國立虎尾科技大學 |

Malware Detection and Cyber Security via Compression.

紀錄類型:	書目-語言資料,手稿 : Monograph/item
正題名/作者:	Malware Detection and Cyber Security via Compression./
作者:	Raff, Edward.
面頁冊數:	1 online resource (289 pages)
附註:	Source: Dissertation Abstracts International, Volume: 79-10(E), Section: B.
Contained By:	Dissertation Abstracts International79-10B(E).
標題:	Computer science. -
電子資源:	click for full text (PQDT)
ISBN:	9780355990027

Malware Detection and Cyber Security via Compression.
Raff, Edward.

Malware Detection and Cyber Security via Compression. - 1 online resource (289 pages)

Source: Dissertation Abstracts International, Volume: 79-10(E), Section: B.

Thesis (Ph.D.)--University of Maryland, Baltimore County, 2018.

Includes bibliographical references

As society becomes increasingly interconnected and dependent on computing systems, so does the importance of cyber security and the prevention of malware. Beyond just the home computer, smart-phones, routers, printers, and all kinds of devices now run operating systems that could be potentially infected. This represents an explosion in the potential attack surface for a malicious actor. The tools currently available to security professions are improving, but limited. Each tool is designed for one software platform, making their scope limited. Adapting these tools to new platforms and hosts requires years of effort and introduces a significant lag time to protecting any new platforms that will arise in the future. Further, malware often involves an adversary intentionally violating format specification and rules. These violations may be intended to slow reverse engineering efforts, hide intent or attribution, or simply be part of an exploit that is part of the malware's functionality.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018

Mode of access: World Wide Web

ISBN: 9780355990027Subjects--Topical Terms:

573171
Computer science.
Index Terms--Genre/Form:

554714
Electronic books.

Malware Detection and Cyber Security via Compression.
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500 $a Source: Dissertation Abstracts International, Volume: 79-10(E), Section: B.
500 $a Adviser: Charles K. Nicholas.
502 $a Thesis (Ph.D.)--University of Maryland, Baltimore County, 2018.
504 $a Includes bibliographical references
520 $a As society becomes increasingly interconnected and dependent on computing systems, so does the importance of cyber security and the prevention of malware. Beyond just the home computer, smart-phones, routers, printers, and all kinds of devices now run operating systems that could be potentially infected. This represents an explosion in the potential attack surface for a malicious actor. The tools currently available to security professions are improving, but limited. Each tool is designed for one software platform, making their scope limited. Adapting these tools to new platforms and hosts requires years of effort and introduces a significant lag time to protecting any new platforms that will arise in the future. Further, malware often involves an adversary intentionally violating format specification and rules. These violations may be intended to slow reverse engineering efforts, hide intent or attribution, or simply be part of an exploit that is part of the malware's functionality.
520 $a In this thesis, we develop a new approach for tackling problems related to malware detection and cyber security in general. Specifically, we develop new methods inspired by compression algorithms that support a wide range of tasks. The compression background allows the methods we develop to be applied to any file format, operating system, or platform. This provides a single method which can be used in all circumstances, and dramatically reduces the potential lag time to protect new platforms. Not only does this provide a wide range of flexibility, but we will also show that our approach significantly improves upon the existing methods available to practitioners today.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2018
538 $a Mode of access: World Wide Web
650 4 $a Computer science. $3 573171
655 7 $a Electronic books. $2 local $3 554714
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710 2 $a University of Maryland, Baltimore County. $b Computer Science. $3 1179407
773 0 $t Dissertation Abstracts International $g 79-10B(E).
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