The Android Malware Handbook: Detection and Analysis by Human and Machine (Paperback)
暫譯: Android 惡意程式手冊：人類與機器的檢測與分析

Han, Qian, Mandujano, Salvador, Porst, Sebastian

The Android Malware Handbook: Detection and Analysis by Human and Machine (Paperback)
  • 出版商: No Starch Press
  • 出版日期: 2023-11-07
  • 售價: $1,800
  • 貴賓價: 9.5 折 $1,710
  • 語言: 英文
  • 頁數: 328
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 171850330X
  • ISBN-13: 9781718503304
  • 相關分類: Android

    • 立即出貨

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商品描述

Written by machine-learning researchers and members of the Android Security team, this all-star guide tackles the analysis and detection of malware that targets the Android operating system.

This groundbreaking guide to Android malware distills years of research by machine learning experts in academia and members of Meta and Google's Android Security teams into a comprehensive introduction to detecting common threats facing the Android eco-system today.

Explore the history of Android malware in the wild since the operating system first launched and then practice static and dynamic approaches to analyzing real malware specimens. Next, examine machine learning techniques that can be used to detect malicious apps, the types of classification models that defenders can implement to achieve these detections, and the various malware features that can be used as input to these models. Adapt these machine learning strategies to the identifica-tion of malware categories like banking trojans, ransomware, and SMS fraud.

You'll:

 

  • Dive deep into the source code of real malware
  • Explore the static, dynamic, and complex features you can extract from malware for analysis
  • Master the machine learning algorithms useful for malware detection
  • Survey the efficacy of machine learning techniques at detecting common Android malware categories


The Android Malware Handbook's team of expert authors will guide you through the Android threat landscape and prepare you for the next wave of malware to come.

商品描述(中文翻譯)

由機器學習研究者及 Android 安全團隊成員撰寫的這本全明星指南，專注於針對 Android 作業系統的惡意軟體分析與檢測。

這本開創性的 Android 惡意軟體指南，將學術界機器學習專家的多年研究以及 Meta 和 Google 的 Android 安全團隊成員的知識，濃縮成一個全面的介紹，幫助讀者檢測當前 Android 生態系統面臨的常見威脅。

探索自作業系統首次推出以來，Android 惡意軟體在野外的歷史，然後練習靜態和動態方法來分析真實的惡意軟體樣本。接下來，檢視可以用來檢測惡意應用程式的機器學習技術、防禦者可以實施的各類分類模型以達成這些檢測，以及可以作為這些模型輸入的各種惡意軟體特徵。將這些機器學習策略調整為識別如銀行木馬、勒索軟體和簡訊詐騙等惡意軟體類別。

您將會：

- 深入研究真實惡意軟體的源代碼
- 探索可以從惡意軟體中提取的靜態、動態和複雜特徵以進行分析
- 精通對於惡意軟體檢測有用的機器學習演算法
- 調查機器學習技術在檢測常見 Android 惡意軟體類別的有效性

《Android 惡意軟體手冊》的專家作者團隊將引導您了解 Android 威脅環境，並為即將到來的下一波惡意軟體做好準備。

作者簡介

Qian Han, Research Scientist at Meta since 2021, received his PhD in Computer Science from Dartmouth College and his Bachelor's in Electronic Engineering from Tsinghua University, Beijing, China.

Salvador Mandujano, Security Engineering Manager at Google, has led product security engineering, malware reverse engineering and payments security teams. Before Google, he held senior security research and architecture positions at Intel and Nvidia. He has a PhD in Artificial Intelligence from Tecnológico de Monterrey, an MSc in Computer Science from Purdue, an MBA from The University of Texas, and a BSc in Computer Engineering from Universidad Nacional Autónoma de México.

Sebastian Porst is manager of Google's Android Application Security Research team, which tries to predict or research novel attacks on Android devices and Android users by malware or through app vulnerabilities. He has an MSc Masters from Trier University of Applied Sciences, Germany in 2007.

V.S. Subrahmanian is the Walter P. Murphy Professor of Computer Science and Buffet Faculty Fellow in the Buffet Institute of Global Affairs at Northwestern University. Prof. Subrahmanian is one of the world's foremost experts at the intersection of AI and security issues. He has written eight books, edited ten, and published over 300 refereed articles.

Sai Deep Tetali, Principal Engineer and Tech Lead Manager at Meta, works on privacy solutions for augmented and virtual reality applications. He spent 5 years at Google developing machine learning techniques to detect Android malware and has a PhD from University of California Los Angeles.

Yanhai Xiong is currently an Assistant Professor in the Department of Computer Science and Engineering at the University of Louisville. She has a PhD from Nanyang Technological University focusing on applying AI techniques to improve the efficiency of electric vehicle infrastructure and a BS in Engineering from the University of Science and Technology of China.

作者簡介(中文翻譯)

Qian Han，自2021年起擔任Meta的研究科學家，獲得達特茅斯學院的計算機科學博士學位，並在中國北京的清華大學獲得電子工程學士學位。

Salvador Mandujano，谷歌的安全工程經理，曾領導產品安全工程、惡意軟體逆向工程和支付安全團隊。在加入谷歌之前，他在英特爾和Nvidia擔任高級安全研究和架構職位。他擁有蒙特雷科技大學的人工智慧博士學位、普渡大學的計算機科學碩士學位、德克薩斯大學的工商管理碩士學位，以及墨西哥國立自治大學的計算機工程學士學位。

Sebastian Porst是谷歌Android應用安全研究團隊的經理，該團隊致力於預測或研究針對Android設備和Android用戶的惡意軟體或應用漏洞的新型攻擊。他於2007年在德國特里爾應用科技大學獲得碩士學位。

V.S. Subrahmanian是西北大學計算機科學的Walter P. Murphy教授及Buffet全球事務研究所的Buffet Faculty Fellow。Subrahmanian教授是AI與安全問題交集領域的世界頂尖專家之一。他撰寫了八本書籍，編輯了十本書，並發表了超過300篇經過審核的文章。

Sai Deep Tetali，Meta的首席工程師及技術負責經理，專注於增強現實和虛擬現實應用的隱私解決方案。他在谷歌工作了5年，開發機器學習技術以檢測Android惡意軟體，並擁有加州大學洛杉磯分校的博士學位。

Yanhai Xiong目前是路易斯維爾大學計算機科學與工程系的助理教授。她擁有南洋理工大學的博士學位，專注於應用AI技術以提高電動車基礎設施的效率，並在中國科學技術大學獲得工程學士學位。

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