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2021-02-08
Li, W., Li, L..  2009.  A Novel Approach for Vehicle-logo Location Based on Edge Detection and Morphological Filter. 2009 Second International Symposium on Electronic Commerce and Security. 1:343—345.

Vehicle-logo location is a crucial step in vehicle-logo recognition system. In this paper, a novel approach of the vehicle-logo location based on edge detection and morphological filter is proposed. Firstly, the approximate location of the vehicle-logo region is determined by the prior knowledge about the position of the vehicle-logo; Secondly, the texture measure is defined to recognize the texture of the vehicle-logo background; Then, vertical edge detection is executed for the vehicle-logo background with the horizontal texture and horizontal edge detection is implemented for the vehicle-logo background with the vertical texture; Finally, position of the vehicle-logo is located accurately by mathematical morphology filter. Experimental results show the proposed method is effective.

2017-04-20
Gomes, T., Salgado, F., Pinto, S., Cabral, J., Tavares, A..  2016.  Towards an FPGA-based network layer filter for the Internet of Things edge devices. 2016 IEEE 21st International Conference on Emerging Technologies and Factory Automation (ETFA). :1–4.

In the near future, billions of new smart devices will connect the big network of the Internet of Things, playing an important key role in our daily life. Allowing IPv6 on the low-power resource constrained devices will lead research to focus on novel approaches that aim to improve the efficiency, security and performance of the 6LoWPAN adaptation layer. This work in progress paper proposes a hardware-based Network Packet Filtering (NPF) and an IPv6 Link-local address calculator which is able to filter the received IPv6 packets, offering nearly 18% overhead reduction. The goal is to obtain a System-on-Chip implementation that can be deployed in future IEEE 802.15.4 radio modules.

2014-09-26
Schwartz, E.J., Avgerinos, T., Brumley, D..  2010.  All You Ever Wanted to Know about Dynamic Taint Analysis and Forward Symbolic Execution (but Might Have Been Afraid to Ask). Security and Privacy (SP), 2010 IEEE Symposium on. :317-331.

Dynamic taint analysis and forward symbolic execution are quickly becoming staple techniques in security analyses. Example applications of dynamic taint analysis and forward symbolic execution include malware analysis, input filter generation, test case generation, and vulnerability discovery. Despite the widespread usage of these two techniques, there has been little effort to formally define the algorithms and summarize the critical issues that arise when these techniques are used in typical security contexts. The contributions of this paper are two-fold. First, we precisely describe the algorithms for dynamic taint analysis and forward symbolic execution as extensions to the run-time semantics of a general language. Second, we highlight important implementation choices, common pitfalls, and considerations when using these techniques in a security context.