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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Sy, D. Bao, L. |
| Copyright Year | 2006 |
| Description | Author affiliation: Bren Sch. of Inf. & Comput. Sci., California Univ., Irvine, CA (Sy, D.; Bao, L.) |
| Abstract | Network-based attacks can be either persistent or sporadic. Persistent attack flows can be relatively easy to trace by mechanisms such as probabilistic packet marking, traffic logging, data mining etc. Sporadic attacks are sometimes easily detected by the intrusion detection systems (IDSs) at the victims, but are hard to trace back to the attack origins. We propose CAPTRA, a coordinated packet traceback mechanism, for wireless sensor networks (WSNs) that takes advantage of the broadcasting nature of the packet transmissions. By remembering packets in multi-dimensional Bloom filters distributed in overhearing sensors and later retrieving the information, CAPTRA identifies the path of the packet transfers using a series of REQUEST-VERDICT-CONFESS message exchanges between the forwarding and overhearing nodes. CAPTRA requires only small memory footprint on the sensors due to the usage of Bloom filters, and allows sensors to asynchronously refresh the Bloom filters so that the network traffic is continuously monitored. CAPTRA is simulated using J-Sim, and a few key parameters are tuned for the best tracing performance |
| Sponsorship | ACM SIGBED & IEEE Signal Process. Soc |
| Starting Page | 152 |
| Ending Page | 159 |
| File Size | 3512701 |
| Page Count | 8 |
| File Format | |
| ISBN | 1595933344 |
| DOI | 10.1109/IPSN.2006.244130 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2006-04-19 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Association for Computing Machinery, Inc. (ACM) |
| Subject Keyword | packet traceback Wireless sensor networks Intrusion detection Telecommunication traffic Broadcasting Traffic control Information filters Information retrieval Bloom filter Information filtering Data mining Monitoring |
| Content Type | Text |
| Resource Type | Article |
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