The text highlights a comprehensive survey that focuses on all security aspects and challenges facing the Internet of Things systems, including outsourcing techniques for partial computations on edge or cloud while presenting case studies to map security challenges. It further covers three security aspects including Internet of Things device identification and authentication, network traffic intrusion detection, and executable malware files detection.
This book:
- Presents a security framework model design named Behavioral Network Traffic Identification and Novelty Anomaly Detection for the IoT Infrastructures
- Highlights recent advancements in machine learning, deep learning, and networking standards to boost Internet of Things security
- Builds a near real-time solution for identifying Internet of Things devices connecting to a network using their network traffic traces and providing them with sufficient access privileges
- Develops a robust framework for detecting IoT anomalous network traffic
- Covers an anti-malware solution for detecting malware targeting embedded devices
It will serve as an ideal text for senior undergraduate and graduate students, and professionals in the fields of electrical engineering, electronics and communication engineering, computer engineering, and information technology.
Betal nemt med kort, Klarna, Apple Pay eller Google Pay. Ikke tilfreds? Du har altid 14 dages fortrydelsesret. Læs mere i vores vilkår. Har du spørgsmål, så send os en mail på hello@memmo.org.
Memmo gør det nemmere at studere – uanset hvor du er i verden. Hos os samler du dine kursusbøger og smarte studieværktøjer ét sted: resuméer, quizzer, podcasts og flashcards. Og så er der Ted, din studieven, der svarer på alt, du undrer dig over. Over 50 000 studerende studerer allerede her – bygget til at hjælpe dig med at lære hurtigere og stresse mindre.