Research on SCADA system security reinforcement method based on distributed Pareto algorithm

2021 ◽  
pp. 1-13
Author(s):  
Hua Ning ◽  
Kaijun Liu ◽  
Yuan Li
Keyword(s):  
System Security ◽  
Optimization Method ◽  
Normal Operation ◽  
Multi Objective Optimization ◽  
Tree Model ◽  
Security Vulnerabilities ◽  
Attack Tree ◽  
Multi Objective ◽  
Scada System ◽  
The Cost

As the SCADA system develops continuously, the dissemination of malicious network behaviors has brought great risk to the normal operation of enterprises, meanwhile resulting in huge economic burden to personal work and life. Therefore, the security reinforcement strategy is crucial to the field of network security management and analysis of the SCADA system. Some researchers have started to investigate on how to minimize the cost of realizing the SCADA system reinforcement strategy. However, the SCADA system administrators are facing a very challenging problem, that’s the reinforcement budget is less than the minimal input of SCADA system security reinforcement. The core of this problem lies on how to choose a subset from massive security reinforcement strategies, so as to minimize the risks from not patching all essential security vulnerabilities within the budget. Based on a deep comparative analysis of existing multi-objective optimization technologies, this paper proposes a multi-objective optimization method based on system attack tree model, and uses Pareto algorithm to solve this problem. The experimental results demonstrate that the Pareto algorithm can effectively make the multi-objective decision in security reinforcement strategy, and can solve practical issues in actual SCADA system security reinforcement practice.

scholarly journals The Method of MMC Redundancy Optimization Allocation Based on Multi-objective Optimization

2018 ◽  
Vol 173 ◽  
pp. 03075
Author(s):  
Enshu Jin ◽  
Yagu Zhang
Keyword(s):  
Optimization Method ◽  
Normal Operation ◽  
Multi Objective Optimization ◽  
Configuration Optimization ◽  
Multi Objective ◽  
Optimal Value ◽  
Optimization Function ◽  
Multi Level ◽  
Optimization Allocation ◽  
Level Converter

When the modular multi-level converter of the sub-module faults, which will cause the unbalanced system, affect the normal operation of the system, so to the MMC arm configuration redundant sub-module is necessary, if the sub-module faults, redundant sub-modules will replace the fault sub-module maintaining the normal operation of system. In this paper, we propose a reasonable and effective method for the configuration optimization of redundant sub-module based on the three indexes, namely, efficient utilization of redundant sub-module, the number of redundant sub-module and the reliability of the system MMC, considering the three factors, establishing a multi-objective optimization function of redundant configuration, By calculating the optimal value to accurately calculate the number of redundant sub-module of MMC, based on the proposed redundancy configuration optimization method, building a simulation model of MMC 5 level in PSCAD, the results verify the rationality and feasibility of the proposed optimization method.

Student Admission Assesment using Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA)

2018 ◽  
Author(s):  
Rivalri Kristianto Hondro ◽  
Mesran Mesran ◽  
Andysah Putera Utama Siahaan
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Support Systems ◽  
Selection Process ◽  
Initial Step ◽  
Optimization Method ◽  
Ratio Analysis ◽  
Multi Objective Optimization ◽  
Prospective Students ◽  
Multi Objective

Procurement selection process in the acceptance of prospective students is an initial step undertaken by private universities to attract superior students. However, sometimes this selection process is just a procedural process that is commonly done by universities without grouping prospective students from superior students into a class that is superior compared to other classes. To process the selection results can be done using the help of computer systems, known as decision support systems. To produce a better, accurate and objective decision result is used a method that can be applied in decision support systems. Multi-Objective Optimization Method by Ratio Analysis (MOORA) is one of the MADM methods that can perform calculations on the value of criteria of attributes (prospective students) that helps decision makers to produce the right decision in the form of students who enter into the category of prospective students superior.

Pareto Set as a Model for Dispatching Resources in Emergency Centres (Preprint)

2018 ◽  
Author(s):  
Ricardo Guedes ◽  
Vasco Furtado ◽  
Tarcísio Pequeno ◽  
Joel Rodrigues
Keyword(s):  
Operational Research ◽  
Real Data ◽  
Pareto Set ◽  
Multi Objective Optimization ◽  
Pareto Dominance ◽  
Four Dimensions ◽  
Multi Objective ◽  
The Best Approximation ◽  
One Year ◽  
The Cost

UNSTRUCTURED The article investigates policies for helping emergency-centre authorities for dispatching resources aimed at reducing goals such as response time, the number of unattended calls, the attending of priority calls, and the cost of displacement of vehicles. Pareto Set is shown to be the appropriated way to support the representation of policies of dispatch since it naturally fits the challenges of multi-objective optimization. By means of the concept of Pareto dominance a set with objectives may be ordered in a way that guides the dispatch of resources. Instead of manually trying to identify the best dispatching strategy, a multi-objective evolutionary algorithm coupled with an Emergency Call Simulator uncovers automatically the best approximation of the optimal Pareto Set that would be the responsible for indicating the importance of each objective and consequently the order of attendance of the calls. The scenario of validation is a big metropolis in Brazil using one-year of real data from 911 calls. Comparisons with traditional policies proposed in the literature are done as well as other innovative policies inspired from different domains as computer science and operational research. The results show that strategy of ranking the calls from a Pareto Set discovered by the evolutionary method is a good option because it has the second best (lowest) waiting time, serves almost 100% of priority calls, is the second most economical, and is the second in attendance of calls. That is to say, it is a strategy in which the four dimensions are considered without major impairment to any of them.

Multi-objective optimization of optimal capacitor allocation in radial distribution systems

2020 ◽  
Vol 21 (3) ◽  
Author(s):  
Sayed Mir Shah Danish ◽  
Mikaeel Ahmadi ◽  
Atsushi Yona ◽  
Tomonobu Senjyu ◽  
Narayanan Krishna ◽  
...  
Keyword(s):  
Radial Distribution ◽  
Distribution System ◽  
Distribution Systems ◽  
Reactive Power ◽  
Stability Index ◽  
Distribution Networks ◽  
Optimization Method ◽  
Optimal Size ◽  
Multi Objective Optimization ◽  
Multi Objective

AbstractThe optimal size and location of the compensator in the distribution system play a significant role in minimizing the energy loss and the cost of reactive power compensation. This article introduces an efficient heuristic-based approach to assign static shunt capacitors along radial distribution networks using multi-objective optimization method. A new objective function different from literature is adapted to enhance the overall system voltage stability index, minimize power loss, and to achieve maximum net yearly savings. However, the capacitor sizes are assumed as discrete known variables, which are to be placed on the buses such that it reduces the losses of the distribution system to a minimum. Load sensitive factor (LSF) has been used to predict the most effective buses as the best place for installing compensator devices. IEEE 34-bus and 118-bus test distribution systems are utilized to validate and demonstrate the applicability of the proposed method. The simulation results obtained are compared with previous methods reported in the literature and found to be encouraging.

scholarly journals A Multi-Objective Optimization Method for Hospital Admission Problem—A Case Study on Covid-19 Patients

Algorithms ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 38
Author(s):  
Amr Mohamed AbdelAziz ◽  
Louai Alarabi ◽  
Saleh Basalamah ◽  
Abdeltawab Hendawi
Keyword(s):  
Medical Care ◽  
Real Life ◽  
Optimization Method ◽  
Multi Objective Optimization ◽  
Admission Process ◽  
Multi Objective ◽  
Admission Time ◽  
King Faisal Specialist Hospital ◽  
Number Of Patients ◽  
Massive Number

The wide spread of Covid-19 has led to infecting a huge number of patients, simultaneously. This resulted in a massive number of requests for medical care, at the same time. During the first wave of Covid-19, many people were not able to get admitted to appropriate hospitals because of the immense number of patients. Admitting patients to suitable hospitals can decrease the in-bed time of patients, which can lead to saving many lives. Also, optimizing the admission process can minimize the waiting time for medical care, which can save the lives of severe cases. The admission process needs to consider two main criteria: the admission time and the readiness of the hospital that will accept the patients. These two objectives convert the admission problem into a Multi-Objective Problem (MOP). Pareto Optimization (PO) is a common multi-objective optimization method that has been applied to different MOPs and showed its ability to solve them. In this paper, a PO-based algorithm is proposed to deal with admitting Covid-19 patients to hospitals. The method uses PO to vary among hospitals to choose the most suitable hospital for the patient with the least admission time. The method also considers patients with severe cases by admitting them to hospitals with the least admission time regardless of their readiness. The method has been tested over a real-life dataset that consisted of 254 patients obtained from King Faisal specialist hospital in Saudi Arabia. The method was compared with the lexicographic multi-objective optimization method regarding admission time and accuracy. The proposed method showed its superiority over the lexicographic method regarding the two criteria, which makes it a good candidate for real-life admission systems.

scholarly journals Mechanical properties optimization of the steering column based on multi-objective optimization design

2016 ◽  
Vol 8 (12) ◽  
pp. 168781401668294 ◽  
Author(s):  
Si Chen ◽  
Zhaohui Wang ◽  
Mi Lv
Keyword(s):  
Mechanical Properties ◽  
Process Parameters ◽  
Optimization Design ◽  
Strain Difference ◽  
Optimization Method ◽  
Equivalent Strain ◽  
Multi Objective Optimization ◽  
Optimal Process ◽  
Multi Objective ◽  
Initial Results

The mechanical properties of the steering column have a significant influence on the comfort and stability of a vehicle. In order for the mechanical properties to be improved, the rotary swaging process of the steering column is studied in this article. The process parameters, including axial feed rate, hammerhead speed, and hammerhead radial reduction, are systematically analyzed and optimized based on a multi-objective optimization design. The response surface methodology and the genetic algorithm are employed for optimal process parameters to be obtained. The maximum damage value, the maximum forming load, and the equivalent strain difference obtained with the optimal process parameters are, respectively, decreased by 30.09%, 7.44%, and 57.29% compared to the initial results. The comparative results present that the quality of the steering column is improved. The torque experiments and fatigue experiments are conducted with the optimal steering column. The maximum torque is measured to be 260 NM, and the service life is measured to be 2 weeks (40 NM, 2500 times), which are, respectively, increased by 8.3% and 8.69% compared to the initial results. The above results display that the mechanical properties of the steering column are optimized to verify the feasibility of the multi-objective optimization method.

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