Robustness of the European power grids under intentional attack

The power grid defines one of the most important technological networks of our times and sustains our complex society. It has evolved for more than a century into an extremely huge and seemingly robust and well understood system. But it becomes extremely fragile as well, when unexpected, usually minimal, failures turn into unknown dynamical behaviours leading, for example, to sudden and massive blackouts. Here we explore the fragility of the European power grid under the effect of selective node removal. A mean field analysis of fragility against attacks is presented together with the observed patterns. Deviations from the theoretical conditions for network percolation (and fragmentation) under attacks are analysed and correlated with non topological reliability measures.Comment: 7 pages, 4 figure

Chaotic multi-objective optimization based design of fractional order PI{\lambda}D{\mu} controller in AVR system

In this paper, a fractional order (FO) PI{\lambda}D\mu controller is designed to take care of various contradictory objective functions for an Automatic Voltage Regulator (AVR) system. An improved evolutionary Non-dominated Sorting Genetic Algorithm II (NSGA II), which is augmented with a chaotic map for greater effectiveness, is used for the multi-objective optimization problem. The Pareto fronts showing the trade-off between different design criteria are obtained for the PI{\lambda}D\mu and PID controller. A comparative analysis is done with respect to the standard PID controller to demonstrate the merits and demerits of the fractional order PI{\lambda}D\mu controller.Comment: 30 pages, 14 figure

Reducing Cascading Failure Risk by Increasing Infrastructure Network Interdependency

Increased coupling between critical infrastructure networks, such as power and communication systems, will have important implications for the reliability and security of these systems. To understand the effects of power-communication coupling, several have studied interdependent network models and reported that increased coupling can increase system vulnerability. However, these results come from models that have substantially different mechanisms of cascading, relative to those found in actual power and communication networks. This paper reports on two sets of experiments that compare the network vulnerability implications resulting from simple topological models and models that more accurately capture the dynamics of cascading in power systems. First, we compare a simple model of topological contagion to a model of cascading in power systems and find that the power grid shows a much higher level of vulnerability, relative to the contagion model. Second, we compare a model of topological cascades in coupled networks to three different physics-based models of power grids coupled to communication networks. Again, the more accurate models suggest very different conclusions. In all but the most extreme case, the physics-based power grid models indicate that increased power-communication coupling decreases vulnerability. This is opposite from what one would conclude from the coupled topological model, in which zero coupling is optimal. Finally, an extreme case in which communication failures immediately cause grid failures, suggests that if systems are poorly designed, increased coupling can be harmful. Together these results suggest design strategies for reducing the risk of cascades in interdependent infrastructure systems

Topological Performance Measures as Surrogates for Physical Flow Models for Risk and Vulnerability Analysis for Electric Power Systems

Critical infrastructure systems must be both robust and resilient in order to ensure the functioning of society. To improve the performance of such systems, we often use risk and vulnerability analysis to find and address system weaknesses. A critical component of such analyses is the ability to accurately determine the negative consequences of various types of failures in the system. Numerous mathematical and simulation models exist which can be used to this end. However, there are relatively few studies comparing the implications of using different modeling approaches in the context of comprehensive risk analysis of critical infrastructures. Thus in this paper, we suggest a classification of these models, which span from simple topologically-oriented models to advanced physical flow-based models. Here, we focus on electric power systems and present a study aimed at understanding the tradeoffs between simplicity and fidelity in models used in the context of risk analysis. Specifically, the purpose of this paper is to compare performances measures achieved with a spectrum of approaches typically used for risk and vulnerability analysis of electric power systems and evaluate if more simplified topological measures can be combined using statistical methods to be used as a surrogate for physical flow models. The results of our work provide guidance as to appropriate models or combination of models to use when analyzing large-scale critical infrastructure systems, where simulation times quickly become insurmountable when using more advanced models, severely limiting the extent of analyses that can be performed

Suitability of chaotic iterations schemes using XORshift for security applications

International audienceThe design and engineering of original cryptographic solutions is a major concern to provide secure information systems. In a previous study, we have described a generator based on chaotic iterations, which uses the well-known XORshift generator. By doing so, we have improved the statistical performances of XORshift and make it behave chaotically, as defined by Devaney. The speed and security of this former generator have been improved in a second study, to make its usage more relevant in the Internet security context. In this paper, these contributions are summarized and a new version of the generator is introduced. It is based on a new Lookup Table implying a large improvement of speed. A comparison and a security analysis between the XORshift and these three versions of our generator are proposed, and various new statistical results are given. Finally, an application in the information hiding framework is presented, to give an illustrative example of the use of such a generator in the Internet security field

COMPARATIVE STUDY OF CHAOTIC SYSTEM FOR ENCRYPTION

Chaotic systems leverage their inherent complexity and unpredictability to generate cryptographic keys, enhancing the security of encryption algorithms. This paper presents a comparative study of 13 chaotic keymaps. Several evaluation metrics, including keyspace size, dimensions, entropy, statistical properties, sensitivity to initial conditions, security level, practical implementation, and adaptability to cloud computing, are utilized to compare the keymaps. Keymaps such as Logistic, Lorenz, and Henon demonstrate robustness and high-security levels, offering large key space sizes and resistance to attacks. Their efficient implementation in a cloud computing environment further validates their suitability for real-world encryption scenarios. The context of the study focuses on the role of the key in encryption and provides a brief specification of each map to assess the effectiveness, security, and suitability of the popular chaotic keymaps for encryption applications. The study also discusses the security assessment of resistance to the popular cryptographic attacks: brute force, known plaintext, chosen plaintext, and side channel. The findings of this comparison reveal the Lorenz Map is the best for the cloud environment based on a specific scenario

Frequency Domain Design of Fractional Order PID Controller for AVR System Using Chaotic Multi-objective Optimization

This is the author accepted manuscript. The final version is available from Elsevier via the DOI in this record.A fractional order (FO) PID or FOPID controller is designed for an Automatic Voltage Regulator (AVR) system with the consideration of contradictory performance objectives. An improved evolutionary Non-dominated Sorting Genetic Algorithm (NSGA-II), augmented with a chaotic Henon map is used for the multi-objective optimization based design procedure. The Henon map as the random number generator outperforms the original NSGA-II algorithm and its Logistic map assisted version for obtaining a better design trade-off with an FOPID controller. The Pareto fronts showing the trade-offs between the different design objectives have also been shown for both the FOPID controller and the conventional PID controller to enunciate the relative merits and demerits of each. The design is done in frequency domain and hence stability and robustness of the design is automatically guaranteed unlike the other time domain optimization based controller design methods