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Conference Paper
Prevalent Traffic Contents Extraction by resemblance and Containment using Longest Common Subsequence
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- Authors
- Sang-Kil Park
- Issue Date
- 2011-11
- Citation
- International Conference on Computers, Communications and Systems (ICCCS) 2011, pp.1-4
- Language
- English
- Type
- Conference Paper
- Abstract
- Internet is used very wide area. Handset devices make huge traffic volume on router or switch. Typically badly written software will be vulnerable to several zero-day vulnerabilities in a short period of time. Exploits that take advantage of common file types are numerous and frequent, as evidenced by their increasing appearances in databases. Newly released software often has a software bug or leakage point, so attacker or cracker used to make a zero-day attack using some vulnerability that does not opened. FPGA-based Traffic measurement NIC card views all traffic and extract traffic using session success rate factor. Extracted packet is transmitted to traffic analysis software block. Contents based traffic pattern extraction function manage session table and it extract prevalent (reiterated) traffic pattern from each packet’s payload. For handling the string data which is prevalent CES uses the RKFP for string hashing and Resemblance and Containment calculating algorithm.
- KSP Keywords
- Analysis software, Longest Common Subsequence, Short period, Success rate, Traffic measurement, Traffic pattern, Traffic volume, Wide area, Zero-day attacks, pattern extraction, string hashing