Intrusion Detection and Security Operation Centers (SOCs) | ISOT research lab

Journal & magazine links

Conference links

ACM CSC
ACM SIGKDD
ISOC (Internet SOCiety) Conferences
Annual Computer Security Applications Conference
UCL Crypto Group
New Security Paradigms Workshop
RAID Symposium
Advanced Computing Systems Association

Sponsored by

W. A. Yousef, I. Traore and W. Briguglio, “Classifier Calibration: with application to threat scores in cybersecurity”, IEEE Transactions on Dependable and Secure Computing, doi: 10.1109/TDSC.2022.3170011., April 2022

Waleed Yousef, Issa Traore, William Briguglio, “UN-AVOIDS: Unsupervised and Nonparametric Approach for Visualizing Outliers and Invariant Detection Scoring”, IEEE Transactions on Information Forensics and Security, Volume 16, Pages: 5195 – 5210, 2021.

C. Nie, P. G. Quinan, I. Traoré and I. Woungang, “Intrusion Detection using a Graphical Fingerprint Model,” 22nd IEEE International Symposium on Cluster, Cloud and Internet Computing (CCGrid), Taormina, Italy, 16-19 May 2022, pp. 806-813, doi: 10.1109/CCGrid54584.2022.00095

Paulo Gustavo Quinan, Issa Traore, Ujwal Reddy Ghondi, Isaac Woungang, “Unsupervised Anomaly Detection using a new Knowledge Graph Model for Network Activity and Events”, 4th International Conference on Machine Learning for Networking (MLN), 2021, Paris, France. In: Renault, É., Boumerdassi, S., Mühlethaler, P. (eds) Machine Learning for Networking. MLN 2021. Lecture Notes in Computer Science, vol 13175. Springer, Cham. pp 117–130.

Nwamuo O., de Faria Quinan P.M., Traore I., Woungang I., Aldribi A., “Arguments Against Using the 1998 DARPA Dataset for Cloud IDS Design and Evaluation and Some Alternative”. In: Boumerdassi S., Renault É., Mühlethaler P. (eds) Machine Learning for Networking. MLN 2019. Lecture Notes in Computer Science, vol 12081. Springer, Cham

Nitika Gupta, Issa Traore, Paulo Magella Faria de Quinan, “Automated Event Prioritization for Security Operation Center using Deep Learning”, 2019 IEEE International Conference on Big Data (Big Data), Los Angeles, CA, USA, USA, 9-12 Dec. 2019.

Sherif Saad; Issa Traore; Marcelo Luiz Brocardo. “Context-aware intrusion alerts verification approach“, 10th International Conference on Information Assurance and Security (IAS), Okinawa, Japan, Nov 28-30, 2014.
W. Lu and I. Traore, “Unsupervised anomaly detection using an evolutionary extension of k-means algorithm”, International Journal on Information and Computer Security (IJICS), Volume 2, Issue 2, pp. 107-139, May-Aug 2008.

W. Lu, I. Traore, “A genetic EM algorithm for learning the optimal number of components of mixture models”, WSEAS Transactions on Computers, Issue 9, Vol. 5, September 2006, pp. 1795-1803 (9 pages).

W. Lu, I. Traore, “A novel evolutionary clustering algorithm based on Gaussian mixture model”, Proceedings of the 10th WSEAS International Conference on Computers, ID. 534-365, Vouliagmeni, Athens, Greece, July 13-15, 2006.

S. Khan and I. Traore, “Queue based analysis of DoS attacks”, Proceedings of the sixth IEEE Systems, Man and Cybernetics Information Assurance Workshop, June 2005, pp. 266-273.

Khan, S., and I. Traore, “A prevention model for algorithmic complexity attacks”, Conference on Detection of Intrusions and Malware & Vulnerability Assessment (DIMVA), Vienna, Austria, July 7-8, 2005, Lecture Notes in Computer Science (LNCS), Springer, K. Julisch and C. Kruegel (Eds.), LNCS 3548, pp. 160-173, 2005.

W. Lu, I. Traore, “A new evolutionary algorithm for determining the optimal number of clusters”, IEEE International Conference on Computational Intelligence for Modeling, Control and Automation (CIMCA), 28-30 November 2005, Vienna – Austria.

W. Lu and I. Traore, “An unsupervised approach for detecting DDOS attacks based on traffic-based metrics”, IEEE Pacific Rim Conference on Communications, Computers and Signal Processing, Pages: 462-465, Victoria, BC, August 2005.

W. Lu and I. Traore, “An unsupervised anomaly detection framework for network intrusions”, Technical Report ECE-05-2, Department of Electrical and Computer Engineering, University of Victoria, Victoria, BC, October 2005.

W. Lu, I. Traore, “Determining the optimal number of clusters using a new evolutionary algorithm”, 17th IEEE International Conference on Tools with Artificial Intelligence, 14-16 November, Hong-Kong.

W. Lu, I. Traore, “A novel unsupervised anomaly detection framework for detecting network attacks in real-time”, 4th International Conference on Cryptology and Network Security (CANS), Xiamen, Fujian Province, China, 14-16 December, 2005, Lecture Notes in Computer Science, Vol. 3810, Pages: 96-109, ISBN 3-540-30849-0, Springer, 2005, Y.G Desmedt et al. (Eds.).

W. Lu, I. Traore, “Detecting new forms of network intrusions using genetic programming”, Computational Intelligence, Vol. 20, No. 3, pp. 475-494, Aug. 2004, Blackwell Publishing, Boston MA & Oxford UK.