Authors :
Sanu Momodu Kabiru; Biralatei Fawei
Volume/Issue :
Volume 11 - 2026, Issue 5 - May
Google Scholar :
https://tinyurl.com/4rnnsfpx
Scribd :
https://tinyurl.com/te65n8td
DOI :
https://doi.org/10.38124/ijisrt/26May1407
Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.
Abstract :
The growing reliance on computer networks to conduct crucial operations has led to increased vulnerability to
cyber-attacks in the form of unauthorized access attempts, malware, denial of service (DoS) attacks, and other cyber
intrusions. As a result, Intrusion Detection Systems (IDS) and Intrusion Prevention Systems (IPS) have emerged as necessary
components of today's computer network infrastructure to combat these threats. An Intrusion Detection System monitors
computer network traffic for any suspicious activities, whereas an Intrusion Prevention System actively blocks all kinds of
attacks to provide real-time protection. While both these systems have been designed with the purpose of improving
computer network security, they exhibit many differences in operational process, impact on computer network performance,
and effectiveness in different scenarios. This research paper examines these two types of security mechanisms by designing
a computer network simulation using the Cisco Packet Tracer software application. For the purposes of this study, a realistic
LAN was set up consisting of various networking devices, including routers, switches, client workstations, and servers. The
IDS was configured in monitoring mode to detect and analyze computer network traffic, while the IPS was put into inline
mode to inspect and block any malicious activity. All the attack scenarios used in this experiment included a DoS attack
(Ping flood), attempts at unauthorized access, and port scanning operations in order to provide a fair comparison of system
performance. Metrics that were analyzed include detection rate, response time, false alarm rate, and performance impact
on the computer network. According to results obtained through the conducted experiment, IPS performed better in terms
of providing more accurate detection rates, faster response times, and lower false alarm rates owing to its preventive
features. IPS was found to have a negative influence on computer network performance because of the need to block
malicious packets. On the contrary, IDS has proven to be efficient in terms of monitoring computer network traffic without
affecting its performance, albeit at the expense of slower response times and a high number of false alerts. In conclusion,
IDS has been proven to be more effective than IPS when it comes to surveillance and forensics, but when compared to IPS,
which gives real-time protection against attacks, IDS lacks this feature. It is also important to note that each security strategy
has its own merits, but at the same time, each strategy involves some degree of sacrifice regarding efficiency and
effectiveness.
References :
- Amoroso, E. (2012). Cyber attacks: Protecting national infrastructure. Butterworth-Heinemann.
- Anderson, J. P. (1980). Computer security threat monitoring and surveillance. Technical Report, James P. Anderson Co.
- Axelsson, S. (2000). Intrusion detection systems: A survey. Technical Report, Chalmers University of Technology.
- Bace, R., & Mell, P. (2001). Intrusion detection systems. National Institute of Standards and Technology (NIST).
- Behl, A., & Behl, K. (2017). Cybersecurity and cyberwar: What everyone needs to know. Oxford University Press.
- Debar, H., Dacier, M., & Wespi, A. (1999). Towards a taxonomy for intrusion-detection systems. Computer Networks, 31(8), 805–822.
- Denning, D. E. (1987). An intrusion-detection model. IEEE Transactions on Software Engineering, SE-13(2), 222–232.
- Garcia-Teodoro, P., Diaz-Verdejo, J., Maciá-Fernández, G., & Vázquez, E. (2009). Anomaly-based network intrusion detection: Techniques, systems and challenges. Computers & Security, 28(1–2), 18–28.
- Julisch, K. (2003). Clustering intrusion detection alarms to support root cause analysis. ACM Transactions on Information and System Security, 6(4), 443–471.
- Kumar, S., & Spafford, E. H. (1994). A pattern matching model for misuse intrusion detection. Proceedings of the National Computer Security Conference.
- Lee, W., & Stolfo, S. J. (1998). Data mining approaches for intrusion detection. Proceedings of the 7th USENIX Security Symposium.
- Liao, H. J., Lin, C. H. R., Lin, Y. C., & Tung, K. Y. (2013). Intrusion detection system: A comprehensive review. Journal of Network and Computer Applications, 36(1), 16–24.
- Modi, C., Patel, D., Borisaniya, B., Patel, A., & Rajarajan, M. (2013). A survey of intrusion detection techniques in cloud. Journal of Network and Computer Applications, 36(1), 42–57.
- Mukherjee, B., Heberlein, L. T., & Levitt, K. N. (1994). Network intrusion detection. IEEE Network, 8(3), 26–41.
- Northcutt, S. (2005). Network intrusion detection. New Riders.
- Paxson, V. (1999). Bro: A system for detecting network intruders in real-time. Computer Networks, 31(23–24), 2435–2463.
- Patcha, A., & Park, J. M. (2007). An overview of anomaly detection techniques: Existing solutions and latest technological trends. Computer Networks, 51(12), 3448–3470.
- Ptacek, T. H., & Newsham, T. N. (1998). Insertion, evasion, and denial of service: Eluding network intrusion detection. Secure Networks Inc.
- Roesch, M. (1999). Snort: Lightweight intrusion detection for networks. Proceedings of LISA '99.
- Scarfone, K., & Mell, P. (2007). Guide to intrusion detection and prevention systems (IDPS). National Institute of Standards and Technology (NIST).
- Sommer, R., & Paxson, V. (2010). Outside the closed world: On using machine learning for network intrusion detection. IEEE Symposium on Security and Privacy.
- Stallings, W. (2018). Network security essentials: Applications and standards (6th ed.). Pearson.
- Tanenbaum, A. S. (2011). Computer networks (5th ed.). Pearson.
- Wagner, D., & Soto, P. (2002). Mimicry attacks on host-based intrusion detection systems. Proceedings of the ACM Conference on Computer and Communications Security.
- Whitman, M. E., & Mattord, H. J. (2016). Principles of information security (5th ed.). Cengage Learning.
The growing reliance on computer networks to conduct crucial operations has led to increased vulnerability to
cyber-attacks in the form of unauthorized access attempts, malware, denial of service (DoS) attacks, and other cyber
intrusions. As a result, Intrusion Detection Systems (IDS) and Intrusion Prevention Systems (IPS) have emerged as necessary
components of today's computer network infrastructure to combat these threats. An Intrusion Detection System monitors
computer network traffic for any suspicious activities, whereas an Intrusion Prevention System actively blocks all kinds of
attacks to provide real-time protection. While both these systems have been designed with the purpose of improving
computer network security, they exhibit many differences in operational process, impact on computer network performance,
and effectiveness in different scenarios. This research paper examines these two types of security mechanisms by designing
a computer network simulation using the Cisco Packet Tracer software application. For the purposes of this study, a realistic
LAN was set up consisting of various networking devices, including routers, switches, client workstations, and servers. The
IDS was configured in monitoring mode to detect and analyze computer network traffic, while the IPS was put into inline
mode to inspect and block any malicious activity. All the attack scenarios used in this experiment included a DoS attack
(Ping flood), attempts at unauthorized access, and port scanning operations in order to provide a fair comparison of system
performance. Metrics that were analyzed include detection rate, response time, false alarm rate, and performance impact
on the computer network. According to results obtained through the conducted experiment, IPS performed better in terms
of providing more accurate detection rates, faster response times, and lower false alarm rates owing to its preventive
features. IPS was found to have a negative influence on computer network performance because of the need to block
malicious packets. On the contrary, IDS has proven to be efficient in terms of monitoring computer network traffic without
affecting its performance, albeit at the expense of slower response times and a high number of false alerts. In conclusion,
IDS has been proven to be more effective than IPS when it comes to surveillance and forensics, but when compared to IPS,
which gives real-time protection against attacks, IDS lacks this feature. It is also important to note that each security strategy
has its own merits, but at the same time, each strategy involves some degree of sacrifice regarding efficiency and
effectiveness.