On Effectiveness of Hopping-Based Spread Spectrum Techniques for Network Forensic Traceback

Wei Yu, Xinwen Fu, Erik Blasch, Khanh Pham, Dan Shen, Genshe Chen, Chao Lu
2013 2013 14th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing  
Network-based crime has been increasing in both extent and severity and network-based forensics encapsulates an essential part of legal surveillance. A key network forensics tool is traceback that can be used to identify true sources of suspects. Both accuracy and secrecy are essential attributes of a successful forensic traceback. In this paper, we study a class of hopping-based spread spectrum techniques for forensic traceback, which fully utilize the benefits of the spread spectrum approach
more » ... nd preserves a greater degree of secrecy. Our investigated techniques, including Code Hopping-Direct Sequence Spread Spectrum (CH-DSSS), Frequency Hopping-Direct Sequence Spread Spectrum (FH-DSSS), and Time Hopping-Spread Spectrum (TH-DSSS), operate to randomize the effects of marking traffic in both time and frequency domains. Our theoretical analysis, simulations, and real-world experiments validate these DSSS techniques in terms of accuracy and secrecy to benefit network forensics and deter cyber crimes.
doi:10.1109/snpd.2013.75 dblp:conf/snpd/YuFBPSCL13 fatcat:r7xybr24fbcqhibfor7heudfey