Comprehensive Analysis of Computer Network Threats and Security Measures
The growing vulnerabilities in computer networks highlight the critical need for robust intrusion detection techniques, particularly host-based systems. This paper evaluates five host-based intrusion detection systems (HIDS) to identify the most effective solution. Among these, the distributed intrusion detection system (DIDS) stands out due to its dual functionality, addressing threats at both local hosts and network levels for enhanced security. Computer applications, comprising interconnected hardware and tools, enable efficient send data and applications and data sharing but are face to various threats. Network threats, such as machine tampering, electrical sparks, and environmental factors, can compromise network infrastructure. Likewise, software threats, including malware and prohibitted access, often exploit hidden vulnerabilities, posing severe risks to data integrity and system performance. Therefore, this study emphasizes proactive measures, including secure setups, regular monitoring, good services, redundant power lines, and controlled environmental conditions. High-level threat detection and vulnerability management are essential for software threats. By implementing these approaches, target-based systems can reduce both hardware and software threats, ensuring network security and scalability. The results underscore the importance of preemptive tasks to identify and address vulnerabilities and improve the resilience of host-based intrusion detection systems in safeguarding modern computer networks against evolving threats.
Authors
- Muhammad Uzair (ORCID: https://orcid.org/0000-0001-8329-9762)
- Adeel Abbasi (ORCID: https://orcid.org/0000-0001-7826-9278)
- Zafran Waheed
- Husnain Mushtaq
- Irshad Ullah (ORCID: https://orcid.org/0000-0002-6365-9449)
Institutions
- Central South University (CN)
Publication Details
- Published
- 2024-12-13
- DOI
- https://doi.org/10.1109/hpcc64274.2024.00249
- Primary Topic
- Network Security and Intrusion Detection
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Hunan Province