The thermal camera can capture keyboard surface temperature change after a human's touch. This phenomenon may be used to steal users' passwords physically. In this paper, based on the study of thermal dynamics of keyboards, we design a password break system using an infrared thermal camera. First, we build a signal model to describe the dynamic process of temperature change on the keyboard using Newton's law of cooling. Next, we develop a maximum likelihood parameter estimation algorithm to estimate the keystroke time instants. Then, by maximizing the probability of key order arrangement, a novel password breaking algorithm is developed. Our algorithm is tested using simulated data as well as real-world data. Experiment results show that our algorithm is effective for physical password breaking using thermal characteristics. Based on our results, we discuss strategies for password protection at the end.
Additive manufacturing (AM, or 3D printing) is a novel manufacturing technology that has been adopted in industrial and consumer settings. However, the reliance of this technology on computerization has raised various security concerns. In this paper, we address issues associated with sabotage via tampering during the 3D printing process by presenting an approach that can verify the integrity of a 3D printed object. Our approach operates on acoustic side-channel emanations generated by the 3D printer's stepper motors, which results in a non-intrusive and real-time validation process that is difficult to compromise. The proposed approach constitutes two algorithms. The first algorithm is used to generate a master audio fingerprint for the verifiable unaltered printing process. The second algorithm is applied when the same 3D object is printed again, and this algorithm validates the monitored 3D printing process by assessing the similarity of its audio signature with the master audio fingerprint. To evaluate the quality of the proposed thresholds, we identify the detectability thresholds for the following minimal tampering primitives: insertion, deletion, replacement, and modification of a single tool path command. By detecting the deviation at the time of occurrence, we can stop the printing process for compromised objects, thus saving time and preventing material waste. We discuss various factors that impact the method, such as background noise, audio device changes, and different audio recorder positions.
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CALL FOR PROPOSALS
The IEEE Signal Processing Society is accepting proposals for the 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP®). SPS Members are invited to submit a proposal to host ICASSP. If you are interested in submitting a proposal, please reference our ICASSP Proposal Guidelines.
ICASSP is the world’s largest and most comprehensive technical conference focused on signal processing applications. The series is sponsored by the IEEE Signal Processing Society and has been held annually since 1976. The conference features world-class speakers, tutorials, exhibits, and over 170 lecture and poster sessions. ICASSP is a cooperative effort of the IEEE Signal Processing Technical Committees:
To submit a proposal, send a notice of intent to bid to the Vice President – Conferences, Prof. Wan-Chi Siu and SPS Conference Services Staff at firstname.lastname@example.org. Include in the notice your contact information and the proposed location. Conference Services Staff will issue the proposal submission form and guidelines upon receipt of the letter of intent. The form must be completed and the proposal submitted to email@example.com by 19 January 2015. Proposals will be assessed by the Conference Board Executive Subcommittee. Accepted bidding teams [finalists] will be invited to present at the Conference Board meeting held at ICASSP 2015, April 19-24, 2015 in Melbourne, Australia.
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