By Raghav Iyer, IT security analyst
The rise of generative AI and allied technologies has led to a surge in the sophistication of cyberattacks. Despite security teams continuously updating their defence strategies, it's a constant challenge to keep pace. This is why security teams are adopting generative AI as a potent force against today's cyberattacks.
Understanding generative AI
Generative AI can be used to create content that's original, creative, and accurate. The technology relies heavily on neural network techniques like generative adversarial networks (GANs) and language models like OpenAI's GPT-3 to create images, videos, and human-like text. Leveraging generative AI can help organisations mimic human behaviour to understand threat patterns or create decoys to deceive attackers.
Adaptive response
One of the core capabilities of generative AI includes adapting to changing requirements. While traditional security systems rely on predefined patterns and signatures, generative AI can dynamically learn from changing threat patterns and continuously update its models to strengthen defensive mechanisms.
Leveraging generative AI for cyberdefence
As generative AI continues to grow, it's becoming crucial for security teams to identify and explore avenues within the scope of security operations centres (SOCs) to integrate generative AI into their cyberdefence strategies. While the following predictions are hypothetical and speculative, the reality of their implementation may not be so distant.
Counter-deceptive content: Developing deceptive content to mislead attackers can be a valuable strategy for security teams. This may involve generating fake traffic, using incorrect credentials, providing misleading information, and other tactics to distract and divert the attention of attackers.
Honeypots and decoys: Generative AI can be used to mimic realistic network behaviour and system events to create a deceptive environment, making it challenging for attackers to identify genuine assets. Organisations can employ this capability as a sophisticated honeypot to lure malicious attackers into a trap.
Automated threat analysis: Utilising generative AI to simulate threat scenarios can prove effective in identifying security weaknesses and vulnerabilities within a network. Security teams can leverage this approach to enhance their security strategy and better prepare for defending against complex threats.
Behaviour analytics: Developing behaviour patterns through the analysis of historical data can help proactively identify potential threat actors. This enables organisations to adopt effective strategies for triaging similar threats in the future.
Compliance and ethical mandates: Generative AI can be used to analyse the compliance standards that an organisation must adhere to, identifying potential gaps that could lead to noncompliance. This, in turn, allows organisations to take proactive measures to ensure ongoing compliance.
The importance of leveraging generative AI for cyberdefence
As the cybersecurity realm prepares to explore the full potential of generative AI, it is important to consider ethical and legal boundaries during deployment. Prioritising transparency in its usage and communicating this to stakeholders is essential to ensure that the technology's use remains within permissible boundaries.
Furthermore, despite AI adoption being a strategic necessity, human expertise is still an irreplaceable component in cybersecurity. Striking the right balance between technological adoption and human intelligence is essential to ensure the complete security of any organisation.