JABER KARIMPOUR, SHAHRIAR LOTFI, ALIAKBAR TAJARI SIAHMARZKOOH

116130

Intrusion detection in network flows based on an optimized clustering criterion

Graph-based intrusion detection approaches consider the network as a graph and detect anomalies based on graph metrics. However, most of these approaches succumb to the cluster-based behavior of the anomalies. To resolve this problem in our study, we use flow and graph-clustering concepts to create a data set first. A new criterion related to the average weight of clusters is then defined and a model is proposed to detect attacks based on the above-mentioned criterion. Finally, the model is evaluated using a DARPA data set. Results show that the proposed approach detects the attacks with high accuracy relative to methods described in previous studies.
Keywords:

Attack, DARPA data set flow, graph clustering, intrusion detection,

PDF
Turkish Journal of Electrical Engineering and Computer Science-Cover
  • ISSN: 1300-0632
  • Yayın Aralığı: Yılda 6 Sayı
  • Yayıncı: TÜBİTAK
Arşiv
Sayıdaki Diğer Makaleler

Krishna BHOWAL, Debasree Chanda SARKAR, Sushanta BISWAS, Partha Pratim SARKAR

MASOUD JAFARI, GHOLAMREZA MORADI, REZA SARRAF SHIRAZI, RASHID MIRZAVAND

ERTUĞRUL BAYRAKTAR, PINAR BOYRAZ

SOHIFUL ANUAR ZAINOL MURAD, IZATUL SYAFINA ISHAK, MOHD FAIRUS AHMAD, SHAIFUL NIZAM MOHYAR

Hamid GHADERI, Peyman KABIRI

Mohamed SALEM, Mahmoud HAMOUDA, Jaleleddine Ben Hadj SLAMA

Tuğba Önal SÜZEK

YALÇIN BALCIOĞLU, GÜNHAN DÜNDAR

MOUAD ADDAD, ALI DJEBBARI

JABER KARIMPOUR, SHAHRIAR LOTFI, ALIAKBAR TAJARI SIAHMARZKOOH