Enhanced Multi-Factor Authentication framework to increase the attack detection speed in Intrusion Detection System

Abstract

Recognizing the rapid growth of the Internet of Things highlights the urgent need for strong security measures, especially with the number of IoT devices expected to reach 75.44 billion by 2025. Despite advancements in security techniques like ethical hacking and machine learning, IoT-specific vulnerabilities persist, necessitating innovative approaches such as Bug Bounty Programs and Responsible Disclosure. The effectiveness of these strategies remains uncertain, emphasizing the importance of comprehensive security planning tailored to the dynamic IoT landscape. MITM attacks leverage advanced encryption, blockchain, and Enhanced Multi-Factor Authentication (E-MFA). The framework proposes post-quantum cryptography, blockchain integration for decentralized key management, and advanced biometrics for user authentication. Machine learning aids in anomaly detection for threat mitigation. The architectural design includes intrusion detection, SSL encryption, and firewalls, emphasizing continuous monitoring and incident response planning to enhance MITM attack detection speed and performance.