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2020-03-09
Kandoussi, El Mehdi, El Mir, Iman, Hanini, Mohamed, Haqiq, Abdelkrim.  2019.  Modeling Virtual Machine Migration as a Security Mechanism by using Continuous-Time Markov Chain Model. 2019 4th World Conference on Complex Systems (WCCS). :1–6.

In Cloud Computing Environment, using only static security measures didn't mitigate the attack considerably. Hence, deployment of sophisticated methods by the attackers to understand the network topology of complex network makes the task easier. For this reason, the use of dynamic security measure as virtual machine (VM) migration increases uncertainty to locate a virtual machine in a dynamic attack surface. Although this, not all VM's migration enhances security. Indeed, the destination server to host the VM should be selected precisely in order to avoid externality and attack at the same time. In this paper, we model migration in cloud environment by using continuous Markov Chain. Then, we analyze the probability of a VM to be compromised based on the destination server parameters. Finally, we provide some numerical results to show the effectiveness of our approach in term of avoiding intrusion.

2019-05-01
Shen, W., Liu, Y., Wu, Q., Tian, Y., Liu, Y., Peng, H..  2018.  Application of Dynamic Security Technology Architecture for Advanced Directional Attacks in Power System Information Security. 2018 International Conference on Power System Technology (POWERCON). :3042–3047.

In view of the increasingly severe network security situation of power information system, this paper draws on the experience of construction of security technology system at home and abroad, with the continuous monitoring and analysis as the core, covering the closed-loop management of defense, detection, response and prediction security as the starting point, Based on the existing defense-based static security protection architecture, a dynamic security technology architecture based on detection and response is established. Compared with the traditional PDR architecture, the architecture adds security threat prediction, strengthens behavior-based detection, and further explains the concept of dynamic defense, so that it can adapt to changes in the grid IT infrastructure and business application systems. A unified security strategy can be formed to deal with more secretive and professional advanced attacks in the future. The architecture emphasizes that network security is a cyclical confrontation process. Enterprise network security thinking should change from the past “emergency response” to “continuous response”, real-time dynamic analysis of security threats, and automatically adapt to changing networks and threat environments, and Constantly optimize its own security defense mechanism, thus effectively solving the problem of the comprehensive technology transformation and upgrading of the security technology system from the traditional passive defense to the active sensing, from the simple defense to the active confrontation, and from the independent protection to the intelligence-driven. At the same time, the paper also gives the technical evolution route of the architecture, which provides a planning basis and a landing method for the continuous fulfillment of the new requirements of the security of the power information system during the 13th Five-Year Plan period.

2018-02-21
Zhou, G., Feng, Y., Bo, R., Chien, L., Zhang, X., Lang, Y., Jia, Y., Chen, Z..  2017.  GPU-Accelerated Batch-ACPF Solution for N-1 Static Security Analysis. IEEE Transactions on Smart Grid. 8:1406–1416.

Graphics processing unit (GPU) has been applied successfully in many scientific computing realms due to its superior performances on float-pointing calculation and memory bandwidth, and has great potential in power system applications. The N-1 static security analysis (SSA) appears to be a candidate application in which massive alternating current power flow (ACPF) problems need to be solved. However, when applying existing GPU-accelerated algorithms to solve N-1 SSA problem, the degree of parallelism is limited because existing researches have been devoted to accelerating the solution of a single ACPF. This paper therefore proposes a GPU-accelerated solution that creates an additional layer of parallelism among batch ACPFs and consequently achieves a much higher level of overall parallelism. First, this paper establishes two basic principles for determining well-designed GPU algorithms, through which the limitation of GPU-accelerated sequential-ACPF solution is demonstrated. Next, being the first of its kind, this paper proposes a novel GPU-accelerated batch-QR solver, which packages massive number of QR tasks to formulate a new larger-scale problem and then achieves higher level of parallelism and better coalesced memory accesses. To further improve the efficiency of solving SSA, a GPU-accelerated batch-Jacobian-Matrix generating and contingency screening is developed and carefully optimized. Lastly, the complete process of the proposed GPU-accelerated batch-ACPF solution for SSA is presented. Case studies on an 8503-bus system show dramatic computation time reduction is achieved compared with all reported existing GPU-accelerated methods. In comparison to UMFPACK-library-based single-CPU counterpart using Intel Xeon E5-2620, the proposed GPU-accelerated SSA framework using NVIDIA K20C achieves up to 57.6 times speedup. It can even achieve four times speedup when compared to one of the fastest multi-core CPU parallel computing solution using KLU library. The prop- sed batch-solving method is practically very promising and lays a critical foundation for many other power system applications that need to deal with massive subtasks, such as Monte-Carlo simulation and probabilistic power flow.

2017-11-20
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.

2017-02-27
Gonzalez-Longatt, F., Carmona-Delgado, C., Riquelme, J., Burgos, M., Rueda, J. L..  2015.  Risk-based DC security assessment for future DC-independent system operator. 2015 International Conference on Energy Economics and Environment (ICEEE). :1–8.

The use of multi-terminal HVDC to integrate wind power coming from the North Sea opens de door for a new transmission system model, the DC-Independent System Operator (DC-ISO). DC-ISO will face highly stressed and varying conditions that requires new risk assessment tools to ensure security of supply. This paper proposes a novel risk-based static security assessment methodology named risk-based DC security assessment (RB-DCSA). It combines a probabilistic approach to include uncertainties and a fuzzy inference system to quantify the systemic and individual component risk associated with operational scenarios considering uncertainties. The proposed methodology is illustrated using a multi-terminal HVDC system where the variability of wind speed at the offshore wind is included.