RESUMEN
The growing need for wearable electronics and self-powered electronic devices has driven the successful development of self-powered two-dimensional (2D) photodetectors using the photovoltaic effect of Schottky and p-n junctions. However, there is an urgent need to develop multifunctional photodetectors capable of harvesting energy from different sources to overcome their limitations in efficiency and cost. While the pyro-phototronic effect has been shown to effectively influence optoelectronic processes in heterojunctions, the number of reported two-dimensional heterojunctions exhibiting interfacial pyroelectricity is still limited, and the responsivity and detectivity based on such heterojunctions tend to be low. In this study, a photodetector based on an Au/WSe2/Ta2NiS5/Au heterojunction was designed and fabricated. By harnessing the interfacial pyro-phototronic effect arising from the built-in electric fields at the Au/WSe2 Schottky junction and WSe2/Ta2NiS5 heterojunction, the photodetector exhibits a broadband response range of 405-1064 nm, with approximately 12 times enhancement in output current compared to solely relying on the photovoltaic effect. Under 660 nm light irradiation, the self-powered photodetector exhibits a responsivity of 121 mA/W, an external quantum efficiency of 22.64%, and a specific detectivity of 2 × 1012 Jones. Notably, its pyroelectric coefficient exceeds 8 × 103 µC·m-2·K-1. These findings pave the way for effectively detecting weak light and temperature variation while presenting a new strategy for developing high-performance photodetectors utilizing the interfacial pyro-phototronic effect.
RESUMEN
The traces used in side-channel analysis are essential to breaking the key of encryption and the signal quality greatly affects the correct rate of key guessing. Therefore, the preprocessing of side-channel traces plays an important role in side-channel analysis. The process of side-channel leakage signal acquisition is usually affected by internal circuit noise, external environmental noise, and other factors, so the collected signal is often mixed with strong noise. In order to extract the feature information of side-channel signals from very low signal-to-noise ratio traces, a hybrid threshold denoising framework using singular value decomposition is proposed for side-channel analysis preprocessing. This framework is based on singular value decomposition and introduces low-rank matrix approximation theory to improve the rank selection methods of singular value decomposition. This paper combines the hard threshold method of truncated singular value decomposition with the soft threshold method of singular value shrinkage damping and proposes a hybrid threshold denoising framework using singular value decomposition for the data preprocessing step of side-channel analysis as a general preprocessing method for non-profiled side-channel analysis. The data used in the experimental evaluation are from the raw traces of the public database of DPA contest V2 and AES_HD. The success rate curve of non-profiled side-channel analysis further confirms the effectiveness of the proposed framework. Moreover, the signal-to-noise ratio of traces is significantly improved after preprocessing, and the correlation with the correct key is also significantly enhanced. Experimental results on DPA v2 and AES_HD show that the proposed noise reduction framework can be effectively applied to the side-channel analysis preprocessing step, and can successfully improve the signal-to-noise ratio of the traces and the attack efficiency.
RESUMEN
Algebraic persistent fault analysis (APFA), which combines algebraic analysis with persistent fault attacks, brings new challenges to the security of lightweight block ciphers and has received widespread attention since its introduction. Threshold Implementation (TI) is one of the most widely used countermeasures for side channel attacks. Inspired by this method, the SKINNY block cipher adopts the S_box decomposition to reduce the number of variables in the set of algebraic equations and the number of Conjunctive Normal Form (CNF) equations in this paper, thus speeding up the algebraic persistent fault analysis and reducing the number of fault ciphertexts. In our study, we firstly establish algebraic equations for full-round faulty encryption, and then analyze the relationship between the number of fault ciphertexts required and the solving time in different scenarios (decomposed S_boxes and original S_box). By comparing the two sets of experimental results, the success rate and the efficiency of the attack are greatly improved by using S_box decomposition. In this paper, We can recover the master key in a minimum of 2000s using 11 pairs of plaintext and fault ciphertext, while the key recovery cannot be done in effective time using the original S_box expression equations. At the same time, we apply S_box decomposition to another kind of algebraic persistent fault analysis, and the experimental results show that using S_box decomposition can effectively reduce the solving time and solving success rate under the same conditions.