Human Centric Security

In the current world the research has been enormously growing in the field of computer science, exploring many applications using Generative AI. With the exploration of generative AI not only pleasing humans but also causing a major threat to the fellow beings. According to the statistics, 82% of breaches involve human behavior. This chapter pivots to human role in modern security and explores the generative AI mechanisms in addressing security vulnerabilities. Especially the cybercriminals are using smarter technologies from ChatGPT to Deep-fake tools for fooling people, with the generative AI able to understand the design of security system of the company and devise a way around. This leads companies would suffer from major financial and reputational losses. The existing rule-based approaches are not sophisticated to protect from such attacks. Establishing new approaches and strategies that can adapt to the Generative AI threats in real time. Generative AI not only threatens an individual or business, it can also create threat to complete national security, by producing disinformation about a country pointing stretching boundaries to its neighbouring countries and creating war situation among the countries. Generative AI amplifies its speed in producing security risks like disinformation, fraud and child abuse at a larger scale and may cause a larger population. Generative AI is also having ability to generate synthetic data that closely resembles real-world user interactions. By training on diverse datasets, Generative AI models develop a nuanced understanding of normal behavior across various contexts, enabling them to differentiate between legitimate activities and potential threats. This synthetic data generation capability not only enhances the robustness of user behavior analysis but also mitigates privacy concerns associated with accessing sensitive information. However, the widespread adoption of Generative AI in user behavior analysis also raises ethical considerations regarding data privacy and algorithmic bias. Safeguarding the integrity and privacy of user data remains paramount, necessitating transparent governance frameworks and rigorous accountability measures. Moreover, efforts to mitigate algorithmic biases and ensure equitable treatment of users are essential for fostering trust and legitimacy in AI-driven security solutions. In conclusion, the integration of Generative AI into user behavior analysis represents a paradigm shift in human-centric security, empowering organizations and nations to navigate the complex cybersecurity landscape with agility and precision. By harnessing the power of AI to decipher human behaviour, organizations and nations can strengthen their defences against evolving threats.