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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Shicong Li Xiaochun Yun Yongzheng Zhang Jun Xiao Yipeng Wang |
| Copyright Year | 2012 |
| Abstract | Because of the widespread Trojan, Internet users become more and more vulnerable to the threat of information leakage. Traditional techniques of Trojan detection were classified into two main categories: host-based and network-based. Unfortunately, existing techniques are insufficient and limited, because of the following reasons: (1)only uncover the known Trojan while inefficiently detecting novel samples, (2) should be adjusted in a timely fashion even a trivial change is applied, and (3)become computationally more expensive. In our work, we focus on a network behavior based method to address the limitations of previous network-based approaches. We analyze the profile of network behavior at two levels: (i)flow-level, (ii)IP-level. Our approach present two main advantages: (1)capture more detailed information to describe the network behavior profile, (2)consume lower computational overhead. We proposed a system, Manto, which detects Trojan communication with high accuracy using clustering technique. We implement Manto on real-world traces. The evaluation results exhibit that Manto is suitable for detecting Trojan communication amongst the vast amount of network traffic, with over 91% accuracy and less than 3.2% false positive ratio. We confidently regard our approach as a complementary way to the existing network-based techniques for we could address their main shortcomings. |
| Starting Page | 49 |
| Ending Page | 58 |
| File Size | 292222 |
| Page Count | 10 |
| File Format | |
| ISBN | 9781467318891 |
| e-ISBN | 9780769547220 |
| DOI | 10.1109/NAS.2012.10 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2012-06-28 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Accuracy Feature extraction Vectors Internet Trojan horses Monitoring |
| Content Type | Text |
| Resource Type | Article |
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