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Whitebox fuzzing is a novel form of security testing based on dynamic symbolic execution and constraint solving. Over the last couple of years, whitebox fuzzers have found many new security vulnerabilities (buffer overflows) in Windows and Linux applicatio ...
Whitebox fuzzing is a novel form of security testing based on runtime symbolic execution and constraint solving. Over the last couple of years, whitebox fuzzers have found dozens of new security vulnerabilities (buffer overflows) in Windows and Linux appli ...
In this paper, we investigate the benefits of instruction set extensions (ISEs) on a 16-bit microcontroller architecture for software implementations of cryptographic hash functions, using the example of the five SHA-3 final round candidates. We identify t ...
Multi-camera systems have attracted attention in recent years due to rapidly dropping cost of digital cameras. This has enabled wide variety of new research topics and applications for Multi View Imaging (MVI) systems. Virtual view synthesis, high performa ...
Recent research suggests that DSM clusters can benefit from parallel coherence controllers. Parallel controllers requires address partitioning and synchronization to avoid handling multiple coherence events for the same memory address simultaneously. This ...
With the omnipresence of embedded processing in all forms of electronics today, there is a strong trend towards wireless, battery-powered, portable embedded systems which have to operate under stringent energy constraints. Consequently, low power consumpti ...
Deep neural networks (DNN) have revolutionized the field of machine learning by providing unprecedented human-like performance in solving many real-world problems such as image or speech recognition. Training of large DNNs, however, is a computationally in ...
To be able to calculate the performances of a hybrid stepping motor or to design it in a short time, it is essential to apply an efficient model, accepting a slight loss of precision. Using software based on finite elements and executing calculations are d ...
Deep neural networks (DNNs) have revolutionized the field of artificial intelligence and have achieved unprecedented success in cognitive tasks such as image and speech recognition. Training of large DNNs, however, is computationally intensive and this has ...
