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| Content Provider | Springer Nature Link |
|---|---|
| Author | Garg, Shree Peddoju, Sateesh K. Sarje, Anil K. |
| Copyright Year | 2016 |
| Abstract | P2P Botnets are one of the most malevolent threats to the Internet users due to their resiliency against takedown efforts. In this paper, we propose a bot detection system that is capable of detecting stealthy bots in a network. This system treats network traffic as a data stream, segregating the traffic into two parallel streams. The detection is based on failure traffic and communication traffic. The traffic is analyzed during small time window, and the infected hosts are reported immediately. The network administrator can monitor the status of hosts in the network and can take the necessary action before the infected hosts harm the system or can involve in the attacks. Experiments and evaluation of the proposed system on a variety of P2P data transfer applications and P2P botnets have demonstrated high accuracy of detection. The scalability of the proposed system is exhibited through its implementation on Hadoop MapReduce. |
| Starting Page | 1209 |
| Ending Page | 1225 |
| Page Count | 17 |
| File Format | |
| ISSN | 19366442 |
| Journal | Peer-to-Peer Networking and Applications |
| Volume Number | 9 |
| Issue Number | 6 |
| e-ISSN | 19366450 |
| Language | English |
| Publisher | Springer US |
| Publisher Date | 2016-02-22 |
| Publisher Place | New York |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | P2P Botnet Bots Hadoop Intrusion Detection System Data Stream NIDS Map Reduce Parallel Detection Malicious Activity Communications Engineering, Networks Information Systems and Communication Service Computer Communication Networks Signal, Image and Speech Processing |
| Content Type | Text |
| Resource Type | Article |
| Subject | Computer Networks and Communications Software |
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