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2018 IEEE 27th International Symposium on Industrial Electronics (ISIE), Cairns, QLD, Australia Optimizing energy usage is becoming an economic necessity for existing buildings. Non-invasive sensors and sensor networks are key technologies for efficiently achieving this goal, since it is of utmost importance that existing hydraulic systems are not changed and the engineering effort for installation remains minimal. This paper presents a data-driven approach that should allow low-cost installation of sensors at arbitrary points of the building and then retrieve the structure of the hydraulic system from the recorded sensor values. The architecture as well as first preliminary results from field test buildings are presented. Energie-Umweltmanagement Forschung Burgenland

With the rise of sensors such as the Microsoft Kinect, Leap Motion, and hand motion sensors in phones (i.e., Samsung Galaxy S6), gesture-based interfaces have become practical. Unfortunately, today, to recognize such gestures, applications must have access to depth and video of the user, exposing sensitive data about the user and her environment. Besides these privacy concerns, there are also security threats in sensor-based applications, such as multiple applications registering the same gesture, leading to a conflict (akin to Clickjacking on the web). We address these security and privacy threats with Prepose, a novel domain-specific language (DSL) for easily building gesture recognizers, combined with a system architecture that protects privacy, security, and reliability with untrusted applications. We run Prepose code in a trusted core, and only return specific gesture events to applications. Prepose is specifically designed to enable precise and sound static analysis using SMT solvers, allowing the system to check security and reliability properties before running a gesture recognizer. We demonstrate that Prepose is expressive by creating gestures in three representative domains: physical therapy, tai-chi, and ballet. We further show that runtime gesture matching in Prepose is fast, creating no noticeable lag, as measured on traces from Microsoft Kinect runs. To show that gesture checking at the time of submission to a gesture store is fast, we developed a total of four Z3-based static analyses to test for basic gesture safety and internal validity, to make sure the so-called protected gestures are not overridden, and to check inter-gesture conflicts. Our static analysis scales well in practice: safety checking is under 0.5 seconds per gesture, average validity checking time is only 188ms, lastly, for 97% of the cases, the conflict detection time is below 5 seconds, with only one query taking longer than 15 seconds.

Within the next year, travelers from dozens of nations may be carrying a new form of passport in response to a mandate by the United States government. The e-passport, as it is sometimes called, represents a bold initiative in the deployment of two new technologies: Radio-Frequency Identification (RFID) and biometrics. Important in their own right, e-passports are also the harbinger of a wave of next-generation ID cards: several national governments plan to deploy identity cards integrating RFID and biometrics for domestic use. We explore the privacy and security implications of this impending worldwide experiment in next-generation authentication technology. We describe privacy and security issues that apply to e-passports, then analyze these issues in the context of the International Civil Aviation Organization (ICAO) standard for e-passports.