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A Frame-Based Approach to Generating Insider Threat Test Suite on Cloud File-Sharing

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Mobile Internet Security (MobiSec 2017)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 971))

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Abstract

Insider threat has attracted considerable attention in security industry. It is difficult to detect insiders, because they know organization’s security countermeasures and usually hide their tracks in their normal activities. For evaluating insider detection algorithm on specific organization, it is important to generate a test suite with the corresponding normal activities. However, it is costly and time consuming to generate tailor-made test suite. Due to the complexity of combining different insider attack technique with different organization’s audit data, the insider attack scenario modeling issue arises when adaptively generate test suite for insider threat detection. In this paper, we propose the insider attack frame hierarchy to describe stereotype features of insider attack scenario. The proposed frame-based approach has been combined with the RBAC technologies, and its instantiation property allow us generate the customized insider attack test suite with full test coverage. The evaluation results show that most of experts satisfy with our proposed system.

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Acknowledgement

This study is conducted under the “III Innovative and Prospective Technologies Project (1/1)” of the Institute for Information Industry which is subsidized by the Ministry of Economic Affairs of the Republic of China. This work was partially supported by National Science Council of the Republic of China under contracts 106-2511-S-468-002-MY3 and 106-2511-S-468-004-MY2.

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Correspondence to Shian-Shyong Tseng .

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Lee, TJ., Tseng, SS., Chen, HC., Lin, SC., Kao, CH. (2019). A Frame-Based Approach to Generating Insider Threat Test Suite on Cloud File-Sharing. In: You, I., Chen, HC., Sharma, V., Kotenko, I. (eds) Mobile Internet Security. MobiSec 2017. Communications in Computer and Information Science, vol 971. Springer, Singapore. https://doi.org/10.1007/978-981-13-3732-1_12

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  • DOI: https://doi.org/10.1007/978-981-13-3732-1_12

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-3731-4

  • Online ISBN: 978-981-13-3732-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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