2,456 research outputs found
Unconventional TV Detection using Mobile Devices
Recent studies show that the TV viewing experience is changing giving the
rise of trends like "multi-screen viewing" and "connected viewers". These
trends describe TV viewers that use mobile devices (e.g. tablets and smart
phones) while watching TV. In this paper, we exploit the context information
available from the ubiquitous mobile devices to detect the presence of TVs and
track the media being viewed. Our approach leverages the array of sensors
available in modern mobile devices, e.g. cameras and microphones, to detect the
location of TV sets, their state (ON or OFF), and the channels they are
currently tuned to. We present the feasibility of the proposed sensing
technique using our implementation on Android phones with different realistic
scenarios. Our results show that in a controlled environment a detection
accuracy of 0.978 F-measure could be achieved.Comment: 4 pages, 14 figure
Conceivable security risks and authentication techniques for smart devices
With the rapidly escalating use of smart devices and fraudulent transaction of users’ data from their devices, efficient and reliable techniques for authentication of the smart devices have become an obligatory issue. This paper reviews the security risks for mobile devices and studies several authentication techniques available for smart devices. The results from field studies enable a comparative evaluation of user-preferred authentication mechanisms and their opinions about reliability, biometric authentication and visual authentication techniques
CardioCam: Leveraging Camera on Mobile Devices to Verify Users While Their Heart is Pumping
With the increasing prevalence of mobile and IoT devices (e.g., smartphones, tablets, smart-home appliances), massive private and sensitive information are stored on these devices. To prevent unauthorized access on these devices, existing user verification solutions either rely on the complexity of user-defined secrets (e.g., password) or resort to specialized biometric sensors (e.g., fingerprint reader), but the users may still suffer from various attacks, such as password theft, shoulder surfing, smudge, and forged biometrics attacks. In this paper, we propose, CardioCam, a low-cost, general, hard-to-forge user verification system leveraging the unique cardiac biometrics extracted from the readily available built-in cameras in mobile and IoT devices. We demonstrate that the unique cardiac features can be extracted from the cardiac motion patterns in fingertips, by pressing on the built-in camera. To mitigate the impacts of various ambient lighting conditions and human movements under practical scenarios, CardioCam develops a gradient-based technique to optimize the camera configuration, and dynamically selects the most sensitive pixels in a camera frame to extract reliable cardiac motion patterns. Furthermore, the morphological characteristic analysis is deployed to derive user-specific cardiac features, and a feature transformation scheme grounded on Principle Component Analysis (PCA) is developed to enhance the robustness of cardiac biometrics for effective user verification. With the prototyped system, extensive experiments involving 25 subjects are conducted to demonstrate that CardioCam can achieve effective and reliable user verification with over 99% average true positive rate (TPR) while maintaining the false positive rate (FPR) as low as 4%
Eavesdropping Whilst You're Shopping: Balancing Personalisation and Privacy in Connected Retail Spaces
Physical retailers, who once led the way in tracking with loyalty cards and
`reverse appends', now lag behind online competitors. Yet we might be seeing
these tables turn, as many increasingly deploy technologies ranging from simple
sensors to advanced emotion detection systems, even enabling them to tailor
prices and shopping experiences on a per-customer basis. Here, we examine these
in-store tracking technologies in the retail context, and evaluate them from
both technical and regulatory standpoints. We first introduce the relevant
technologies in context, before considering privacy impacts, the current
remedies individuals might seek through technology and the law, and those
remedies' limitations. To illustrate challenging tensions in this space we
consider the feasibility of technical and legal approaches to both a) the
recent `Go' store concept from Amazon which requires fine-grained, multi-modal
tracking to function as a shop, and b) current challenges in opting in or out
of increasingly pervasive passive Wi-Fi tracking. The `Go' store presents
significant challenges with its legality in Europe significantly unclear and
unilateral, technical measures to avoid biometric tracking likely ineffective.
In the case of MAC addresses, we see a difficult-to-reconcile clash between
privacy-as-confidentiality and privacy-as-control, and suggest a technical
framework which might help balance the two. Significant challenges exist when
seeking to balance personalisation with privacy, and researchers must work
together, including across the boundaries of preferred privacy definitions, to
come up with solutions that draw on both technology and the legal frameworks to
provide effective and proportionate protection. Retailers, simultaneously, must
ensure that their tracking is not just legal, but worthy of the trust of
concerned data subjects.Comment: 10 pages, 1 figure, Proceedings of the PETRAS/IoTUK/IET Living in the
Internet of Things Conference, London, United Kingdom, 28-29 March 201
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