Scan design is a widely used design-for-testability (DFT) technique that improves the controllability and observability of integrated circuits (ICs) resulting in the facilitation of the testing. However, it can also b...
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ISBN:
(纸本)9789881404732
Scan design is a widely used design-for-testability (DFT) technique that improves the controllability and observability of integrated circuits (ICs) resulting in the facilitation of the testing. However, it can also be used to access secret information of crypto chips, and thus threaten dramatically the security of the cipher keys. In this paper, we propose a secure scan DFT architecture to thwart scan-based side-channel attacks. This architecture provides the scan chain reset mechanism, and thus can prevent these attacks based on mode switching. Meanwhile, the secret key is isolated from scan chains of an advanced encryption standard (AES) design in the test mode. Therefore, it can also halt the test-mode-only scan attacks. The proposed secure scan DFT technique ensures the security without compromising the testability of original chip. Most important of all, the secure scan test is implemented with extremely low hardware overhead.
In this paper, a Connected Dominating Set (CDS) construction algorithm CSCDS (Connected Subset based CDS) is proposed, which is based on the connected subset concept. The CSCDS contains two main stages, which are domi...
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Since the majority of the available steganographic schemes in OOXML format documents suffered the disadvantages of unsatisfactory anti-detection capability and security level, a characteristic-preserving steganographi...
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For robust face recognition tasks, we particularly focus on the ubiquitous scenarios where both training and testing images are corrupted due to occlusions. Previous low-rank based methods stacked each error image int...
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For robust face recognition tasks, we particularly focus on the ubiquitous scenarios where both training and testing images are corrupted due to occlusions. Previous low-rank based methods stacked each error image into a vector and then used L 1 or L 2 norm to measure the error matrix. However, in the stacking step, the structure information of the error image can be lost. Depart from the previous methods, in this paper, we propose a novel method by exploiting the low-rankness of both the data representation and each occlusion-induced error image simultaneously, by which the global structure of data together with the error images can be well captured. In order to learn more discriminative low-rank representations, we formulate our objective such that the learned representations are optimal for classification with the available supervised information and close to an ideal-code regularization term. With strong structure information preserving and discrimination capabilities, the learned robust and discriminative low-rank representation (RDLRR) works very well on face recognition problems, especially with face images corrupted by continuous occlusions. Together with a simple linear classifier, the proposed approach is shown to outperform several other state-of-the-art face recognition methods on databases with a variety of face variations.
In this paper, a Price learning based Load Distribution Strategy (PLDS) is proposed at first. In PLDS model, Smart Power Service, Utility Company and History Load Curves are included, and by considering both the avera...
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In China, the expressway isn’t free. When a vehicle exits, the exit toll station needs to calculate the toll according to the vehicle trajectory obtained by sending a trajectory query task to the trajectory center re...
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In smart grid, privacy implications to individuals and their family is an important issue, due to the fine-grained usage data collection. Wireless communications are considered by many utility companies to obtain info...
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