| Title | An Anti-Collusion Fingerprinting based on CFF Code and RS Code |
| Publication Type | Conference Paper |
| Year of Publication | 2020 |
| Authors | Sun, Yuxin, Zhang, Yingzhou, Zhu, Linlin |
| Conference Name | 2020 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC) |
| Date Published | oct |
| Keywords | CFF, Collusion Attacks, composability, concatenated coding, Data security, digital fingerprinting, Distributed databases, encoding, Fingerprint recognition, Human Behavior, leak traceability, Metrics, Organizations, Provenance, pubcrawl, Reed-Solomon code, Reed-Solomon codes, Resiliency, Resists |
| Abstract | Data security is becoming more and more important in data exchange. Once the data is leaked, it will pose a great threat to the privacy and property security of users. Copyright authentication and data provenance have become an important requirement of the information security defense mechanism. In order to solve the collusion leakage of the data distributed by organization and the low efficiency of tracking the leak provenance after the data is destroyed, this paper proposes a concatenated-group digital fingerprint coding based on CFF code and Reed-solomon (RS) that can resist collusion attacks and corresponding detection algorithm. The experiments based on an asymmetric anti-collusion fingerprint protocol show that the proposed method has better performance to resist collusion attacks than similar non-grouped fingerprint coding and effectively reduces the percentage of misjudgment, which verifies the availability of the algorithm and enriches the means of organization data security audit. |
| DOI | 10.1109/CyberC49757.2020.00019 |
| Citation Key | sun_anti-collusion_2020 |
An Anti-Collusion Fingerprinting based on CFF Code and RS Code