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With the widespread use of smart devices, device authentication has received much attention. One popular method for device authentication is to utilize internally measured device fingerprints, such as device ID, software or hardware-based characteristics. In this article, we propose DeMiCPU , a stimulation-response-based device fingerprinting technique that relies on externally measured information, i.e., magnetic induction (MI) signals emitted from the CPU module that consists of the CPU chip and its affiliated power-supply circuits. The key insight of DeMiCPU is that hardware discrepancies essentially exist among CPU modules and thus the corresponding MI signals make promising device fingerprints, which are difficult to be modified or mimicked. We design a stimulation and a discrepancy extraction scheme and evaluate them with 90 mobile devices, including 70 laptops (among which 30 are of totally identical CPU and operating system) and 20 smartphones. The results show that DeMiCPU can achieve 99.7% precision and recall on average, and 99.8% precision and recall for the 30 identical devices, with a fingerprinting time of 0.6~s. The performance can be further improved to 99.9% with multi-round fingerprinting. In addition, we implement a prototype of DeMiCPU docker, which can effectively reduce the requirement of test points and enlarge the fingerprinting area.

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Nowadays, most Internet of Things devices in smart homes rely on radio frequency channels for communication, making them exposed to various attacks such as spoofing and eavesdropping attacks. Existing methods using encryption keys may be inapplicable on these resource-constrained devices that cannot afford the computationally expensive encryption operations. Thus, in this article, we design a key-free communication method for such devices in a smart home. In particular, we introduce the Home-limited Channel (HLC) that can be accessed only within a house yet inaccessible for outside-house attackers. Utilizing HLCs, we propose HlcAuth, a challenge-response mechanism to authenticate the communications between smart devices without keys. The advantages of HlcAuth are low cost, lightweight as well as key-free, and requiring no human intervention. According to the security analysis, HlcAuth can defeat replay attacks, message-forgery attacks, and man-in-the-middle (MiTM) attacks, among others. We further evaluate HlcAuth in four different physical scenarios, and results show that HlcAuth achieves 100% true positive rate (TPR) within 4.2m for in-house devices while 0% false positive rate (FPR) for outside attackers, i.e., guaranteeing a high-level usability and security for in-house communications. Finally, we implement HlcAuth in both single-room and multi-room scenarios.

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