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Abstract: Embedded systems are vulnerable to buffer overflow attacks. In this paper, we propose a hardware memory monitor module that aims to detect buffer overflow attacks by analyzing the security of an embedded processor at the instruction level. The functionality of the memory monitor module does not rely on the source code and can perform security check through dynamic methods. Compared with several existing countermeasures that protect only part of the program’s data space, our proposed memory monitor module can protect the program’s entire data space. The proposed memory monitor module has negligible performance overhead because it runs in parallel with the embedded processor. As demonstrated in an FPGA (Field Programmable Gate Array) based prototype, the experimental results show that our memory monitor module can effectively resist several types of buffer overflow attacks with approximately a 15% hardware cost overhead and only a 0.1% performance penalty. [Copyright &y& Elsevier]

Abstract: This paper develops a novel dynamic framed slotted ALOHA (DFSA) algorithm based on Bayesian estimation to improve the throughput of the radio frequency identification (RFID) system. At first, four types of anti-collision algorithms for tag identification are analyzed. Then, the proposed DFSA based on Bayesian estimation is deduced and introduced. Compared with the conventional DFSA algorithms, this algorithm takes advantage of the evidence in previous frames as the a priori information of the current frame which can end up with more precise estimation of tag number and rational frame length adjustment. Finally, the common simulation tool from Matlab is used to demonstrate the effectiveness of the proposed new algorithm for the average throughput improvements of the RFID system. [Copyright &y& Elsevier]