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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 and preserves a greater degree of secrecy. Our investigated techniques, including Code Hopping-Direct Sequence Spread Spectrum (CHDSSS), 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.