On-body devices are an intrinsic part of the Internet-of-Things (IoT) vision to provide human-centric services. These on-body IoT devices are largely embedded devices that lack a sophisticated user interface to facilitate traditional Pre-Shared Key based security protocols. Motivated by this real-world security vulnerability, this paper proposes SecureTag, a system designed to add defense in depth against active attacks by integrating physical layer (PHY) information with upper-layer protocols. The underpinning of SecureTag is a signal processing technique that extracts the peculiar propagation characteristics of creeping waves to discern on-body devices. Upon overhearing a suspicious transmission, SecureTag initiates a PHY-based challenge-response protocol to mitigate attacks. We implement our system on different commercial off-the-shelf (COTS) wearables and a smartphone. Extensive experiments are conducted in a lab, apartments, malls, and outdoor areas, involving 12 volunteer subjects of different age groups, to demonstrate the robustness of our system. Results show that our system can mitigate 96.13 of active attack attempts while triggering false alarms on merely 5.64 of legitimate traffic.
The shared secrets can be generated from user interactions, auxiliary channels, or authenticated with user actions or auxiliary channel. Examples of the former include gesture-based authentication @cite_15 @cite_0 that encodes authentication information as gestures defined by authenticators or users, and the techniques that require users to simultaneously provide the same drawings @cite_11 or shaking trajectories @cite_12 . The auxiliary channel based approaches leverage a special channel to create shared secrets. Many studies use ambient environments, such as ambient sound @cite_41 @cite_20 , or a combination of multiple environments @cite_30 as the proof of physical proximity. The auxiliary channel itself is also leveraged as the source to generate shared secrets. Normally, the two devices send messages to each other within a short time to measure the channel between them. Electromyography (EMG) sensors are leveraged in @cite_37 to capture the electrical activities caused by human muscle contractions, which are encoded into secret bits to pair devices in contact with one hand. @cite_13 use the frequency shapes of the wireless channel between two devices to generate secret bits. Similarly, @cite_5 use the channel sate information (CSI) as shared secrets.
@cite_30 @cite_37 @cite_41 @cite_0 @cite_5 @cite_15 @cite_20 @cite_13 @cite_12 @cite_11
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New approaches that generate secret keys from radio channel characteristics have been recently proposed. The security of these schemes usually relies on the reciprocity principle which states that the channel fluctuations can be a source of common randomness for two communicating peers and these fluctuations can't be measured by any eavesdropper. A validation of these properties for indoor environments is presented in this work. The shared keys are created by measuring the reciprocal channel features and converting this information to binary vectors using a quantization algorithm. This paper addresses the problem of quantization. It identifies an important weakness of existing key generation algorithms and it shows that the secret bits extraction has a significant impact on the robustness and security of these algorithms. A new adaptive quantization algorithm for secret key generation is presented. This method has the advantages to create sufficient long secret keys with a high key agreement ratio between authorized users without revealing information to the attacker. The new scheme is experimentally validated using Ultra Wide Band technology. Existing secret key extraction techniques use quantization to map wireless channel amplitudes to secret bits. This paper shows that such techniques are highly prone to environment and local noise effects: They have very high mismatch rates between the two nodes that measure the channel between them. This paper advocates using the shape of the channel instead of the size (or amplitude) of the channel. It shows that this new paradigm shift is significantly robust against environmental and local noises. We refer to this shape-based technique as Puzzle. Implementation in a software-defined radio (SDR) platform demonstrates that Puzzle has a 63 reduction in bit mismatch rate than the state-of-art frequency domain approach (CSI-2bit). Experiments also show that unlike the state-of-the-art received signal strength (RSS)-based methods like ASBG, Puzzle is robust against an attack in which an eavesdropper can predict the secret bits using planned movements. Secure communication over wireless channels necessitates authentication of communication partners to prevent man-in-the-middle attacks. For spontaneous interaction between independent, mobile devices, no a priori information is available for authentication purposes. However, traditional approaches based on manual password input or verification of key fingerprints do not scale to tens to hundreds of interactions a day, as envisioned by future ubiquitous computing environments. One possibility to solve this problem is authentication based on similar sensor data: when two (or multiple) devices are in the same situation, and thus experience the same sensor readings, this constitutes shared, (weakly) secret information. This paper introduces the Candidate Key Protocol (CKP) to interactively generate secret shared keys from similar sensor data streams. It is suitable for two-party and multi-party authentication, and supports opportunistic authentication. It has been shown that the radio channel impulse response for a pair of legitimate Ultra-wide band (UWB) transceivers can be used to generate secret keys for secure communications. Past proposed secret key generation algorithms under-exploited the available number of secret key bits from the radio channel. This paper proposes a new efficient method for generation of the shared key where the transceivers use LDPC decoders to resolve the differences in their channel impulse response measurements caused by measurement noise. To ensure secret key agreement, a method of public discussion between the two users is performed using the syndrome from Hamming (7,3) binary codes. An algorithm is proposed to check the equality of generated keys for both legitimate users, and ensure error-free secure communication. The security of this algorithm has been verified by AVISPA. Comparisons are performed with previous work on secret key generation and it has been shown that this algorithm reliably generates longer secret keys in standard UWB radio channels.