Types and Methods of Detecting the Penetration of MaliciousCargoes
DOI:
https://doi.org/10.31185/wjcms.224Abstract
Intrusion detection systems are management programs that detect possible attacks on networks and
computers, and usually do so by identifying information in the header of packages. But the cargo of packages
containing the main information can help detect abnormal traffic. This article examines the types of malicious cargo
and the different types of penetration detection systems and the methods offered to detect based on cargo. At the
end of this article, we will also introduce the Metasploit Framework, which is a framework used by testers and even
attackers and contains a variety of ready-made cargoes for different systems
References
] H. Alaidaros, M. Mahmuddin, and A. Al-Mazari An Overview of Flow-Based and Packet-Based Intrusion Detection Performance in High Speed
Networks.
B. Beigh and M. A. Peer Intrusion Detection and Prevention System : Classification and Quick Review, vol. 2, pp. 661–675, 2012.
Cloudflare What Is A Malicious Payload?, pp. 7–7, 2019.
C. Figueroa Intrusion Detection Systems Overview, 2016.
I. M. Iqbal and R. A. Calix, “Analysis of a Payload-based Network Intrusion Detection System using Pattern Recognition Processors,” Int. Conf.
Collab. Technol. Syst, pp. 398–403, 2016.
M. Mahoney and P. K. Chan Learning Nonstationary Models of Normal Network Traffic for Detecting Novel Attacks, pp. 376–385, 2002.
K. Labib and R. Vemuri NSOM: A real-time network-based intrusion detection system using self-organizing maps, pp. 1–6, 2002.
K. Wang and S. J. Stolfo, “Anomalous Payload-based Network Intrusion Detection,” Comput. Sci. Dep. Columbia Univ, 2005.
Alfouadi, Saeea and Neamah , Wasit Journal of Computer and Mathematics Science, Vol. 2 No. 4 (2023) p. 107-114
D. Bolzoni, S. Etalle, P. Hartel, and E. Zambon, “POSEIDON: A 2-tier anomaly-based network intrusion detection system,” Proc. - Fourth IEEE
Int, pp. 144–156, 2006.
S. Thorat, K. Kishore, A. K. Khandelwal, and B. Bruhadeshwar, “Payload Content based Network Anomaly Detection,” Cent. Secur. Theory
Algorithmic Res, 2008.
K. Wang, J. J. Parekh, and S. J. Stolfo, “Anagram : A Content Anomaly Detector Resistant to,” Comput. Sci. Dep, 2007.
A. Jamdagni, Z. Tan, X. He, P. Nanda, and R. P. Liu, “RePIDS: A multi tier Real-time Payload-based Intrusion Detection System,” Comput.
Networks, vol. 57, no. 3, pp. 811–824, 2013.
S. Mrdovic, “Data Mining for Anomalous Network Payload Detection,” Univ. Sarajev. Fac. Electr. Eng, 2018.
2019.
Downloads
Published
Issue
Section
License
Copyright (c) 2023 Hasanain M. J. Alfouadi, Marwah Nafea Saeea, Ali Fahem Neamah
This work is licensed under a Creative Commons Attribution 4.0 International License.
