Trust, Security and Privacy for Big Data

Data has revolutionized the digital ecosystem. Readily available large datasets foster AI and machine learning automated solutions. The data generated from diverse and varied sources including IoT, social platforms, healthcare, system logs, bio-informatics, etc. contribute to and define the ethos of Big Data which is volume, velocity and variety. Data lakes formed by the amalgamation of data from these sources requires powerful, scalable and resilient storage and processing platforms to reveal the true value hidden inside this data mine. Data formats and its collection from various sources not only introduce unprecedented challenges to different domains including IoT, manufacturing, smart cars, power grids etc., but also highlight the security and privacy issues in this age of big data. Security and privacy in big data is facing many challenges, such as generative adversary networks, efficient encryption and decryption algorithms, encrypted information retrieval, attribute-based encryption, attacks on availability, and reliability. Providing security and privacy for big data storage, transmission, and processing have been attracting much attention in all big data related areas.

The book provides timely and comprehensive information for researchers and industry partners in communications and networking domains to review the latest results in security and privacy related work of Big Data. It will serve computer science and cybersecurity communities including researchers, academicians, students, and practitioners who have interest in big data trust privacy and security aspects. It is a comprehensive work on the most recent developments in security of datasets from varied sources including IoT, cyber physical domains, big data architectures, studies for trustworthy computing, and approaches for distributed systems and big data security solutions etc.

數據已經改變了數字生態系統。可用的大型數據集促進了人工智能和機器學習的自動化解決方案。來自各種不同來源的數據，包括物聯網、社交平台、醫療保健、系統日誌、生物信息學等，為大數據的特性——數量、速度和多樣性做出了貢獻並定義了其本質。由這些來源數據組成的數據湖需要強大、可擴展和堅韌的存儲和處理平台，以揭示其中隱藏的真正價值。來自各種來源的數據格式及其收集不僅給不同領域帶來了前所未有的挑戰，包括物聯網、製造業、智能汽車、電力網等，同時也凸顯了大數據時代的安全和隱私問題。大數據的安全和隱私面臨著許多挑戰，例如生成對抗網絡、高效的加密和解密算法、加密信息檢索、基於屬性的加密、可用性和可靠性攻擊等。在所有與大數據相關的領域中，為大數據存儲、傳輸和處理提供安全和隱私一直受到廣泛關注。

該書為通信和網絡領域的研究人員和行業合作夥伴提供了及時而全面的信息，以回顧大數據安全和隱私相關工作的最新成果。它將服務於計算機科學和網絡安全社區，包括研究人員、學者、學生和從業人員，他們對大數據的信任、隱私和安全方面感興趣。這是一本關於來自不同來源的數據安全的最新發展的綜合性著作，包括物聯網、物理領域、大數據架構、可信計算研究以及分布式系統和大數據安全解決方案等方面的研究。

Mamoun Alazab is an associate professor at the College of Engineering, IT and Environment at Charles Darwin University, Australia. He received his Ph.D. degree in Computer Science from the Federation University of Australia, School of Science, Information Technology and Engineering. He is a cybersecurity researcher and practitioner with industry and academic experience. Alazab's research is multidisciplinary that focuses on cybersecurity and digital forensics of computer systems with a focus on cybercrime detection and prevention. He has more than 150 research papers in many international journals and conferences. He works closely with government and industry on many projects, including Northern Territory (NT) Department of Information and Corporate Services, IBM, Trend Micro, the Australian Federal Police (AFP), the Australian Communications and Media Authority (ACMA), Westpac, United Nations Office on Drugs and Crime (UNODC), and the Attorney General's Department. He is a senior member of the IEEE. He is the founding chair of the IEEE Northern Territory (NT) Subsection.

Maanak Gupta is an assistant professor in Department of Computer Science at Tennessee Tech University, USA. He received his Ph.D. in Computer Science from the University of Texas at San Antonio and has worked as a postdoctoral research fellow at the Institute for Cyber Security. He also holds an M.S. degree in Information Systems from Northeastern University, Boston. His primary area of research includes security and privacy in cyber space focused in studying foundational aspects of access control and their application in technologies including cyber physical systems, cloud computing, IoT and Big data. Dr Gupta has worked in developing novel security mechanisms, models and architectures for next generation smart cars, smart cities, intelligent transportation systems and smart farming. He is also interested in machine learning based malware analysis and AI assisted cyber security solutions. His scholarly work is regularly published at top peer-reviewed security venues including ACM SIGSAC conferences and refereed journals. His research has been funded by the US National Science Foundation (NSF), NASA, US Department of Defense (DoD) and private industry. He is also the co-founder and co-chair of SMARTFARM-2020 and SaT-CPS 2021 workshops. In addition, he is a reviewer for several journals and conferences.

Mamoun Alazab是澳大利亞查爾斯達爾文大學工程、資訊科技和環境學院的副教授。他在澳大利亞聯邦大學科學、資訊技術和工程學院獲得計算機科學博士學位。他是一位具有行業和學術經驗的網絡安全研究員和實踐者。Alazab的研究是多學科的，專注於計算機系統的網絡安全和數字取證，重點是網絡犯罪的檢測和預防。他在許多國際期刊和會議上發表了150多篇研究論文。他與政府和行業密切合作，包括北領地信息和企業服務部、IBM、趨勢科技、澳大利亞聯邦警察局、澳大利亞通信和媒體管理局、Westpac、聯合國毒品和犯罪辦公室以及澳大利亞總檢察長部門。他是IEEE的高級會員，也是IEEE北領地分會的創始主席。

Maanak Gupta是美國田納西科技大學計算機科學系的助理教授。他在德克薩斯大學聖安東尼奧分校獲得計算機科學博士學位，並在網絡安全研究所擔任博士後研究員。他還擁有波士頓東北大學的信息系統碩士學位。他的主要研究領域包括網絡空間中的安全和隱私，專注於研究訪問控制的基礎方面及其在包括物聯網、大數據和雲計算等技術中的應用。Gupta博士致力於開發新穎的安全機制、模型和架構，應用於下一代智能汽車、智慧城市、智能交通系統和智慧農業。他還對基於機器學習的惡意軟件分析和人工智能輔助的網絡安全解決方案感興趣。他的學術工作經常在ACM SIGSAC會議和審查期刊上發表。他的研究得到了美國國家科學基金會（NSF）、美國國家航空航天局（NASA）、美國國防部（DoD）和私營行業的資助。他還是SMARTFARM-2020和SaT-CPS 2021研討會的聯合創始人和聯合主席。此外，他還是多個期刊和會議的審稿人。