Volume 16 (2024)
Volume 15 (2023)
Volume 14 (2022)
Volume 13 (2021)
Volume 12 (2020)
Volume 11 (2019)
Volume 10 (2018)
Volume 9 (2017)
Volume 8 (2016)
Volume 7 (2015)
Volume 6 (2014)
Volume 5 (2013)
Volume 4 (2012)
Volume 3 (2011)
Volume 2 (2010)
Volume 1 (2009)
A Semi-Supervised IDS for Cyber-Physical Systems Using a Deep Learning Approach

Amirhosein Salehi; Siavash Ahmadi; Mohammad Reza Aref

Volume 15, Issue 3 , October 2023, , Pages 43-50


  Industrial control systems are widely used in industrial sectors and critical infrastructures to monitor and control industrial processes. Recently, the security of industrial control systems has attracted a lot of attention, because these systems are now increasingly interacting with the Internet. Classic ...  Read More

A Graph-based Online Feature Selection to Improve Detection of New Attacks

Hajar Dastanpour; Ali Fanian

Volume 14, Issue 2 , July 2022, , Pages 115-130


  Today, intrusion detection systems are used in the networks as one of the essential methods to detect new attacks. Usually, these systems deal with a broad set of data and many features. Therefore, selecting proper features and benefitting from previously learned knowledge is suitable for efficiently ...  Read More

Real-Time intrusion detection alert correlation and attack scenario extraction based on the prerequisite consequence approach

Z. Zali; M. R. Hashemi; H. Saidi

Volume 4, Issue 2 , July 2012, , Pages 125-136


  Alert correlation systems attempt to discover the relations among alerts produced by one or more intrusion detection systems to determine the attack scenarios and their main motivations. In this paper a new IDS alert correlation method is proposed that can be used to detect attack scenarios in real-time. ...  Read More

A hybridization of evolutionary fuzzy systems and ant Colony optimization for intrusion detection

M. Saniee Abadeh; J. Habibi

Volume 2, Issue 1 , January 2010, , Pages 33-46


  A hybrid approach for intrusion detection in computer networks is presented in this paper. The proposed approach combines an evolutionary-based fuzzy system with an Ant Colony Optimization procedure to generate high-quality fuzzy-classification rules. We applied our hybrid learning approach to network ...  Read More