Security and Privacy in Internet of Things (IoTs)
Models, Algorithms, and Implementations
The Internet of Things (IoT) has attracted strong interest from both academia and industry. Unfortunately, it has also attracted the attention of hackers. Security and Privacy in Internet of Things (IoTs): Models, Algorithms, and Implementations brings together some of the top IoT security experts from around the world who contribute their knowledge regarding different IoT security aspects. It answers the question "How do we use efficient algorithms, models, and implementations to cover the four important aspects of IoT security, i.e., confidentiality, authentication, integrity, and availability?"
The book consists of five parts covering attacks and threats, privacy preservation, trust and authentication, IoT data security, and social awareness. The first part introduces all types of IoT attacks and threats and demonstrates the principle of countermeasures against those attacks. It provides detailed introductions to specific attacks such as malware propagation and Sybil attacks. The second part addresses privacy-preservation issues related to the collection and distribution of data, including medical records. The author uses smart buildings as an example to discuss privacy-protection solutions.
The third part describes different types of trust models in the IoT infrastructure, discusses access control to IoT data, and provides a survey of IoT authentication issues. The fourth part emphasizes security issues during IoT data computation. It introduces computational security issues in IoT data processing, security design in time series data aggregation, key generation for data transmission, and concrete security protocols during data access. The fifth and final part considers policy and human behavioral features and covers social-context-based privacy and trust design in IoT platforms as well as policy-based informed consent in the IoT.
Table of Contents
Internet of Things (IoT) as Interconnection of Threats (IoT). Attack, Defense, and Network Robustness of Internet of Things. Sybil Attack Detection in Vehicular Networks. Malware Propagation and Control in Internet of Things. Solution-Based Analysis of Attack Vectors on Smart Home Systems. Privacy Preservation Data Dissemination. Privacy Preservation for IoT Used in Smart Buildings. Social Features for Location Privacy Enhancement in Internet of Vehicles. Lightweight and Robust Schemes for Privacy Protection in Key Personal IoT Applications: Mobile WBSN and Participatory Sensing. Trust and Trust Models for the IoT. Self-Organizing "Things" and Their Software Representatives. Preventing Unauthorized Access to Sensor Data. Authentication in IoT. Computational Security for the IoT and Beyond. Privacy-Preserving Time Series Data Aggregation for Internet of Things. Secure Path Generation Scheme for Real-Time Green Internet of Things. Security Protocols for IoT Access Networks. User-Centric Decentralized Governance Framework for Privacy and Trust in IoT. Policy-Based Approach for Informed Consent in Internet of Things. Security and Impact of the Internet of Things (IoT) on Mobile Networks.
Fei Hu is a professor in the Department of Electrical and Computer Engineering at the University of Alabama, Tuscaloosa. He earned his PhDs at Tongji University, Shanghai, China, in the field of signal processing in 1999, and at Clarkson University, New York, in electrical and computer engineering in 2002. He has published over 200 journal/conference papers and books. Dr. Hu’s research has been supported by the U.S. National Science Foundation, Cisco, Sprint, and other sources. His research expertise may be summarized as 3S: security, signals, and sensors. Recently, he has focused on cyberphysical system security and medical security issues.