Federated Cyber Intelligence: Federated Learning for Cybersecurity
暫譯: 聯邦網路情報：用於網路安全的聯邦學習
Tabrizchi, Hamed, Aghasi, Ali
商品描述
This book offers a detailed exploration of how federated learning can address critical challenges in modern cybersecurity. It begins with an introduction to the core principles of federated learning. Then it highlights a strong foundation by exploring the fundamental components, workflow, and algorithms of federated learning, alongside its historical development and relevance in safeguarding digital systems.
The subsequent sections offer insight into key cybersecurity concepts, including confidentiality, integrity, and availability. It also offers various types of cyber threats, such as malware, phishing, and advanced persistent threats. This book provides a practical guide to applying federated learning in areas such as intrusion detection, malware detection, phishing prevention, and threat intelligence sharing. It examines the unique challenges and solutions associated with this approach, such as data heterogeneity, synchronization strategies and privacy-preserving techniques.
This book concludes with discussions on emerging trends, including blockchain, edge computing and collaborative threat intelligence. This book is an essential resource for researchers, practitioners and decision-makers in cybersecurity and AI.
商品描述(中文翻譯)
這本書詳細探討了聯邦學習如何解決現代網路安全中的關鍵挑戰。書中首先介紹了聯邦學習的核心原則。接著，通過探索聯邦學習的基本組件、工作流程和算法，以及其歷史發展和在保護數位系統中的相關性，強調了其堅實的基礎。
隨後的章節提供了關鍵網路安全概念的見解，包括保密性、完整性和可用性。書中還介紹了各種網路威脅類型，如惡意軟體、釣魚攻擊和持續性威脅。這本書提供了一個實用指南，說明如何在入侵檢測、惡意軟體檢測、釣魚防範和威脅情報共享等領域應用聯邦學習。它探討了與這種方法相關的獨特挑戰和解決方案，例如數據異質性、同步策略和隱私保護技術。
本書最後討論了新興趨勢，包括區塊鏈、邊緣計算和協作威脅情報。這本書是網路安全和人工智慧領域的研究人員、實務工作者和決策者的重要資源。
作者簡介
Hamed Tabrizchi earned his Bachelor's and Master's degrees in Computer Science from Shahid Bahonar University of Kerman, Iran, in 2017 and 2019, respectively. At the present time, he is a Ph.D. candidate and university lecturer in the computer science department at the University of Tabriz. As a person who was awarded as a talented student of the University of Tabriz in 2020 and a national elite in 2023. In addition to being an experienced artificial intelligence researcher, Hamed has served as a consultant in fields such as cloud computing and cloud computing security for various startups and industrial projects since 2017. Beyond his research endeavors, he has lectured at universities, led workshops, and contributed extensively to leading scientific journals, amassing over 900 citations. Furthermore, he has reviewed more than 300 papers as verified in Web of Science for international journals and conferences.
Ali Aghasi holds a PhD in Computer Engineering from the University of Isfahan, with a research focus on optimizing energy consumption in cloud data centers using AI-driven methods. Currently serving as the Cybersecurity Manager at the IT Center of Shahid Bahonar University of Kerman, Ali Aghasi leads innovative projects deploying artificial intelligence to detect malicious activities and enhance the resilience of IT infrastructures. His expertise bridges the domains of AI, cybersecurity, and energy-efficient computing, making him a leader in advancing secure, efficient systems.
作者簡介(中文翻譯)
Hamed Tabrizchi 於 2017 年和 2019 年分別在伊朗的 Kerman Shahid Bahonar 大學獲得計算機科學的學士和碩士學位。目前，他是塔布里茲大學計算機科學系的博士候選人和大學講師。作為 2020 年塔布里茲大學的優秀學生獲獎者以及 2023 年的全國菁英，Hamed 除了是一位經驗豐富的人工智慧研究者外，自 2017 年以來，他還擔任多家初創公司和工業項目的雲計算及雲計算安全顧問。除了研究工作外，他還在大學授課、主持研討會，並廣泛貢獻於領先的科學期刊，累積超過 900 次引用。此外，他已經為國際期刊和會議審查了超過 300 篇論文，這些都在 Web of Science 中得到了驗證。
Ali Aghasi 擁有伊斯法罕大學的計算機工程博士學位，研究重點是利用人工智慧驅動的方法優化雲數據中心的能源消耗。目前，他擔任 Kerman Shahid Bahonar 大學 IT 中心的網絡安全經理，領導創新項目，利用人工智慧檢測惡意活動並增強 IT 基礎設施的韌性。他的專業知識橋接了人工智慧、網絡安全和能源高效計算的領域，使他成為推進安全、高效系統的領導者。
