IMMAESA

2021 ◽  
Vol 15 (1) ◽  
pp. 65-98
Author(s):  
Mhamed Zineddine
Keyword(s):  
Nuclear Power ◽  
Optimal Solution ◽  
Bat Algorithm ◽  
Cyber Attacks ◽  
Plant Design ◽  
Industrial Control Systems ◽  
Novel Approach ◽  
Commercial Off The Shelf ◽  
Ict Security ◽  
The Impact

The rise of digitization in industrial control systems using commercial off-the-shelf software has encouraged the use of existing IT security solutions. The aim of this study is to prevent intrusion detection and prevention systems' actions from affecting the normal functions of sensitive ICSs. A novel approach called IMMAESA based on a heuristic algorithm is proposed to evaluate the impact of IDPSs' actions when mitigating cyber-attacks. The crux of this novel approach is the IDPS does not react until it assesses the impact of its actions. The bat-algorithm is used to find an optimal solution that preserves the reliability of the system. IMMAESA method is simulated on a known nuclear power plant design, the APR1400. Results show that the proposed method lets the IDPS effectively makes tradeoffs before execution, thus, avoid any undesirable effects. The IDPS selects a set of actions (severity ~ 0,750 and reliability ~ 0,767) with minor consequences. Thus, the proposed method would be a major contribution to the ICT security field.

Towards Protecting Critical Infrastructures

2015 ◽  
pp. 121-165 ◽  
Author(s):  
Filipe Caldeira ◽  
Tiago Cruz ◽  
Paulo Simões ◽  
Edmundo Monteiro
Keyword(s):  
Power Distribution ◽  
Prediction Models ◽  
Critical Infrastructures ◽  
Industrial Control ◽  
Industrial Control Systems ◽  
Cascading Effects ◽  
Degree Of Confidence ◽  
Ict Security ◽  
Real Time Information ◽  
The Impact

Critical Infrastructures (CIs) such as power distribution are referred to as “Critical” as, in case of failure, the impact on society and economy can be enormous. CIs are exposed to a growing number of threats. ICT security plays a major role in CI protection and risk prevention for single and interconnected CIs were cascading effects might occur. This chapter addresses CI Protection discussing MICIE Project main results, along with the mechanisms that manage the degree of confidence assigned to risk alerts allowing improving the resilience of CIs when faced with inaccurate/inconsistent alerts. The CockpitCI project is also presented, aiming to improve the resilience and dependability of CIs through automatic detection of cyber-threats and the sharing of real-time information about attacks among CIs. CockpitCI addresses one MICIE's shortcoming by adding SCADA-oriented security detection capabilities, providing input for risk prediction models and assessment of the operational status of the Industrial Control Systems.

Computationally Efficient Combined Plant Design and Controller Optimization Using a Coupling Measure

2012 ◽  
Vol 134 (7) ◽  
Author(s):  
Rakesh Patil ◽  
Zoran Filipi ◽  
Hosam Fathy
Keyword(s):  
Optimal Control ◽  
Computational Cost ◽  
Systems Design ◽  
Plant Design ◽  
Coupling Term ◽  
Control Optimization ◽  
Novel Approach ◽  
Design Variables ◽  
The Impact ◽  
Plant Control

This paper presents a novel approach to the optimization of a dynamic systems design and control. Traditionally, these problems have been solved either sequentially or in a combined manner. We propose a novel approach that uses a previously derived coupling measure to quantify the impact of plant design variables on optimal control cost. This proposed approach has two key advantages. First, because the coupling term quantifies the gradient of the control optimization objective with respect to plant design variables, the approach ensures combined plant/control optimality. Second, because the coupling term equals the integral of optimal control co-states multiplied by static gradient terms that can be computed a priori, the proposed approach is computationally attractive. We illustrate this approach using an example cantilever beam structural design and vibration control problem. The results show significant computational cost improvements compared to traditional combined plant/control optimization. This reduction in computational cost becomes more pronounced as the number of plant design variables increases.

A novel approach for EMHD Williamson nanofluid over nonlinear sheet with double stratification and Ohmic dissipation

2021 ◽  
pp. 095440892110596
Author(s):  
Muhammad Bilal ◽  
Muhammad Ramzan ◽  
Yasir Mehmood ◽  
Tanveer Sajid ◽  
Sajid Shah ◽  
...  
Keyword(s):  
Differential Equations ◽  
Variable Viscosity ◽  
Optimal Solution ◽  
Lewis Number ◽  
Double Stratification ◽  
Ohmic Dissipation ◽  
Novel Approach ◽  
Homotopy Analysis ◽  
Higher Temperature ◽  
The Impact

The current article highlights the non-Newtonian Williamson nanofluid with electro-magnetohydrodynamic (EMHD) flow over a nonlinear expanding sheet. Thermal and solutal stratification effects are considered due to the higher temperature difference and the impact of variable viscosity along with Ohmic dissipation is also incorporated. Transformation is applied for the conversion of physical partial differential equations (PDEs) into non-dimensional higher order nonlinear ordinary differential equations (ODEs). A well-known analytical approach known as the homotopy analysis method (HAM) is effectively applied to solve the differential equations. Different non-dimensional emerging parameters such as Weissenberg and Hartman number, Brownian motion and stratification parameters, stretching index, viscosity parameter, and Lewis number are used to check their impacts on velocity, concentration, and temperature profiles. To acquire the optimal solution through HAM, [Formula: see text] -curves are drawn. In the tabulated form, the numerical values for the non-dimensional Nusselt number and skin friction are arranged.

Probability of the Loss of Offsite Power and Damage to Road Network due to a Rare Event

2012 ◽  
Author(s):  
Jack Cavaluzzi ◽  
Chase Gilmore ◽  
Bilal Khan ◽  
Minh Hong Tran
Keyword(s):  
Initial Data ◽  
Nuclear Power ◽  
Critical Infrastructure ◽  
Rare Event ◽  
Road Networks ◽  
Event Analysis ◽  
Plant Design ◽  
Analysis Model ◽  
The Road ◽  
The Impact

The main goal of the project was to better understand the impact to a nuclear power plant due to the unavailability of critical infrastructure. We evaluated the use of rare event analysis to establish rare event occurrences in the vicinity of the plant. For the purpose of this report, rare events were considered extreme scenarios of natural disasters. The initial data was acquired by viewing STP FSARs and topographical maps of the region. The two specific factors that were extracted by analyzing the initial data of the plant design and location were the road networks and the electrical grid system. These two variables were then analyzed in light of the rare event analysis model that was used as a building block for this project. The rare event analysis also provided information regarding the types of data and distributions that were likely to be seen as a result. For the road networks, the road layout around the plant was mapped and the relevant data was used to consider the possible routes to the plants in case of a rare event. Data regarding LOOP Events were gathered mainly from NRC Documents and Institutional Sources. These data were used to analyze how many events occurred per year and the downtime associated with the rare event.

Cyber attacks threaten South Korean nuclear safety

2015 ◽  
Keyword(s):  
Cyber Security ◽  
Nuclear Power ◽  
The United States ◽  
Public Perceptions ◽  
Cyber Attacks ◽  
Power Sector ◽  
South Korean Government ◽  
Content Type ◽  
South Korean ◽  
The Impact

Subject Cyber security in South Korea's civil nuclear power sector. Significance Korea Hydro & Nuclear Power (KHNP) became the victim of sustained cyber attacks beginning in early December, and admitted on December 30 that the intrusions were still underway. President Park Geun-hye on December 23 called the attacks a grave matter for national security. KHNP and the South Korean government now face strong pressure to close down the cyber attacks, bring the perpetrators to justice and offer a public accounting of how the breaches could have occurred. Impacts North Korea has not been blamed, but will feature in policy discussion nevertheless. That the attacks happened so soon after those on Sony Pictures is a coincidence, but will magnify the impact. The attacks will feed public perceptions that nuclear power is dangerous, emboldening anti-nuclear activists. The company's and government's responses will feed perceptions that lax regulation and lack of transparency are pervasive in South Korea. The United States, China, Japan and some EU countries will become more directly involved in Korean cyber issues.

scholarly journals Detecting and Handling Cyber-Attacks in Model Predictive Control of Chemical Processes

Mathematics ◽  
2018 ◽  
Vol 6 (10) ◽  
pp. 173 ◽  
Author(s):  
Zhe Wu ◽  
Fahad Albalawi ◽  
Junfeng Zhang ◽  
Zhihao Zhang ◽  
Helen Durand ◽  
...  
Keyword(s):  
Control Systems ◽  
Predictive Control ◽  
Chemical Processes ◽  
Cyber Attacks ◽  
Safe Operation ◽  
Industrial Control ◽  
Industrial Control Systems ◽  
Predictive Controller ◽  
Communication Control ◽  
The Impact

Since industrial control systems are usually integrated with numerous physical devices, the security of control systems plays an important role in safe operation of industrial chemical processes. However, due to the use of a large number of control actuators and measurement sensors and the increasing use of wireless communication, control systems are becoming increasingly vulnerable to cyber-attacks, which may spread rapidly and may cause severe industrial incidents. To mitigate the impact of cyber-attacks in chemical processes, this work integrates a neural network (NN)-based detection method and a Lyapunov-based model predictive controller for a class of nonlinear systems. A chemical process example is used to illustrate the application of the proposed NN-based detection and LMPC methods to handle cyber-attacks.

scholarly journals Empirical Stochastic Model of Multi-GNSS Measurements

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4566
Author(s):  
Dominik Prochniewicz ◽  
Kinga Wezka ◽  
Joanna Kozuchowska
Keyword(s):  
Stochastic Model ◽  
Density Ratio ◽  
Functional Model ◽  
Optimal Solution ◽  
Global Navigation Satellite Systems ◽  
Unknown Parameters ◽  
Short Baseline ◽  
Stochastic Parameters ◽  
Dependent Model ◽  
The Impact

The stochastic model, together with the functional model, form the mathematical model of observation that enables the estimation of the unknown parameters. In Global Navigation Satellite Systems (GNSS), the stochastic model is an especially important element as it affects not only the accuracy of the positioning model solution, but also the reliability of the carrier-phase ambiguity resolution (AR). In this paper, we study in detail the stochastic modeling problem for Multi-GNSS positioning models, for which the standard approach used so far was to adopt stochastic parameters from the Global Positioning System (GPS). The aim of this work is to develop an individual, empirical stochastic model for each signal and each satellite block for GPS, GLONASS, Galileo and BeiDou systems. The realistic stochastic model is created in the form of a fully populated variance-covariance (VC) matrix that takes into account, in addition to the Carrier-to-Noise density Ratio (C/N0)-dependent variance function, also the cross- and time-correlations between the observations. The weekly measurements from a zero-length and very short baseline are utilized to derive stochastic parameters. The impact on the AR and solution accuracy is analyzed for different positioning scenarios using the modified Kalman Filter. Comparing the positioning results obtained for the created model with respect to the results for the standard elevation-dependent model allows to conclude that the individual empirical stochastic model increases the accuracy of positioning solution and the efficiency of AR. The optimal solution is achieved for four-system Multi-GNSS solution using fully populated empirical model individual for satellite blocks, which provides a 2% increase in the effectiveness of the AR (up to 100%), an increase in the number of solutions with errors below 5 mm by 37% and a reduction in the maximum error by 6 mm compared to the Multi-GNSS solution using the elevation-dependent model with neglected measurements correlations.

scholarly journals Network Attack Path Selection and Evaluation Based on Q-Learning

2020 ◽  
Vol 11 (1) ◽  
pp. 285
Author(s):  
Runze Wu ◽  
Jinxin Gong ◽  
Weiyue Tong ◽  
Bing Fan
Keyword(s):  
Distribution System ◽  
Path Selection ◽  
Cyber Attacks ◽  
Power Distribution System ◽  
Q Learning ◽  
Attack Model ◽  
Cross Domain ◽  
Time Operation ◽  
Attack Path ◽  
The Impact

As the coupling relationship between information systems and physical power grids is getting closer, various types of cyber attacks have increased the operational risks of a power cyber-physical System (CPS). In order to effectively evaluate this risk, this paper proposed a method of cross-domain propagation analysis of a power CPS risk based on reinforcement learning. First, the Fuzzy Petri Net (FPN) was used to establish an attack model, and Q-Learning was improved through FPN. The attack gain was defined from the attacker’s point of view to obtain the best attack path. On this basis, a quantitative indicator of information-physical cross-domain spreading risk was put forward to analyze the impact of cyber attacks on the real-time operation of the power grid. Finally, the simulation based on Institute of Electrical and Electronics Engineers (IEEE) 14 power distribution system verifies the effectiveness of the proposed risk assessment method.

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