Security and Privacy in Internet of Things (IoTs): Models, Algorithms, and Implementations is published by CRC Press on April 1, 2016. This book has 604 pages in English, ISBN-10 1498723187, ISBN-13 978-1498723183. PDF is available for download below.
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.