­čöĺ Cybersecurity and AI-Generated deception: Protecting authenticity in the digital era ­čöĺ

clipdrop altered image over altered Lazaro Gamio/Axios image

In its most basic sense, a deepfake is a combination of artificial intelligence technologies that clone faces and voices, allowing the creation of computer-generated videos that resemble real individuals. In terms of security, deepfakes are going to be a nightmare.
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Kymatio – Human Firewall Activation

The growing popularity of artificial intelligence (AI) technologies is enabling new creative opportunities, but it has also raised concerns in the field of cybersecurity.

One of the most disturbing issues is the proliferation of AI-generated deepfakes, a technique that uses advanced algorithms to manipulate multimedia content such as videos, images, or audio in an extremely convincing manner.

Recently, a fascinating experiment has been conducted with StableDiffusion Gen1, developed by Martin Haerlin, which demonstrates how effectively we can make the audience part of the story we want to tell. However, it is important to address the risks associated with this technology and ensure that its use is conducted ethically and safely.

Gen1’s ability to change the style of input videos raises questions about the authenticity of audiovisual content. This means that without proper safeguards, malicious actors could exploit this tool to create deepfakes that are difficult to detect and deceive unsuspecting individuals.

Furthermore, with the advent of Gen2, which has the capability to create entirely new videos based on text and input images, the potential threat of deepfakes multiplies. This technology could be used by cybercriminals to spread false information and manipulate public opinion in an alarming manner.

To protect our society and preserve the authenticity of information, it is crucial to take appropriate cybersecurity measures. Some recommendations include:


  1. Awareness and education: It is essential for people to be informed about the existence and implications of deepfakes. Ongoing education about this threat will help the public stay vigilant and be able to identify possible manipulations.
  2. Verification with reliable sources: Before sharing information or multimedia content, it is important to verify the authenticity of the source. Paying attention to details such as video quality, inconsistencies in audio, or suspicious movements can help detect a deepfake.
  3. Development of detection technologies: Investment in research and development of deepfake detection tools is crucial. These AI-based solutions can help identify manipulated content and prevent its spread.
  4. Legislation and policies for responsible use: It is necessary to establish regulations and policies that address the responsible use of deepfake technology. This includes penalizing those who use this technology for malicious purposes and promoting transparency in its utilization.


While the experimentation with StableDiffusion Gen1 and Gen2 showcases the creative potential of deepfake technology, we must also be aware of the risks it carries. Cybersecurity must be a priority to protect our authenticity and safeguard trust in the digital era.

We must promote responsible use of this technology, but at the same time, we need to address these challenges as soon as possible, train our people for what lies ahead, and be prepared for the emergence of AI-driven attacks in the hands of cybercriminals.

We must get accustomed to the new digital paradigm where a significant portion of the content we encounter may not be precisely real.