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Rootkit detection through phase-spac...

Dawson, Joel.

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Rootkit detection through phase-space analysis of system call timing and power data.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Rootkit detection through phase-space analysis of system call timing and power data./
作者:	Dawson, Joel.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2017,
面頁冊數:	125 p.
附註:	Source: Masters Abstracts International, Volume: 78-10.
Contained By:	Masters Abstracts International78-10.
標題:	Applied Mathematics. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10267772
ISBN:	9781369716993

Rootkit detection through phase-space analysis of system call timing and power data.
Dawson, Joel.

Rootkit detection through phase-space analysis of system call timing and power data. - Ann Arbor : ProQuest Dissertations & Theses, 2017 - 125 p.

Source: Masters Abstracts International, Volume: 78-10.

Thesis (M.S.)--University of South Alabama, 2017.

This item must not be sold to any third party vendors.

Rootkits are powerful pieces of malicious software that have grown in popularity with cybercriminals and nation state actors. These programs threaten a system by acquiring administrator privilege and then evading detection or removal by through active and passive stealth tactics. This research proposes an anomaly-based system to detect rootkit infection through an analysis of system call timing and power measurement traces. Our algorithm uses phase-space graphs which reconstruct the dynamics of the computer system from time-delay embedding of the original time-series data. We analyze effectiveness of this approach using measurements from a host infected with the KBeast rootkit. Our experimental methodology answers two key questions: whether timing data collected at the hypervisor level is useful for rootkit detection compared to data collected via kernel level modules and whether low-frequency power data can be used as a determining feature for the presence of rootkits themselves. Our results indicate, that at least for the KBeast rootkit, both questions are answered positively. Broader interpretation of the results may lead us to conclude that such techniques would also be effective for detecting other rootkits that hook system calls in the same manner that KBeast does.

ISBN: 9781369716993Subjects--Topical Terms:

1669109
Applied Mathematics.
Subjects--Index Terms:

Anomaly detection

Rootkit detection through phase-space analysis of system call timing and power data.
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653 $a Intrusion detection system
653 $a Malware
653 $a Nonlinear mathematics
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