Booth Id:
SOFT010
Category:
Systems Software
Year:
2025
Finalist Names:
Nyambirai, Gigi (School: Peterhouse Girls School)
Abstract:
As cyber threats like malware and ransomware evolve, traditional antivirus solutions struggle to keep pace. Inspired by bacteriophages, viruses that selectively target bacteria, this project develops an AI-driven antivirus that mimics their precision and adaptability.
The program identifies malware through unique digital signatures, similar to how bacteriophages recognize host markers. Once a threat is detected, it generates customized countermeasures to neutralize it, adapting continuously to new threats. This enables proactive defense, particularly against polymorphic malware, which alters its code to evade detection.
A prototype was developed and tested against a simulated malware dataset. Results demonstrated adaptive threat detection and effective neutralization, proving the potential for a scalable cybersecurity solution.
By merging biology and computer science, this research introduces a novel biomimetic approach to cybersecurity. The AI-driven antivirus system offers intelligent, evolving protection, addressing the urgent need for adaptive, efficient, and scalable digital defenses in an interconnected world.
Awards Won: