Framework for Analyzing Intruder Behavior of IoT Cyber Attacks Based on Network Forensics by Deploying Honeypot Technology

This paper proposes an improved framework or methodology for analyzing the activities of network intruders and malwares in the area of cybercrime by utilizing honeypot technology and packet analyzer based on network forensics fundamentals to finally identify those intruders based on their intrusion scenarios. Learning on how new intruder and malware attacks aids organizations to be more aware and give the advantage to prepare their cyber-security systems against any attacks and solve real-world problems. The main advantage of this proposed method is resulted in the form of framework that can be served as a guideline to analyze attackers and overcome the discovered vulnerabilities along with strengthening the existing cyber-security systems for preventing future attacks. The proposed hypothesis is proven through a real experiment on a virtual machine using a virtual server. The literature reviews about the topic described are raised to support and validate our findings, a model is used to simulate the experiment processes done by the authors, therefore, it is found that the proposed framework and scenario in this study is possible to be achieved.