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Smartapp code11/28/2023 ![]() ![]() Jokar, P., Arianpoo, N., Leung, V.C.M.: Spoofing Detection in IEEE 802.15.4 Networks Based on Received Signal Strength. In: The Network and Distributed System Security Symposium (NDSS) (2017) Jia, Y.J., Chen, Q.A., Wang, S., Rahmati, A., Fernandes, E., Mao, Z.M., Prakash, A.: ContexIoT: Towards providing contextual integrity to appified IoT platforms. JFR, ABR and NOBRIOT: Z-wave command class specification (2016). In: USENIX Security Symposium (USENIX Security) (2016) įernandes, E., Paupore, J., Rahmati, A., Simionato, D., Conti, M., Prakash, A.: FlowFence: practical data protection for emerging IoT application frameworks. In: 2016 IEEE Symposium on Security and Privacy (SP), pp. In: IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks (SECON) (2007)įernandes, E., Jung, J., Prakash, A.: Security analysis of emerging smart home applications. In: Dictionary of Algorithms and Data Structures (2008)Ĭhen, Y., Trappe, W., Martin, R.P.: Detecting and localizing wireless spoofing attacks. KeywordsĪlliance, Z.: Zigbee specification (2012). By injecting spoofing traffic, HoMonit obfuscates the SmartApp traffic pattern sufficiently to defeat inference attacks against the smart home network while preserving the capability of detecting misbehaved SmartApps. Moreover, as the same side-channel vector can be exploited by a close-by attacker to breach the privacy of the residents, we further propose a privacy enhancement module. The evaluation results suggest that HoMonit can effectively validate the working logic of SmartApps and achieve high accuracy in the detection of SmartApp misbehaviors. These malicious SmartApps either perform over-privileged accesses to smart devices or conduct event-spoofing attacks. To evaluate the effectiveness of HoMonit, we perform the evaluation on 60 malicious SmartApps in Samsung SmartThings platform. To detect misbehavior, HoMonit compares the SmartApps activities inferred from the encrypted traffic with their expected behaviors dictated in their source code. To address these problems, this chapter leverages side-channel inference capabilities to design and develop a system, dubbed HoMonit, to monitor SmartApps from encrypted wireless traffic. In the application platform layer, due to several security flaws in the design, there are malicious smart home apps (or SmartApps) to possess more privileges than they were designed and to eavesdrop or spoof events. ![]()
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