Legal regulation of social engineering in cybersecurity using AI

Legal regulation of social engineering in cybersecurity using AI, on the example of ChatGPT

Currently, artificial intelligence (AI) and neural networks are becoming more common in our lives, including in the areas of cybersecurity. One important aspect of cybersecurity is the fight against social engineering, which uses psychological methods to gain access to computer systems and data. This paper will consider the legal regulation of social engineering in cybersecurity using AI using the example of ChatGPT.

AI technology and ChatGPT

ChatGPT is an artificial intelligence model developed by OpenAI based on the GPT-3.5 architecture. ChatGPT uses deep learning and neural networks to analyze text data and create answers to user questions. ChatGPT can exchange messages with users in natural language, which makes it very useful for a variety of tasks, including customer support and cybersecurity issues.

Legal regulation of social engineering using AI

Most countries have laws that govern the use of social engineering in cybersecurity. The United States has the Computer Fraud and Misuse of Information Act, which prohibits unauthorized access to computer systems and data, including the use of social engineering. In addition, some US states have additional laws that prohibit the use of social engineering.

The European Union has a General Data Protection Regulation (GDPR) that governs the collection, processing and use of personal data. This regulation requires organizations that process personal data to provide adequate security for that data, including protection from social engineering.

With the use of ChatGPT, legal regulation of social engineering can be strengthened. ChatGPT can be trained to detect social engineering attemptserii and prevent them by learning from examples, what methods have been used in the past and what responses were considered effective in combating social engineering.

It is also possible to use ChatGPT to educate users on how to detect and prevent social engineering attempts. ChatGPT can educate users on what manipulations are used in such attacks and what signs may indicate such attempts.

However, the use of AI in cybersecurity also has its limitations and challenges. For example, ChatGPT, like any other technology, cannot be 100% effective in preventing social engineering. The use of AI in cybersecurity can also raise questions about data privacy and security, as it is a technology that can process a lot of personal information.

Conclusion

Artificial intelligence and neural networks are becoming more common in cybersecurity, including the fight against social engineering. Legal regulation of social engineering using AI can be improved by training ChatGPT on examples of social engineering attempts and using it to educate users on how to detect and prevent such attempts. However, the use of AI in cybersecurity also has its own challenges to consider. In general, the development and use of AI in cybersecurity should be carried out in compliance with legal norms and principles that ensure the safety and privacy of users.