Dependable Artificial Intelligence and Cyber Security

Concepts, Techniques, Infrastructures, and Applications
1. Auflage 2027
ISBN: 978-1-032-34888-9
Verlag: Taylor & Francis Ltd

Buch, Englisch, 816 Seiten, Format (B × H): 178 mm x 254 mm, Gewicht: 453 g

Progress in Artificial Intelligence (AI), Technologies such as Machine Learning (ML) and Generative AI, have has resulted in them being integrated with every application area. While the AI/ML techniques may be subject to cyber-attacks, the AI/ML algorithms are also being applied to solve cyber security problems. This book covers both AI/ML for cyber security as well as ensuring that AI/ML systems are secure, ensure privacy and integrity, among others. The AI/ML techniques that ensure security, integrity, privacy, fairness, and are fault tolerant and resilient have come to be known as Dependable Artificial Intelligence (DAI) and Dependable Machine learning (DML).

This book addresses various aspects of DAI/DML with cyber security applications as the main focus area. This book is divided into five parts, each describing some aspect of the technology that is relevant to DML and DAI. Part I describes supporting technologies for DML and DAI including security and privacy, an overview of various ML and AI techniques, applying AI/ML for Cyber Security, and (ii) Big Data, Cloud Computing, IoT and Blockchain technologies. Part II describes various concepts and techniques in DML. In particular, we discuss a framework for DML, different adversarial machine learning techniques, such as support vector machines and relevance vector machines, Privacy aware ML techniques such as privacy aware synthetic data generation and privacy aware federated learning with blockchain, Fairness in ML, and aspects such as integrity and resilience for ML applications.

Part III describes secure cloud-based data infrastructures for DML. We focus on Cloud-based infrastructures due to the extensive experimental work we have carried out in this field and many of the DML systems are currently hosted on cloud platforms. In particular, we discuss cloud-based infrastructure for secure cloud-based query processing infrastcrtures, assured information sharing infrastructures, data integration infrastructures to host DML models, systems and applications. Part IV discusses applications of DML in cyber security. The cyber security applications we have discussed include malware detection and insider threat detection. We also discuss how attackers could use ML to penetrate into various computing systems. Part V focusses on various DAI technologies and systems. In particular, we describe a framework for DAI, securing LLMs (Large Language Models), applying LLMs for security, as well as aspects of AI Governance.

The book is concluded in Chapter 43 with a discussion of future directions. It also includes two appendices, one which shows how we have evolved from data management to data mining to data science to ML to AI, and other providing readings in Dependable AI and Cyber Security.

Zielgruppe

Academic, Postgraduate, and Professional

Autoren/Hrsg.

Thuraisingham, Dr. Bhavani

Fachgebiete

• Mathematik | Informatik EDV | Informatik Daten / Datenbanken
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen
• Mathematik | Informatik EDV | Informatik Computerkommunikation & -vernetzung Netzwerksicherheit
• Mathematik | Informatik EDV | Informatik Technische Informatik Computersicherheit
• Mathematik | Informatik EDV | Informatik EDV & Informatik Allgemein

Inhaltsverzeichnis

Chapter 1: Empowering the Future: The Role of AI and IOMT. Chapter 2: Big Data and Machine Learning Integration for Real-time Insights from IoMT Devices. Chapter 3: The Role of AI and IoMT in Global Health Initiatives. Chapter 4: Developing a Smart Healthcare Solution for Diabetes disease early prediction using Machine Learning classification algorithm, k-fold cross-validation and Ensemble Techniques. Chapter 5: Revolutionizing Healthcare: The Impact of AI and IoMT on Biomedical Advancement. Chapter 6: IoMT-Enabled Patient Monitoring and Management. Chapter 7: AI Integrated Mental Health Care Apps: Current and Emerging Trends. Chapter 8: Leveraging Machine Learning Algorithms for Real-time Data Analysis in IoMT Devices. Chapter 9: Blood Group Testing Using Various Machine Learning Techniques. Chapter 10: Transforming Cervical Cancer Detection: The Role of Artificial Intelligence in Early Diagnosis and Care. Chapter 11: Real-Time Eye-Tracking Mouse Control Using HOG-Based Facial Landmark Detection. Chapter 12: A.I. & BIG DATA IN HEALTHCARE DIAGNOSIS PREDICTION: REVIEW. Chapter 13: AI-Driven Virtual Tutors: Bridging the Gap between Traditional and Online Education. Chapter 14: Employment of Machine Learning Techniques for Identifying various skin diseases: A Study. Chapter 15: AI-Based Smart Healthcare System. Chapter 16: Automated Detection of Monkeypox Skin Infections: An Image Classification Approach. Chapter 17: An Advanced Hybrid Model Based on Transfer Learning: Utilizing ResNet-50 and Support Vector Machine for Melanoma Detection in Dermoscopic Images. Chapter 18: Hepatitis C Detection Using an Optimized Perceptron Neural Network with the Penguin Optimization Algorithm. Chapter 19: Diabetes Detection Using Machine Learning Algorithms on the PIMA Dataset. Chapter 20: Revolutionizing Medical Education: The Role of AI, Virtual Reality, and Simulation Technologies. Chapter 21: Role of Deep Learning Algorithms for Early Prediction of Health Diseases: A Case Study of Asthma Disease Prediction. Chapter 22: AI-Powered CrossFit Coach: Integrating Local Small Language Model and Geospatial Technology for Enhanced Fitness Training. Chapter 23: A Comprehensive Analysis of Image-Based Dietary Assessment Methodologies using Visual Representation.

Über Autor(innen)

Dr. Bhavani Thuraisingham is the Founders Chair Professor of Computer Science, the Founding Executive Director of the Cyber Security Research and Education Institute (2004-2021) and is a Senior Strategist for AI and Security (2021-Present) at The University of Texas at Dallas (UT Dallas). She is an Associate Director of the USDOT National UTC (University Technology Center) on Transportation Cybersecurity and Resiliency since 2023 and served as a Visiting Senior Research Fellow at Kings College, University of London (2015-2022) and a New America Foundation Cybersecurity Policy Fellow (2017-8). She is an elected Fellow of prestigious organizations including the ACM, IEEE, AAAS, NAI (National Academy of Inventors) and the BCS (British Computer Society). Her research interests are on integrating cyber security with AI/ML. She is also a Co-Director of the Women in Cyber Security and Women in Data Science Centers at UTD. She has worked in cyber security (e.g., data security) since 1985 and on integrating AI and Cyber Security since 1986 and published the first paper on Security for Large AI Systems at the AAAI conference workshop in 1988. Her early work on AI was on developing expert systems for process control in the 1980s and on the inference problem in database security in the 1980s and 1990s. Since 2000, her focus has been applying AI/ML for detecting cyber threats and national security, Privacy Enhanced ML, and more recently on securing GenAI systems.

Dr. Thuraisingham has received several technical, education and leadership awards including the IEEE CS 1997 Edward J. McCluskey Technical Achievement Award, the 2023 IEEE CS Taylor L. Booth Education Award, ACM SIGSAC 2010 Outstanding Contributions Award, the IEEE ComSoc Communications and Information Security 2019 Technical Recognition Award, the IEEE CS TC (Technical Committee) on Services Computing 2017 Research Innovation Award, IEEE CS TC on Multimedia Computing 2023 Technical Impact Award, the ACM CODASPY 2017 Lasting Research Award, the IEEE ISI 2010 Research Leadership Award, the ACM SACMAT 10 Year Test of Time Awards in 2018 and 2019 (for papers published in 2008 and 2009), the IEEE CS TC on Cloud Computing Women in Cloud Computing Award, IEEE ICDM 2018 Service Award, the IEEE Big Data Security 2024 Pioneer Award, the Armed Forces communications and Electronics Association 2011 Medal of Merit Award, and the Dallas Business Journal 2017 Women in Technology Award.

Her 45 year career includes industry (Honeywell), Federal Research Laboratory (MITRE), US Government (NSF) and Academia. She has delivered over 250 keynote/featured addresses, over 150 panel presentations including at the United Nations, White House Office of Science and Technology Policy, Fortune Media, Dell Technologies World, Lloyds of London Insurance, and Professors Without Borders, written 16 books, edited 12 books, published over 140 journal articles (including in several IEEE and ACM Transactions) and over 350 conference papers (including in top tier venues such as ACM CCS, ACM KDD, IEEE ICDM, IEEE ICDE, PVLDB, and AAAI), has 7 US patents and participated in several podcasts. She has also written opinion columns and articles on security for venues such as the New York Times, WomensDay.com, Inc. Magazine, the Legal 500, the Connected World, the New York Daily News, the Dallas Morning News, and the D Magazine. Out of the 24 PhD students she has graduated at UT Dallas 12 are female and also include members from a variety of communities. Over the years she has educated a global community including several organizations of the US Department of War (formerly Defense), teaches at the University of Dschang in Cameroon, Africa since 2021 (pro-bono), motivates the general public in practicing cyber hygiene including giving talks at public libraries in DFW. She organizes panels at events such as NIST NICE on engaging rural America in cyber security and teaches and mentors high school students in DFW and across the nation in cyber security during summer (since 2021). Her work has also focused on protecting children from inappropriate content on the web as well using AI for Good to help children, is writing a children’s book that introduces them to cyber security, and supports various charities for children.

Dr. Thuraisingham received her PhD from the University of Wales, Swansea, UK, and the prestigious earned higher doctorate (D. Eng) from the University of Bristol, UK. She has a Certificate in Public Policy Analysis from the London School of Economics and Political Science and one in Terrorism Studies from St. Andrews University in Scotland. She has been featured in various venues including in the book by the ACM in 2024 titled: “Rendering History: The Women of ACM-W” as one of the 30+ “Women that Changed the Face of World Wide Computing Forever.”