay vigilant against it, and they can do so by:


1.     Integrating Detection Technology

Businesses can protect their data security from deepfake attacks by using automated technology to detect them. Using AI-integrated software for detection is a feasible solution. The deep learning algorithms used to train deepfake can also be used to train a threat detection technology to help locate any altercation in an image or a video. Intelligent threat detection will analyze the entire altered content to identify any malicious activity that can breed from it. Cybersecurity professionals can take the required corrective actions if an altercation is detected.


2.     Watermarking Content

Another way is to embed watermark payloads (which convey unique information about every watermarked item) into video and audio files of trusted content producers or creators. This payload contains segment identifiers, which lets the user tie one’s actions and record these traits about them, which helps to understand their use patterns of the media, such as audio or video. It includes a unique numerical user identification and other characteristics, such as name, email, etc., that they may know. Segment identifier is used for media content segments and the hash of these content segments. Hashing refers to transforming any given string characters into some other value and identifying the segments. It allows authentication of uploaded contents or comparison of remote files to local files without needing to download them.

In this scenario, an individual’s facial features will be assigned a unique value. This will then enable combating attempts of copying the watermarked content as the hash segments embedded in the individual’s facial features won’t match with the hash given to the watermark. This is because altercating a file’s value without changing the hash value is not possible. The watermarked content helps in tamper detection and performs three critical tasks - alerts users when the deepfake content is encountered, prevents the deepfake content detected from spreading, and allows forensic analysis to locate and destroy the deepfake content posted.


3.     Deploying Stringent Training

One primary reason why deepfake is a looming danger for businesses is that it is an emerging risk that not many are aware of. Many companies worldwide are unaware of the damage that deepfake content can cause. However, they can reduce the threat of it by educating and training its workforce, management and high-level executives about the nature and impact of it. Companies need to organize a systematic approach for enforcing a high-alert culture for cybersecurity threats. Training the entire organization about the risks of deepfake disruption will enable proactive measures toward detecting deepfake and ensuring data security.


4.     Slowing Down Actions

One thing that companies need to be aware of is that cybercriminals will always try to hurry their victims into making ill-advised and hasty decisions. Any force of urgency arriving in any interactions should alert the workforce and consider it a possible cyber threat. Employees should be trained and made aware to appropriately respond to such urgent requests by patiently communicating the need for more details to confirm the identity of the person making the request. The same should be done for any non-urgent requests.


Deepfakes can be seen as a significant threat as they can be used to cause misinformation, manipulation, extortion, or more. This emerging cyberattack technology is a way to foresee the advancement that cyberattacks and threats are producing. Deepfake can easily deceive the victim into behaving how it wants it to and disrupt a business. Companies worldwide need to accurately identify deepfake content to mitigate any threats and ensure its data security.


GajShield provides its customers with robust cyber security solutions and ensures its protection against any threats or attacks. Its contextual intelligence engine, threat surface management, data leak prevention, proactive security, and many more solutions strive towards creating an optimum data security environment. Contact us to learn more about our advanced cybersecurity solutions.





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