Pregled bibliografske jedinice broj: 1163855
Using Approximation of Standard Deviation and Variance in Flow Features for Efficient Intrusion Detection
Using Approximation of Standard Deviation and Variance in Flow Features for Efficient Intrusion Detection // 16th International Conference on Telecommunications (ConTEL 2021)
Zagreb, Hrvatska: Institute of Electrical and Electronics Engineers (IEEE), 2021. 21012632, 5 doi:10.23919/contel52528.2021.9495962 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), ostalo)
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Naslov
Using Approximation of Standard Deviation and
Variance in Flow Features for Efficient Intrusion
Detection
Autori
Puselj, Dora ; Katic, Lovro ; Ostroski, Dominik ; Brajdic, Ivona ; Slovenec, Karlo
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), ostalo
ISBN
978-9-5318-4271-6
Skup
16th International Conference on Telecommunications (ConTEL 2021)
Mjesto i datum
Zagreb, Hrvatska, 30.06.2021. - 02.07.2021
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
Intrusion Detection , Anomaly Detection , Feature Reduction , CIC-IDS2017
Sažetak
Intrusion Detection Systems (IDS) are one of the most important defense tools against dangerous and sophisticated network attacks. In recent years high-speed network interfaces have become common in data centers and servers. To process such high- speed network traffic entirely, the feature extraction phase of an IDS must be highly efficient. The speed and overall efficiency of the feature extraction phase of anomaly-based Intrusion Detection Systems can be improved by substituting the exact values for standard deviation and variance with lower complexity approximations. This paper demonstrates that using range rule of thumb approximations instead of exact values does not affect the classification results of the model tested in its various configurations. The results show that the accuracy of the model output obtained using the approximations does not differ from the results obtained using the real values by more than 0.05%.
Izvorni jezik
Engleski
