NDLI: Fast Detection of Transformed Data Leaks

Content Provider	IEEE Xplore Digital Library
Author	Xiaokui Shu Jing Zhang Danfeng Daphne Yao Wu-Chun Feng
Copyright Year	2005
Abstract	The leak of sensitive data on computer systems poses a serious threat to organizational security. Statistics show that the lack of proper encryption on files and communications due to human errors is one of the leading causes of data loss. Organizations need tools to identify the exposure of sensitive data by screening the content in storage and transmission, i.e., to detect sensitive information being stored or transmitted in the clear. However, detecting the exposure of sensitive information is challenging due to data transformation in the content. Transformations (such as insertion and deletion) result in highly unpredictable leak patterns. In this paper, we utilize sequence alignment techniques for detecting complex data-leak patterns. Our algorithm is designed for detecting long and inexact sensitive data patterns. This detection is paired with a comparable sampling algorithm, which allows one to compare the similarity of two separately sampled sequences. Our system achieves good detection accuracy in recognizing transformed leaks. We implement a parallelized version of our algorithms in graphics processing unit that achieves high analysis throughput. We demonstrate the high multithreading scalability of our data leak detection method required by a sizable organization.
Sponsorship	IEEE Signal Processing Society
Starting Page	528
Ending Page	542
Page Count	15
File Size	2989872
File Format	PDF
ISSN	15566013
Volume Number	11
Issue Number	3
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2016-01-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Automata Security Leak detection Pattern matching Algorithm design and analysis Heuristic algorithms Organizations parallelism Data leak detection content inspection sampling alignment dynamic programming
Content Type	Text
Resource Type	Article
Subject	Computer Networks and Communications Safety, Risk, Reliability and Quality

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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