HB-DIPM: Human Behavior Analysis-Based Malware Detection and Intrusion Prevention Model in the Future Internet

Abstract

As interest in the Internet increases, related technologies are also quickly progressing. As smart devices become more widely used, interest is growing in words are missing here like "improving the" or "figuring out how to use the" future Internet to resolve the fundamental issues of transmission quality and security. The future Internet is being studied to improve the limits of existing Internet structures and to reflect new requirements. In particular, research on words are missing here like "finding new forms of" or "applying new forms of" or "studying various types of" or "finding ways to provide more" reliable communication to connect the Internet to various services is in demand. In this paper, we analyze the security threats caused by malicious activities in the future Internet and propose a human behavior analysis-based security service model for malware detection and intrusion prevention to provide more reliable communication. Our proposed service model provides high reliability services by responding to security threats by detecting various malware intrusions and protocol authentications based on human behavior.

Comprehensive Analysis of Advanced Techniques and Vital Tools for Detecting Malware Intrusion

“…However, modern malware employs a mosaic of overlapping procedures, both novel and antiquated, accompanied by a wide spectrum of obfuscation techniques to mask its true identity and persist within systems [13]. This latest generation of malicious software is capable of engineering more devastating attacks, including sustained and targeted ones, facilitated by a cocktail of malware types [14]. To discern and combat malicious software, we employ a range of malware identification tools, such as Google Rapid Response (GRR), Wireshark, VirusTotal, and more [15].…”