商品描述
Cyber threats are a common issue to your security and privacy. As various malicious threats and malware have been launched that target critical online services--such as e-commerce, e-health, social networks, and other major cyber applications--it has become more critical to protect important information from being accessed. Data-driven network intelligence is a crucial development in preserving the integrity of your computer by identifying anomalies and ensuring information privacy.
Data-driven Network Intelligence for Cybersecurity provides a comprehensive introduction to exploring technologies, applications, and issues in data-driven cyber infrastructure. It describes a proposed novel, data-driven network intelligence system that helps provide safeguards for edge-enabled infrastructure, edge-enabled artificial intelligence (AI) engines, and threat intelligence. Focusing particularly on encryption-based anomaly detection protocol, this book highlights the capability of a network intelligence system in helping target and identify unauthorized access, malicious interactions, and the destruction of critical information and communication technology.
Data-driven Network Intelligence for Cybersecurity readers will also find:
- Discussion of network anomalies and cyber threats
- Background information on AI and cyber infrastructure, particularly as regards trustworthy and robust artificial intelligence applications
- A presentation of a system and security model in the edge intelligence
- Detailed descriptions of the design of predicates and privacy-preserving anomaly detection features
Data-driven Network Intelligence for Cybersecurity is an essential reference for all professional computer engineers and researchers in cyber security and artificial intelligence, as well as graduate students in these fields.
商品描述(中文翻譯)
透過這本重要的網路安全參考書籍來幫助保護您的網路
網路威脅是影響安全性和隱私的常見問題。隨著各種針對關鍵在線服務（如電子商務、電子健康、社交網路及其他主要網路應用）的惡意威脅和惡意軟體的出現，保護重要資訊不被訪問變得更加重要。以數據為驅動的網路智能是維護計算機完整性的一項關鍵發展，能夠識別異常並確保資訊隱私。
以數據為驅動的網路智能在網路安全中提供了對數據驅動的網路基礎設施技術、應用和問題的全面介紹。它描述了一個提議的創新數據驅動網路智能系統，幫助為邊緣啟用基礎設施、邊緣啟用的人工智慧（AI）引擎和威脅情報提供保護。這本書特別聚焦於基於加密的異常檢測協議，突顯了網路智能系統在幫助識別未經授權的訪問、惡意互動以及關鍵資訊和通信技術的破壞方面的能力。
以數據為驅動的網路智能在網路安全的讀者還將發現：
- 網路異常和網路威脅的討論
- 有關人工智慧和網路基礎設施的背景資訊，特別是關於可信和穩健的人工智慧應用
- 邊緣智能中的系統和安全模型的介紹
- 對於預測和隱私保護異常檢測功能設計的詳細描述
以數據為驅動的網路智能在網路安全是所有專業計算機工程師和網路安全及人工智慧研究人員，以及這些領域的研究生的重要參考資料。
作者簡介
Shengjie Xu, PhD, is Assistant Professor of the Beacom College of Computer and Cyber Sciences Department at Dakota State University, US.
Yi Qian, PhD, is an IEEE member and is a Professor in the Department of Electrical and Computer Engineering at the University of Nebraska-Lincoln, US
Rose Qingyang Hu, PhD, is an IEEE member. She is also a Professor with the Electrical and Computer Engineering Department and the Associate Dean for Research of the College of Engineering, Utah State University, US.
作者簡介(中文翻譯)
徐勝杰，博士，是美國達科他州立大學（Dakota State University）比康計算機與網絡科學學院（Beacom College of Computer and Cyber Sciences）系的助理教授。
錢怡，博士，是IEEE會員，並且是美國內布拉斯加州林肯大學（University of Nebraska-Lincoln）電機與計算機工程系的教授。
胡青揚，博士，是IEEE會員。她同時是美國猶他州立大學（Utah State University）電機與計算機工程系的教授及工程學院的研究副院長。
