Data Mining Tools for Malware Detection (Hardcover)

Mehedy Masud, Latifur Khan, Bhavani Thuraisingham

  • 出版商: Auerbach Publication
  • 出版日期: 2011-12-07
  • 售價: $2,980
  • 貴賓價: 9.5$2,831
  • 語言: 英文
  • 頁數: 450
  • 裝訂: Hardcover
  • ISBN: 1439854548
  • ISBN-13: 9781439854549
  • 相關分類: Data-mining
  • 立即出貨 (庫存=1)

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商品描述

Although the use of data mining for security and malware detection is quickly on the rise, most books on the subject provide high-level theoretical discussions to the near exclusion of the practical aspects. Breaking the mold, Data Mining Tools for Malware Detection provides a step-by-step breakdown of how to develop data mining tools for malware detection. Integrating theory with practical techniques and experimental results, it focuses on malware detection applications for email worms, malicious code, remote exploits, and botnets.

The authors describe the systems they have designed and developed: email worm detection using data mining, a scalable multi-level feature extraction technique to detect malicious executables, detecting remote exploits using data mining, and flow-based identification of botnet traffic by mining multiple log files. For each of these tools, they detail the system architecture, algorithms, performance results, and limitations.

  • Discusses data mining for emerging applications, including adaptable malware detection, insider threat detection, firewall policy analysis, and real-time data mining
  • Includes four appendices that provide a firm foundation in data management, secure systems, and the semantic web
  • Describes the authors’ tools for stream data mining

From algorithms to experimental results, this is one of the few books that will be equally valuable to those in industry, government, and academia. It will help technologists decide which tools to select for specific applications, managers will learn how to determine whether or not to proceed with a data mining project, and developers will find innovative alternative designs for a range of applications.

商品描述(中文翻譯)

儘管使用數據挖掘進行安全和惡意軟件檢測的應用正在迅速增長,但大多數關於此主題的書籍都只提供高層次的理論討論,幾乎不涉及實際方面。《惡意軟件檢測的數據挖掘工具》打破了這種模式,提供了開發惡意軟件檢測的數據挖掘工具的逐步分解。該書將理論與實際技術和實驗結果相結合,重點關注電子郵件蠕蟲、惡意代碼、遠程攻擊和僵尸網絡的惡意軟件檢測應用。

作者描述了他們設計和開發的系統:使用數據挖掘進行電子郵件蠕蟲檢測,使用可擴展的多層特徵提取技術檢測惡意可執行文件,使用數據挖掘檢測遠程攻擊,以及通過挖掘多個日誌文件來識別僵尸網絡流量。對於這些工具,他們詳細介紹了系統架構、算法、性能結果和限制。

本書討論了數據挖掘在新興應用中的應用,包括可適應的惡意軟件檢測、內部威脅檢測、防火牆策略分析和實時數據挖掘。書中還包括四個附錄,提供了關於數據管理、安全系統和語義網的基礎知識。此外,書中還描述了作者的流數據挖掘工具。

從算法到實驗結果,這是少數幾本對工業界、政府和學術界同樣有價值的書籍之一。它將幫助技術人員決定選擇哪些工具用於特定應用,管理人員將學習如何判斷是否進行數據挖掘項目,開發人員將找到一系列應用的創新替代設計。