In recent years, deep learning methods have become prevalent in the field of side-channel analysis (SCA), leading to a decline in research on nonprofiled attacks and their preprocessing techniques. However, while deep-learning-based SCA methods can reduce the requirements for the quality of leakage signals, they do not fully resolve the need for preprocessing in SCA. Additionally, there is a lack of universal, nontrained preprocessing methods for side-channel leakage under various types of interference. In this article, a new method for preprocessing side channel leakage using synchrosqueezing wavelet transform and ridge energy extraction is proposed to deal with complex scenarios. This method involves two steps: first, applying synchrosqueezing theory to concentrate signal energy in the wavelet domain, and second, utilizing a dynamic path optimization algorithm to locate and extract ridge energy for subsequent attacks. Our proposed solution extracts key information features from the traces, effectively addressing trace distortion caused by varying levels of noise and random disturbances. We validate the effectiveness of our analysis and solution through extensive experiments on four public databases and two self-collected datasets containing power and electromagnetic leakage (EM) from both hardware and software encryption implementations. We compare our experimental results from four indicators: 1) success rate; 2) guessing entropy; 3) signal to noise ratio; and 4) normalized interclass varianc. Besides, we demonstrate the advantages of our method by comparing Measurements to Disclosure and on public datasets. Our method demonstrates significant potential for preprocessing traces in nonprofiled SCA.

We present an automatic hexahedralization tool, based on a systematic treatment that removes some of the singularities that would lead to degenerate volumetric parameterization. Such singularities could be abundant in automatically generated frame fields guiding the interior and boundary layouts of the hexahedra in an all hexahedral mesh. We first give the mathematical definitions of the inadmissible singularities prevalent in frame fields, including newly introduced surface singularity types. We then give a practical framework for adjusting singularity graphs by automatically modifying the rotational transition of frames between charts (cells of a tetrahedral mesh for the volume) to resolve the issues detected in the internal and boundary singularity graph. After applying an additional re-smoothing of the frame field with the modified transition conditions, we cut the volume into a topologically trivial domain, with the original topology encoded by the self-intersections of the boundary of the domain, and solve a mixed integer problem on this domain for a global parameterization. Finally, a properly connected hexahedral mesh is constructed from the integer isosurfaces of (u,v,w) in the parameterization. We demonstrate the applicability of the method on complex shapes, and discuss its limitations.

One of the important problems in the design of the Earth-Moon low energy transfer is to find the patch point of the unstable manifold of the Lyapunov orbit around Sun-Earth L2 and the stable manifold of the Lyapunov orbit around Earth-Moon L2. The traditional method is “trial and error”. It is extremely sensitive with the changes in the initial condition. In this paper, evolutionary algorithms are used to optimize the initial condition. An improved differential evolution algorithm is proposed to solve this problem. We incorporate the uniform design technology and the self-adaptive parameter control method into standard differential evolution to accelerate its convergence speed and improve the stability. The improvement algorithm is compared with three evolutionary algorithms. The experiment results indicate that our approach is able to find the better, or at least comparably, in terms of the quality and stability of the final solutions. Moreover, it proves the application of evolutionary algorithms in the Earth-Moon low energy transfer optimization problem is effective.

The fine-grained access control (FGAC) is important to Web applications. However, it can be circumvented by indirect access such as inferring sensitive data from insensitive data. In the previous FGAC studies, the inference information leakage is not well controlled. In addition, the soundness property, which requires that the results of a query under the FGAC should be the subset of the results of the query without the FGAC over the same database states, can not be held for all SQL statements. Moreover, without soundness information leakage would occur in databases in some situations. In this paper, we divide the approaches which implement FGAC with query modification into two types: the first, the FGAC policy is executed over the results obtained from the query issued by a user; the second, the query issued by a user is executed over the results obtained from the FGAC policy. Then we introduce three types of information leakages of FGAC, which is implemented by using the first approach, and analyze why the existing approaches can not hold soundness for all SQL statements. A novel approach is proposed to control the information leakages and satisfy the soundness property for all SQL statements. Then we implement our approach in DM DBMS with query modification and analyze the test results.

The use of association patterns for text categorization has attracted great interest and a variety of useful methods have been developed. However, the key characteristics of pattern-based text categorization remain unclear. Indeed, there are still no concrete answers for the following two questions: First, what kind of association patterns are the best candidate for pattern-based text categorization? Second, what is the most desirable way to use patterns for text categorization? In this paper, we focus on answering the above two questions. Specifically, we show that hyperclique patterns are more desirable than frequent patterns for text categorization. Along this line, we develop an algorithm for text categorization using hyperclique patterns. The experimental results show that our method provides better performance than state-of-the-art methods in terms of both computational performance and classification accuracy.