1,626 research outputs found

    Security analysis of network anomalies mitigation schemes in IoT networks

    Get PDF
    The Internet of Things (IoT) is on the rise and it is giving a new shape to several fields such as smart cities, smart homes, smart health, etc. as it facilitates the connection of physical objects to the internet. However, this advancement comes along with new challenges in terms of security of the devices in the IoT networks. Some of these challenges come as network anomalies. Hence, this has prompted the use of network anomaly mitigation schemes as an integral part of the defense mechanisms of IoT networks in order to protect the devices from malicious users. Thus, several schemes have been proposed to mitigate network anomalies. This paper covers a review of different network anomaly mitigation schemes in IoT networks. The schemes' objectives, operational procedures, and strengths are discussed. A comparison table of the reviewed schemes, as well as a taxonomy based on the detection methodology, is provided. In contrast to other surveys that presented qualitative evaluations, our survey provides both qualitative and quantitative evaluations. The UNSW-NB15 dataset was used to conduct a performance evaluation of some classification algorithms used for network anomaly mitigation schemes in IoT. Finally, challenges and open issues in the development of network anomaly mitigation schemes in IoT are discussed

    Secure Distributed Dynamic State Estimation in Wide-Area Smart Grids

    Full text link
    Smart grid is a large complex network with a myriad of vulnerabilities, usually operated in adversarial settings and regulated based on estimated system states. In this study, we propose a novel highly secure distributed dynamic state estimation mechanism for wide-area (multi-area) smart grids, composed of geographically separated subregions, each supervised by a local control center. We firstly propose a distributed state estimator assuming regular system operation, that achieves near-optimal performance based on the local Kalman filters and with the exchange of necessary information between local centers. To enhance the security, we further propose to (i) protect the network database and the network communication channels against attacks and data manipulations via a blockchain (BC)-based system design, where the BC operates on the peer-to-peer network of local centers, (ii) locally detect the measurement anomalies in real-time to eliminate their effects on the state estimation process, and (iii) detect misbehaving (hacked/faulty) local centers in real-time via a distributed trust management scheme over the network. We provide theoretical guarantees regarding the false alarm rates of the proposed detection schemes, where the false alarms can be easily controlled. Numerical studies illustrate that the proposed mechanism offers reliable state estimation under regular system operation, timely and accurate detection of anomalies, and good state recovery performance in case of anomalies
    • …
    corecore