| Abstrakt: |
With a vast array of smart and connected devices and applications available in many areas, including green IoT-based agriculture, smart farming, smart homes, smart transportation, smart health, smart grid, smart cities, and smart environment, the Internet of Things (IoT) technology has emerged to enhance people's lives. IoT devices are susceptible to cyberattacks. Though, researchers have sufficiently embraced the use of diverse techniques and algorithms as a means of securing data and information generated and transmitted in the Internet of Things ecosystem. Additionally, these techniques have been effectively applied in a number of domains, demonstrating its superiority in tackling intrusion detection attacks. The anomaly-based Intrusion Detection System (IDS) has an edge in identifying zero-day attacks because signature-based detection is limited when it comes to unknown threats. Therefore, this paper explicitly and systematically analyzed current techniques deployed in IoT ecosystem for the detection of anomaly-based intrusion attacks. Also, the processes and functionalities adopted by the techniques to predict the abnormality-based intrusion attacks, development and simulation tools adopted to implement and evaluate the effectiveness and performance of the techniques are highlight and discussed extensively. Finally, a summary of challenges and weaknesses of the techniques are briefly discussed, for onward investigation in future researches. [ABSTRACT FROM AUTHOR] |
