This document summarises the results of several research campaigns over the past seven years. The main connecting theme is the physical layer of widely deployed sensors in Pervasive Computing domains. In particular, we have focused on the RF-channel or on ambient audio. The initial problem from which we started this work was that of distributed adaptive transmit beamforming. We have been looking for a simple method to align the phases of jointly transmitting nodes (e.g. sensor or IoT nodes). The algorithmic solution to this problem was to implement a distributed random optimisation method on the participating nodes in which the transmitters and the receiver follow an iterative question-and-answer scheme. We have been able to derive sharp asymptotic bounds on the expected optimisation time of an evolutionary random optimiser and presented an asymptotically optimal approach. One thing that we have learned from the work on these physical layer algorithms was that the signals we work on are fragile and perceptive to physical environmental changes. These could be obstacles such as furniture, opened or closed windows or doors as well as movement of individuals. This observation motivated us to view the wireless interface as a sensor for environmental changes in Pervasive Computing environments. Another use of physical layer RF-signals is for security applications. We are currently working to further push these mentioned directions and novel fields of physical prototyping. In particular, the calculation of mathematical operations on the wireless channel at the time of transmission appears to contain good potential for gains in efficiency for communication and computation in Pervasive Computing domains.
@cite_28: 
@cite_109: 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.
@cite_226: Small, mobile devices without user interfaces, such as Bluetooth headsets, often need to communicate securely over wireless networks. Active attacks can only be prevented by authenticating wireless communication, which is problematic when devices do not have any a priori information about each other. We introduce a new method for device-to-device authentication by shaking devices together. This paper describes two protocols for combining cryptographic authentication techniques with known methods of accelerometer data analysis to the effect of generating authenticated, secret keys. The protocols differ in their design, one being more conservative from a security point of view, while the other allows more dynamic interactions. Three experiments are used to optimize and validate our proposed authentication method.
@cite_84: Current mechanisms for authenticating communication between devices that share no prior context are inconvenient for ordinary users, without the assistance of a trusted authority. We present and analyze seeing-is-believing, a system that utilizes 2D barcodes and camera-telephones to implement a visual channel for authentication and demonstrative identification of devices. We apply this visual channel to several problems in computer security, including authenticated key exchange between devices that share no prior context, establishment of a trusted path for configuration of a TCG-compliant computing platform, and secure device configuration in the context of a smart home.
@cite_72: In this paper we present a signal processing methodology for sharing symmetric keys in personal area networks. Symmetric encryption and decryption are commonly used because of limitations in computing power and energy consumption. However, key sharing still imposes challenges regarding usability, computational complexity of algebraic key exchange algorithms, and security. Our approach is that keys are generated locally on devices by shaking them, and that the keys are equal if and only if the devices are shaken together. Based on practical assessments, we show that the key generation algorithm is able to generate keys from acceleration data with an average entropy of 13bit key in 70 of the cases.
@cite_181: Ubiquitous computing is associated with a vision of everything being connected to everything. However, for successful applications to emerge, it will not be the quantity but the quality and usefulness of connections that will matter. Our concern is how qualitative relations and more selective connections can be established between smart artefacts, and how users can retain control over artefact interconnection. We propose context proximity for selective artefact communication, using the context of artefacts for matchmaking. We further suggest to empower users with simple but effective means to impose the same context on a number of artefacts. To prove our point we have implemented Smart-Its Friends, small embedded devices that become connected when a user holds them together and shakes them.
@cite_201: Hard restrictions in computing power and energy consumption favour symmetric key methods to encrypt the communication in wireless body area networks which in term impose questions on effective and user-friendly unobtrusive ways for key distribution. In this paper, we present a novel approach to establish a secure connection between two devices by shaking them together. Instead of distributing or exchanging a key, the devices independently generate a key from the measured acceleration data by appropriate signal processing methods. Exhaustive practical experiments based on acceleration data gathered from real hardware prototypes have shown that in about 80 of the cases, a common key can be successfully generated. The average entropy of these generated keys exceed 13bits.
Contextual or sensor information of mobile devices can be incorporated as a solution for authentication @cite_181 . When the seed to the key is implicit with the context, no information that could be used to reconstruct the key is transmitted during key generation. For instance, @cite_84 introduced , utilizing the camera of a mobile device to capture a 2D barcode which is displayed on the screen of another device. of @cite_28 implements a similar scheme but exploits spoken audio. A user reads aloud a text message displayed on one device and a second device recognizes the speech for authentication. A further example mechanism by @cite_226 uses accelerometer readings when devices are shaken simultaneously by a single person. Also, Mayrhofer derived in @cite_109 that the sharing of secret keys is possible with a similar protocol by repeatedly exchanging hashes of key-sub-sequences until a common secret is found. generalise this approach to noisy acceleration readings @cite_72 @cite_201 . They utilize a hash function that maps similar acceleration patterns to identical key sequences. These approaches require explicit user interaction.