TY - JOUR
T1 - Hit-list worm detection using distributed sliding window
AU - Kawaguchi, Nobutaka
AU - Shigeno, Hiroshi
AU - Okada, Ken’ichi
N1 - Publisher Copyright:
© 2011 Information Processing Society of Japan.
PY - 2011
Y1 - 2011
N2 - In this paper, we propose a new distributed hit-list worm detection method: the Anomaly Connection Tree Method with Distributed Sliding Window (ACTM-DSW). ACTM-DSW employs multiple distributed network Intrusion Detection Systems (IDSs), each of which monitors a small portion of an enterprise network. In ACTM-DSW, worm propagation trees are detected by using a sliding time window. More precisely, the distributed IDSs in ACTM-DSW cooperatively detect tree structures composed of the worm’s infection connections that have been made within a time window. Through computer-based simulations, we demonstrate that ACTM-DSW outperforms an existing distributed worm detection method, called d-ACTM/VT, for detecting worms whose infection intervals are not constant, but rather have an exponential or uniform distribution. In addition, we implement the distributed IDSs on Xen, a virtual machine environment, and demonstrate the feasibility of the proposed method experimentally.
AB - In this paper, we propose a new distributed hit-list worm detection method: the Anomaly Connection Tree Method with Distributed Sliding Window (ACTM-DSW). ACTM-DSW employs multiple distributed network Intrusion Detection Systems (IDSs), each of which monitors a small portion of an enterprise network. In ACTM-DSW, worm propagation trees are detected by using a sliding time window. More precisely, the distributed IDSs in ACTM-DSW cooperatively detect tree structures composed of the worm’s infection connections that have been made within a time window. Through computer-based simulations, we demonstrate that ACTM-DSW outperforms an existing distributed worm detection method, called d-ACTM/VT, for detecting worms whose infection intervals are not constant, but rather have an exponential or uniform distribution. In addition, we implement the distributed IDSs on Xen, a virtual machine environment, and demonstrate the feasibility of the proposed method experimentally.
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U2 - 10.2197/ipsjjip.19.180
DO - 10.2197/ipsjjip.19.180
M3 - Article
AN - SCOPUS:84941271798
SN - 0387-5806
VL - 19
SP - 180
EP - 189
JO - Journal of information processing
JF - Journal of information processing
ER -