1,287 research outputs found

    Securing Cyber-Physical Social Interactions on Wrist-worn Devices

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    Since ancient Greece, handshaking has been commonly practiced between two people as a friendly gesture to express trust and respect, or form a mutual agreement. In this article, we show that such physical contact can be used to bootstrap secure cyber contact between the smart devices worn by users. The key observation is that during handshaking, although belonged to two different users, the two hands involved in the shaking events are often rigidly connected, and therefore exhibit very similar motion patterns. We propose a novel key generation system, which harvests motion data during user handshaking from the wrist-worn smart devices such as smartwatches or fitness bands, and exploits the matching motion patterns to generate symmetric keys on both parties. The generated keys can be then used to establish a secure communication channel for exchanging data between devices. This provides a much more natural and user-friendly alternative for many applications, e.g., exchanging/sharing contact details, friending on social networks, or even making payments, since it doesn’t involve extra bespoke hardware, nor require the users to perform pre-defined gestures. We implement the proposed key generation system on off-the-shelf smartwatches, and extensive evaluation shows that it can reliably generate 128-bit symmetric keys just after around 1s of handshaking (with success rate >99%), and is resilient to different types of attacks including impersonate mimicking attacks, impersonate passive attacks, or eavesdropping attacks. Specifically, for real-time impersonate mimicking attacks, in our experiments, the Equal Error Rate (EER) is only 1.6% on average. We also show that the proposed key generation system can be extremely lightweight and is able to run in-situ on the resource-constrained smartwatches without incurring excessive resource consumption

    Secure store and forward proxy for dynamic IoT applications over M2M networks

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    Internet of Things (IoT) applications are expected to generate a huge unforeseen amount of traffic flowing from Consumer Electronics devices to the network. In order to overcome existing interoperability problems, several standardization bodies have joined to bring a new generation of Machine to Machine (M2M) networks as a result of the evolution of wireless sensor/actor networks and mobile cellular networks to converged networks. M2M is expected to enable IoT paradigms and related concepts into a reality at a reasonable cost. As part of the convergence, several technologies preventing new IoT services to interfere with existing Internet services are flourishing. Responsive, message-driven, resilient and elastic architectures are becoming essential parts of the system. These architectures will control the entire data flow for an IoT system requiring sometimes to store, shape and forward data among nodes of a M2M network to improve network performance. However, IoT generated data have an important personal component since it is generated in personal devices or are the result of the observation of the physical world, so rises significant security concerns. This article proposes a novel opportunistic flexible secure store and forward proxy for M2M networks and its mapping to asynchronous protocols that guarantees data confidentiality
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