Hardware Trojan is increasingly becoming a major threat in the filed of hardware security. To solve that security threat, we propose a novel strategy for hardware Trojan detection combining trustworthy design with thermal radiation analysis. We use ring oscillators to fill the vulnerable area of target IC, and their layouts can serve as the trustworthy reference. Ring oscillator's thermal radiation is related to its stage, so that the location and stage of ring oscillators can be extracted from thermal maps by k-means clustering. Removing, breaking or degrading ring oscillators to insert a hardware Trojan can be detected by thermal radiation analysis. Therefore, our countermeasure can efficiently and conveniently detect the insertion of hardware Trojan without fabricated golden-chip. Experimental results on FPGA show that our countermeasure can accurately identify the thermal radiation change of ring oscillators and be used for hardware Trojan detection.

Hardware trojan (HT) is increasingly becoming a major threat in the integrated circuit (IC) industry. Among all the countermeasures, academia is currently paying their most attention to the side-channel ones. However, most of the existing side-channel countermeasures need fabricated golden chips that are difficult to obtain practically. In this article, we propose a novel strategy for HT detection using the target chip's quiescent thermal maps and its active area (AA) shape from the GDS II file. The AA shape cannot expose the design information of the target chip and serves as the golden reference, which means that our countermeasure does not need fabricated golden chips anymore. In addition, this countermeasure cannot be influenced by process variation (PV) from the perspective of our detection mechanism. The results of the experiment on our designed YinHeFeiTeng-digital signal processor (YHFT-DSP) indicate that our countermeasure can effectively detect trojans with a very small scale.

This paper proposed an advanced round modification fault analysis (RMFA) at the theoretical level on AEGIS-128, which is one of seven finalists in CAESAR competition. First, we clarify our assumptions and simplifications on the attack model, focusing on the encryption security. Then, we emphasize the difficulty of applying vanilla RMFA to AEGIS-128 in the practical case. Finally we demonstrate our advanced fault analysis on AEGIS-128 using machine-solver based algebraic techniques. Our enhancement can be used to conquer the practical scenario which is difficult for vanilla RMFA. Simulation results show that when the fault is injected to the initialization phase and the number of rounds is reduced to one, two samples of injections can extract the whole 128 key bits within less than two hours. This work can also be extended to other versions such as AEGIS-256.

Hardware Trojan (HT) is increasingly becoming a serious problem in the information security field. Compared to other countermeasures, thermal maps based detection can mitigate process variation (PV) and have a higher accuracy. However, HT cannot be differentiated from the others directly from the original thermal maps. Therefore, in this study, the authors first propose a general HT detection framework based on difference temperature matrix, and introduce the PV mitigation mechanism. Then, they demonstrate how principal component analysis can implement spatial projection transformation and expose HT signal. Finally, they introduce their experimental setup and design, and then validate their countermeasure with Xilinx field programmable gate arrays which are configured with the pure AES circuit and the infected AES circuits. The power proportions (PPs) of HTs in the different infected AES circuits are various. The experimental results indicate that their proposed countermeasure can clearly detect HT with 0.14% small PP.

A multimodal gesture recognition method is proposed based on Choquet integral by fusing information from camera and 3D accelerometer data. By calculating the optimal fuzzy measures for the camera recognition module and the accelerometer recognition module, the proposal obtains enough recognition rate 92.7% in average for 8 types of gestures by improving the recognition rate approximate 20% compared to that of each module. The proposed method aims to realize the casual communication from humans to robots by integrating nonverbal gesture messages and verbal messages.

A fuzzy logic based multi-modal gesture recognition method is proposed, where both camera images and hand motion data (given by a 3D acceleration sensor put on human wrists) are used to notify the emotion of humans to robots in real time. To demonstrate the validity, it is applied to a part of the home party scenario enjoyed by five eye robots and four human participants, where 8 types of human emotional-gestures are successfully recognized by robots. The proposed method aims to realize the casual communication between robots and humans in the mascot robot system that has been developed by authors' group.