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Fu, Shichong, Li, Xiaoling, Zhao, Yao.  2022.  Improved Steganography Based on Referential Cover and Non-symmetric Embedding. 2022 IEEE 5th International Conference on Electronics Technology (ICET). :1202–1206.
Minimizing embedding impact model of steganography has good performance for steganalysis detection. By using effective distortion cost function and coding method, steganography under this model becomes the mainstream embedding framework recently. In this paper, to improve the anti-detection performance, a new steganography optimization model by constructing a reference cover is proposed. First, a reference cover is construed by performing a filtering operation on the cover image. Then, by minimizing the residual between the reference cover and the original cover, the optimization function is formulated considering the effect of different modification directions. With correcting the distortion cost of +1 and \_1 modification operations, the stego image obtained by the proposed method is more consistent with the natural image. Finally, by applying the proposed framework to the cost function of the well-known HILL embedding, experimental results show that the anti-detection performance of the proposed method is better than the traditional method.
ISSN: 2768-6515
Paramathma, M. K., Devaraj, D., Reddy, B. S..  2016.  Artificial neural network based static security assessment module using PMU measurements for smart grid application. 2016 International Conference on Emerging Trends in Engineering, Technology and Science (ICETETS). :1–5.

Power system security is one of the key issues in the operation of smart grid system. Evaluation of power system security is a big challenge considering all the contingencies, due to huge computational efforts involved. Phasor measurement unit plays a vital role in real time power system monitoring and control. This paper presents static security assessment scheme for large scale inter connected power system with Phasor measurement unit using Artificial Neural Network. Voltage magnitude and phase angle are used as input variables of the ANN. The optimal location of PMU under base case and critical contingency cases are determined using Genetic algorithm. The performance of the proposed optimization model was tested with standard IEEE 30 bus system incorporating zero injection buses and successful results have been obtained.

Wang, C. H..  2015.  A Modelling Framework for Managing Risk-Based Checkpoint Screening Systems with Two-Type Inspection Queues. 2015 Third International Conference on Robot, Vision and Signal Processing (RVSP). :220–223.

In this paper, we study the security and system congestion in a risk-based checkpoint screening system with two kinds of inspection queues, named as Selectee Lanes and Normal Lanes. Based on the assessed threat value, the arrival crossing the security checkpoints is classified as either a selectee or a non-selectee. The Selectee Lanes with enhanced scrutiny are used to check selectees, while Normal Lanes are used to check non-selectees. The goal of the proposed modelling framework is to minimize the system congestion under the constraints of total security and limited budget. The system congestion of the checkpoint screening system is determined through a steady-state analysis of multi-server queueing models. By solving an optimization model, we can determine the optimal threshold for differentiating the arrivals, and determine the optimal number of security devices for each type of inspection queues. The analysis conducted in this study contributes managerial insights for understanding the operation and system performance of such risk-based checkpoint screening systems.