Anomaly behavior analysis for IoT sensors

Abstract

The Internet of Things (IoT) will not only connect computers and mobile devices but also interconnect smart buildings, homes, and cities, as well as electrical grids, gas, and water networks, automobiles, airplanes, etc. IoT will lead to the development of a wide range of advanced information services that need to be processed in real time and require large storage and computational power. The integration of IoT with fog and cloud computing not only brings the computational requirements but also enables IoT services to be pervasive, cost‐effective, and accessible from anywhere and at anytime. In any IoT application, sensors are indispensable to bring the physical world into the digital world that can be implemented by leveraging fog computing. However, IoT sensors will introduce major security challenges as they contribute to a significant increase in the IoT attack surface. In this paper, we present a methodology to develop an intrusion detection system on the basis of anomaly behavior analysis to detect when a sensor has been compromised and used to provide misinformation. Our preliminary experimental results show that our approach can accurately authenticate sensors on the basis of their behavior and can detect known and unknown sensor attacks with high detection rate and low false alarms.

A collaborative mobile edge computing and user solution for service composition in 5G systems

“…The issues of security and privacy in fog and mobile edge computing are also a concern that many researchers are considering in their work. The authors of related works– have briefly presented these issues and considered some counter measurements. A selective forwarding model that provides monitoring capabilities for detecting malicious nodes and tracing nodes' movements has been presented in the work of Yaseen et al The model has shown huge improvements in terms of detecting malicious nodes by leveraging the fog computing infrastructure.…”

“…Integration of IoT devices with fog computing has enabled richer IoT services that are cost effective and allow for accessibility from anywhere at any time . However, there are some major security challenges that need to be considered.…”

“…However, there are some major security challenges that need to be considered. Pacheco and Hariri developed an intrusion detection system model for fog computing to detect when an IoT sensor is under attack or is being compromised. Experimental results have shown that the proposed model accurately identifies known and unknown sensor attacks.…”

EdgeCloudSim: An environment for performance evaluation of edge computing systems

“…A crucial challenge in proposing a new edge computing solution is to realistically assess the performance of the envisioned system while considering the relevant engineering parameters. The researchers can use the real cloud environments, experimental test beds, or simulators to evaluate their approaches. There are pros and cons in selection of these options.…”

Batch‐based security‐aware spectrum sharing with simultaneous assignment decisions in time‐critical IoT networks with cognitive radio capabilities

“…One critical requirement in enabling efficient CRIoT networking with time‐critical traffic is operating under the unavailability security threat . In CRIoT networks, the unavailability threat is defined by the denial of a CRIoT device from successfully delivering data packets within a given delay requirements by disrupting/jamming the communications over the selected channel(s) .…”