Detecting Local Machine Data Leakage in Real Time - Advances in Digital Forensics XVI Access content directly
Conference Papers Year : 2020

Detecting Local Machine Data Leakage in Real Time

Jingcheng Liu
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Yaping Zhang
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Yuze Li
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Yongheng Jia
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Yao Chen
Jin Cao
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Abstract

Data privacy leaks are becoming a serious problem. A large percentage of privacy leaks are due to inadvertent user errors. Most data leak detection solutions do not have privacy-preserving functionality. Moreover, due to the third-party delivery of data in the cloud, it is not possible to guarantee real-time leak detection.This chapter proposes a local-side data leakage detection method that uses a suffix array. The method also employs encryption for data protection. The method is compared with mature data leak detection algorithms to demonstrate its effectiveness in real time and that the additional data protection overhead is acceptable.
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hal-03657228 , version 1 (02-05-2022)

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Jingcheng Liu, Yaping Zhang, Yuze Li, Yongheng Jia, Yao Chen, et al.. Detecting Local Machine Data Leakage in Real Time. 16th IFIP International Conference on Digital Forensics (DigitalForensics), Jan 2020, New Delhi, India. pp.291-308, ⟨10.1007/978-3-030-56223-6_16⟩. ⟨hal-03657228⟩
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