Abstract. Bitcoin is quickly emerging as a popular digital payment system. However, in spite of its reliance on pseudonyms, Bitcoin raises a number of privacy concerns due to the fact that all of the transactions that take place are publicly announced in the system. In this paper, we investigate the privacy provisions in Bitcoin when it is used as a primary currency to support the daily transactions of individuals in a university setting. More specifically, we evaluate the privacy that is provided by Bitcoin (i) by analyzing the genuine Bitcoin system and (ii) through a simulator that faithfully mimics the use of Bitcoin within a university. In this setting, our results show that the profiles of almost 40% of the users can be, to a large extent, recovered even when users adopt privacy measures recommended by Bitcoin. To the best of our knowledge, this is the first work that comprehensively analyzes, and evaluates the privacy implications of Bitcoin.

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In this work we present a systematic presentation attack against ECG biometrics. We demonstrate the attack's effectiveness using the Nymi Band, a wrist band that uses electrocardiography (ECG) as a biometric to authenticate the wearer. We instantiate the attack using a hardware-based Arbitrary Waveform Generator (AWG), an AWG software using a computer sound card, and the playback of ECG signals encoded as .wav files using an off-the-shelf audio player. In two sets of experiments we collect data from a total of 41 participants using a variety of ECG monitors, including a medical monitor, a smartphone-based mobile monitor and the Nymi Band itself. We use the first dataset to understand the statistical differences in biometric features that arise from using different measurement devices and modes. Such differences are addressed through the automated derivation of so-called mapping functions, whose purpose is to transform ECG signals from any device in order to resemble the morphology of the signals recorded with the Nymi Band. As part of our second dataset, we enroll users into the Nymi Band and test whether data from any of our sources can be used for a signal injection attack. Using data collected directly on the Nymi Band we achieve a success rate of 81%. When only using data gathered on other devices, this rate decreases to 43% when using raw data, and 62% after applying the mapping function. While we demonstrate the attack on the Nymi Band, we expect other ECG-based authentication systems to most likely suffer from the same, fundamental weaknesses. Permission to freely reproduce all or part of this paper for noncommercial purposes is granted provided that copies bear this notice and the full citation on the first page. Reproduction for commercial purposes is strictly prohibited without the prior written consent of the Internet Society, the first-named author (for reproduction of an entire paper only), and the author's employer if the paper was prepared within the scope of employment.

Eye tracking devices have recently become increasingly popular as an interface between people and consumer-grade electronic devices. Due to the fact that human eyes are fast, responsive, and carry information unique to an individual, analyzing person's gaze is particularly attractive for effortless biometric authentication. Unfortunately, previous proposals for gaze-based authentication systems either suffer from high error rates, or require long authentication times.We build upon the fact that some eye movements can be reflexively and predictably triggered, and develop an interactive visual stimulus for elicitation of reflexive eye movements that supports the extraction of reliable biometric features in a matter of seconds, without requiring any memorization or cognitive effort on the part of the user. As an important benefit, our stimulus can be made unique for every authentication attempt and thus incorporated in a challenge-response biometric authentication system. This allows us to prevent replay attacks, which are possibly the most applicable attack vectors against biometric authentication.Using a gaze tracking device, we build a prototype of our system and perform a series of systematic user experiments with 30 participants from the general public. We investigate the performance and security guarantees under several different attack scenarios and show that our system surpasses existing gaze-based authentication methods both in achieved equal error rates (6.3%) and significantly lower authentication times (5 seconds).

Abstract-Device pairing is the problem of having two devices securely establish a key that can be used to secure subsequent communication. The problem arises every time two devices that do not already share a secret need to bootstrap a secure communication channel. Many solutions exist, all suited to different situations, and all with their own strengths and weaknesses.In this paper, we propose a novel approach to device pairing that applies whenever a user wants to pair two devises that can be physically touched at the same time. The pairing process is easy to perform, even for novice users. A central problem for a device (Alice) running a device pairing protocol, is determining whether the other party (Bob) is in fact the device that we are supposed to establish a key with. Our scheme is based on the idea that two devices can perform device pairing, if they are physically held by the same person (at the same time). In order to pair two devices, a person touches a conductive surface on each device. While the person is in contact with both devices, the human body acts as a transmission medium for intra-body communication and the two devices can communicate through the body. This body channel is used as part of a pairing protocol which allows the devices to agree on a mutual secret and, at the same time, extract physical features to verify that they are being held by the same person. We prove that our device pairing protocol is secure in our threat model and we build a proof of concept set-up and conduct experiments with 15 people to verify the idea in practice.

IEEE 802.15.4z, a standard for Ultra-Wide Band (UWB) secure distance measurement, was adopted in 2020 and the chips that implement this standard are already deployed in mobile phones and in the automotive industry (for Passive Keyless Entry and Start). The standard specifies two different modes-LRP and HRP. Whereas the security of LRP mode has been analyzed, there is no publicly available security analysis of the HRP mode, which is used in different chips like NXP Trimension SR150/SR040, Samsung smartphones, and U1 chip deployed in Apple iPhones. In this work, we perform the first open analysis of the 802.15.4z HRP mode. Our analysis reviews possible attacks on HRP and assesses strategies that an HRP receiver could implement. We show that in realistic deployments, despite countermeasures, HRP is hard to configure to be both performant and secure. If a distance missdetection rate is set to less than 10% (in benign scenarios), the probability of a successful distance shortening attacks ranges from 7% to over 90%.

Bitcoin is a decentralized payment system that relies on Proof-of-Work (PoW) to resist double-spending through a distributed timestamping service. To ensure the operation and security of Bitcoin, it is essential that all transactions and their order of execution are available to all Bitcoin users.Unavoidably, in such a setting, the security of transactions comes at odds with transaction privacy. Motivated by the fact that transaction confirmation in Bitcoin requires tens of minutes, we analyze the conditions for performing successful double-spending attacks against fast payments in Bitcoin, where the time between the exchange of currency and goods is short (in the order of a minute). We show that unless new detection techniques are integrated in the Bitcoin implementation, double-spending attacks on fast payments succeed with considerable probability and can be mounted at low cost. We propose a new and lightweight countermeasure that enables the detection of double-spending attacks in fast transactions.In light of such misbehavior, accountability becomes crucial. We show that in the specific case of Bitcoin, accountability complements privacy. To illustrate this tension, we provide accountability and privacy definition for Bitcoin, and we investigate analytically and empirically the privacy and accountability provisions in Bitcoin.

Secure distance measurement and therefore secure Time-of-Arrival (ToA) measurement is critical for applications such as contactless payments, passive-keyless entry and start systems, and navigation systems. This paper initiates the study of Message Time of Arrival Codes (MTACs) and their security. MTACs represent a core primitive in the construction of systems for secure ToA measurement. By surfacing MTACs in this way, we are able for the first time to formally define the security requirements of physical-layer measures that protect ToA measurement systems against attacks. Our viewpoint also enables us to provide a unified presentation of existing MTACs (such as those proposed in distance-bounding protocols and in a secure distance measurement standard) and to propose basic principles for protecting ToA measurement systems against attacks that remain unaddressed by existing mechanisms. We also use our perspective to systematically explore the tradeoffs between security and performance that apply to all signal modulation techniques enabling ToA measurements.