Cyber threats are increasing in volume, velocity, and complexity, and traditional defence mechanisms cannot handle them, making it a pressing issue for both organisations and governments. Automated, more sophisticated, and adaptive attacks are slowly becoming the norm in the modern online environment as cybercriminals continue to utilise Artificial Intelligence (AI). The threat environment is being deployed to rise without even referring to polymorphic malware that can thus go undetected, through hyper-personalised phishing attacks, and through multiple-stage attacks designed by the adversary. The advent of generative AI, which can social-engineer disinformation in real-world settings, automate disinformation, and create synthetic identities in large quantities, has further amplified these risks. In this paper, a comprehensive AI-based cybersecurity system will be proposed to combat the increasing threat. It uses real-time attack detection, behaviour anomaly analysis, and automated incident response to reduce detection and response times. Further, there are already more advanced techniques, including predictive systems, self-healing platforms, and adaptable designs, which are used to stay ahead of attacks through flexible re-structuring of the defence. It is robust to evolving attack vectors, thanks to its counter-adversarial AI engine and explainable AI frameworks. We consider human-centred UI design to ensure transparency and trust in automated decision-making, enhance analyst interpretation, improve incident response processes, and improve feedback. It is also more open, fostering additional trust in automated decision-making. The suggested solution can exclude the threat of AI use by the enemy and enhance the resilience, speed, and effectiveness of cybersecurity systems, as they are innovative and proactive defence frameworks. This two-sided argument concerns the need for a highly desirable balance between the unbelievable opportunities of AI and ethical responsibility and healthy research. Lastly, the framework states that when in the right hands, AI will assist in restoring equilibrium to its proper place — back to the defenders — so they can safeguard the protector of a vital piece of digital infrastructure against a more formidable assemblage of intruders with even more sophisticated weaponry.

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The AI Paradox in Cybersecurity: Harnessing Artificial Intelligence and Human-Centred UI for Advanced Threat Defence

  • Suryaprakash Nalluri,
  • Nadiya Sri Nadikudhiti,
  • Murali Mohan Malyala,
  • Hemalatha Kandagiri,
  • Kishore Kalavakuri,
  • Pranitha Reddy Gaddam

摘要

Cyber threats are increasing in volume, velocity, and complexity, and traditional defence mechanisms cannot handle them, making it a pressing issue for both organisations and governments. Automated, more sophisticated, and adaptive attacks are slowly becoming the norm in the modern online environment as cybercriminals continue to utilise Artificial Intelligence (AI). The threat environment is being deployed to rise without even referring to polymorphic malware that can thus go undetected, through hyper-personalised phishing attacks, and through multiple-stage attacks designed by the adversary. The advent of generative AI, which can social-engineer disinformation in real-world settings, automate disinformation, and create synthetic identities in large quantities, has further amplified these risks. In this paper, a comprehensive AI-based cybersecurity system will be proposed to combat the increasing threat. It uses real-time attack detection, behaviour anomaly analysis, and automated incident response to reduce detection and response times. Further, there are already more advanced techniques, including predictive systems, self-healing platforms, and adaptable designs, which are used to stay ahead of attacks through flexible re-structuring of the defence. It is robust to evolving attack vectors, thanks to its counter-adversarial AI engine and explainable AI frameworks. We consider human-centred UI design to ensure transparency and trust in automated decision-making, enhance analyst interpretation, improve incident response processes, and improve feedback. It is also more open, fostering additional trust in automated decision-making. The suggested solution can exclude the threat of AI use by the enemy and enhance the resilience, speed, and effectiveness of cybersecurity systems, as they are innovative and proactive defence frameworks. This two-sided argument concerns the need for a highly desirable balance between the unbelievable opportunities of AI and ethical responsibility and healthy research. Lastly, the framework states that when in the right hands, AI will assist in restoring equilibrium to its proper place — back to the defenders — so they can safeguard the protector of a vital piece of digital infrastructure against a more formidable assemblage of intruders with even more sophisticated weaponry.