Publications

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Filters: Author is Roberto Perdisci  [Clear All Filters]
2005
G. Giacinto, Perdisci, R., e Roli, F., «Alarm Clustering for Intrusion Detection Systems in Computer Networks», in Machine Learning and Data Mining in Pattern Recognition (MLDM 2005), Leipzig, Germany, 2005, vol 3587, pagg 184-193.
G. Giacinto, Perdisci, R., e Roli, F., «Network Intrusion Detection by Combining One-class Classifiers», in 13th International Conference on Image Analysis and Processing (ICIAP 2005), Cagliari, Italy, 2005, vol 3617, pagg 58-65.
2006
R. Perdisci, Giacinto, G., e Roli, F., «Alarm clustering for intrusion detection systems in computer networks», Engineering Applications of Artificial Intelligence, vol 19, pagg 429-438, 2006.
2007
D. Ariu, Corona, I., Giacinto, G., Perdisci, R., e Roli, F., «Intrusion Detection Systems based on anomaly detection techniques», in Italian Workshop on Privacy and Security (PRISE), Rome, 2007.
D. Ariu, Giacinto, G., e Perdisci, R., «Sensing attacks in Computers Network with Hidden Markov Models», in Machine Learning and Data Mining in Pattern Recognition, MLDM 2007, Leipzig, 2007, vol 4571, pagg 449-463. (315.94 KB)
R. Perdisci, «Statistical Pattern Recognition Techniques for Intrusion Detection in Computer Networks. Challenges and Solutions.», Cagliari (Italy), 2007.
2009
R. Perdisci, Corona, I., Dagon, D., e Lee, W., «Detecting Malicious Flux Service Networks through Passive Analysis of Recursive DNS Traces», in Annual Computer Security Applications Conference (ACSAC), Honolulu, Hawaii, USA, 2009. (206.97 KB)
R. Perdisci, Ariu, D., Fogla, P., Giacinto, G., e Lee, W., «McPAD: A Multiple Classifier System for Accurate Payload-based Anomaly Detection», Computer Networks, vol 53, pagg 864-881, 2009. (882.94 KB)
2012
R. Perdisci, Corona, I., e Giacinto, G., «Early Detection of Malicious Flux Networks via Large-Scale Passive DNS Traffic Analysis», IEEE Transactions on Dependable and Secure Computing, vol 9, pagg 714-726, 2012. (1.37 MB)
2013
R. Perdisci, Ariu, D., e Giacinto, G., «Scalable Fine-Grained Behavioral Clustering of HTTP-Based Malware», Computer Networks - Special Issue on Botnet Activity: Analysis, Detection and Shutdown, vol 57, pagg 487-500, 2013. (797.8 KB)