Abstract

The Internet of Things (IoT) is a rapidly evolving concept with the potential to revolutionize interactions between individuals and organizations in the physical world. IoT connectivity aims to enable seamless and secure communication among various “things” by leveraging IT infrastructure. This technology has found applications in diverse domains, including healthcare, education, resource management, and data processing. However, the integration of IoT technology raises significant safety and privacy concerns that require addressing before widespread adoption. One critical aspect of improving the cybersecurity of IoT devices and networks involves mitigating Distributed Denial of Service (DDoS) attacks, which can exploit the bandwidth of IoT devices. IoT networks, characterized by their wireless nature, self-configurability, independence from existing infrastructures, and numerous nodes with unpredictable mobility patterns, require robust security measures. To enhance the cybersecurity of IoT devices and networks, we propose a method designed to counteract DDoS attacks, which represent a challenging and hard-to-detect threat that can severely degrade network performance. DDoS attacks involve a coordinated effort by malicious nodes to target a victim, effectively denying legitimate users access to network services and resources. Intrusion Prevention Systems (IPS) within IoT devices complement Intrusion Detection Systems (IDS) by actively combating and thwarting identified attacks. Our proposed approach focuses on analyzing bandwidth-based attacks, particularly DDoS attacks, which are highly disruptive and can significantly impair network functionality. The suggested methodology relies on insights derived from IDS reports, generated after thorough data analysis during forensic examinations. By leveraging the information from these reports, we can proactively enhance the security of IoT devices and networks, bolstering their resilience against DDoS attacks and other malicious activities.