Hybrid Computational Modeling for Web Application Security Assessment

Transformation from conventional business management systems to smart digital systems is a recurrent trend in the current era.This has led to digital revolution,and in this context,the hardwired technologies in the software industry play a significant role However,from the beginning,software security remains a serious issue for all levels of stakeholders.Software vulnerabilities lead to intrusions that cause data breaches and result in disclosure of sensitive data,compromising the organizations’reputation that translates into,financial losses as well.Most of the data breaches are financially motivated,especially in the healthcare sector.The cyber invaders continuously penetrate the E-Health data because of the high cost of the data on the dark web.Therefore,security assessment of healthcare web-based applications demands immediate intervention mechanisms to weed out the threats of cyber-attacks.The aim of this work is to provide efficient and effective healthcare web application security assessment.The study has worked with the hybrid computational model of Multi-Criteria Decision Making(MCDM)based on Analytical Hierarchy Process(AHP)and Technique for Order of Preference by Similarity to Ideal-Solutions(TOPSIS)under the Hesitant Fuzzy(HF)environment.Hesitant fuzzy sets provide effective solutions to address decision making problems where experts counter hesitation to make a decision.The proposed research endeavor will support designers and developers in identifying,selecting and prioritizing the best security attributes for web applications’development.The empirical analysis concludes that Robustness got highest priority amongst the assessed security attributes set followed by Encryption,Authentication,Limit Access,Revoke Access,Data Validation,and Maintain Audit Trail.The results of this research endeavor depict that this proposed computational procedure would be the most conversant mechanism for determining the web application security.The study also establishes guidelines which the developers can refer for the identification and prioritization of security attributes to build more secure and trustworthy web-based applications.

Ecological Security Assessment of Red River Basin in Guangxi

[Objective] The study aimed at assessing the ecological security of Red River basin in Guangxi. [Method] Firstly, the ecological security assessment index system of Red River basin was established based on the framework of 'pressure-state-response' model, and index information of ecological security assessment was extracted by using RS and GIS technology; afterwards, the ecological security of Red River basin was divided into five grades according to ecological security index, and the distribution and characteristics of ecological security at various levels were analyzed; finally, the measures to maintain the ecological security of Red River basin were put forward on the basis of problems in ecological security. [Result] Most areas of Red River basin in Guangxi were in generally safe state, especially Lingyun County, Fengshan County, Du'an County, Dahua County, Shanglin County, Binyang County, Guiping City, etc., and the area accounted for 74.25% of total area; next came safer state (12.74%), the regions in the two states above were the most important environmental areas of Red River basin. The ecological security problems of Red River basin were mainly related to fragile ecological environment, lagging economic development, rapid population growth, excessive development and utilization of natural resources and so forth. [Conclusion] The research could provide scientific references for the rational development and utilization of land resources, protection and construction of ecological environment in Red River basin.

Ecological Investigation and Ecological Security Assessment of Xizhijiang River Basin in Huizhou City of Guangdong Province

In addition to such ecological problems as the pollution of the water system,the unreasonable structure of the upstream Basin and the insufficient water conservation forests,the Xizhi River Basin also faces human decision-making problems such as imperfect ecological compensation mechanism.In view of the above problems,using the DPSIR model(Drivers,Pressures,States,Impacts,Responses),this paper analyzed eucalyptus forest in Xizhi River Basin to assess the security of the Xizhi River ecological Basin,and finally concluded that the ecological status of Xizhi River Basin remains safe.

Understanding Discrepancy of Power System Dynamic Security Assessment with Unknown Faults: A Reliable Transfer Learning-based Method

This letter proposes a reliable transfer learning(RTL)method for pre-fault dynamic security assessment(DSA)in power systems to improve DSA performance in the presence of potentially related unknown faults.It takes individual discrepancies into consideration and can handle unknown faults with incomplete data.Extensive experiment results demonstrate high DSA accuracy and computational efficiency of the proposed RTL method.Theoretical analysis shows RTL can guarantee system performance.

Fortifying Smart Grids: A Holistic Assessment Strategy against Cyber Attacks and Physical Threats for Intelligent Electronic Devices

Intelligent electronic devices(IEDs)are interconnected via communication networks and play pivotal roles in transmitting grid-related operational data and executing control instructions.In the context of the heightened security challenges within smart grids,IEDs pose significant risks due to inherent hardware and software vulner-abilities,as well as the openness and vulnerability of communication protocols.Smart grid security,distinct from traditional internet security,mainly relies on monitoring network security events at the platform layer,lacking an effective assessment mechanism for IEDs.Hence,we incorporate considerations for both cyber-attacks and physical faults,presenting security assessment indicators and methods specifically tailored for IEDs.Initially,we outline the security monitoring technology for IEDs,considering the necessary data sources for their security assessment.Subsequently,we classify IEDs and establish a comprehensive security monitoring index system,incorporating factors such as running states,network traffic,and abnormal behaviors.This index system contains 18 indicators in 3 categories.Additionally,we elucidate quantitative methods for various indicators and propose a hybrid security assessment method known as GRCW-hybrid,combining grey relational analysis(GRA),analytic hierarchy process(AHP),and entropy weight method(EWM).According to the proposed assessment method,the security risk level of IEDs can be graded into 6 levels,namely 0,1,2,3,4,and 5.The higher the level,the greater the security risk.Finally,we assess and simulate 15 scenarios in 3 categories,which are based on monitoring indicators and real-world situations encountered by IEDs.The results show that calculated security risk level based on the proposed assessment method are consistent with actual simulation.Thus,the reasonableness and effectiveness of the proposed index system and assessment method are validated.

A New Model for Network Security Situation Assessment of the Industrial Internet

To address the problem of network security situation assessment in the Industrial Internet,this paper adopts the evidential reasoning(ER)algorithm and belief rule base(BRB)method to establish an assessment model.First,this paper analyzes the influencing factors of the Industrial Internet and selects evaluation indicators that contain not only quantitative data but also qualitative knowledge.Second,the evaluation indicators are fused with expert knowledge and the ER algorithm.According to the fusion results,a network security situation assessment model of the Industrial Internet based on the ER and BRB method is established,and the projection covariance matrix adaptive evolution strategy(P-CMA-ES)is used to optimize the model parameters.This method can not only utilize semiquantitative information effectively but also use more uncertain information and prevent the problem of combinatorial explosion.Moreover,it solves the problem of the uncertainty of expert knowledge and overcomes the problem of low modeling accuracy caused by insufficient data.Finally,a network security situation assessment case of the Industrial Internet is analyzed to verify the effectiveness and superiority of the method.The research results showthat this method has strong applicability to the network security situation assessment of complex Industrial Internet systems.It can accurately reflect the actual network security situation of Industrial Internet systems and provide safe and reliable suggestions for network administrators to take timely countermeasures,thereby improving the risk monitoring and emergency response capabilities of the Industrial Internet.

Ontology-Based Model of Network and Computer Attacks for Security Assessment

With increased cyber attacks over years,information system security assessment becomes more and more important.This paper provides an ontology-based attack model,and then utilizes it to assess the information system security from attack angle.We categorize attacks into a taxonomy suitable for security assessment.The proposed taxonomy consists of five dimensions,which include attack impact,attack vector,attack target,vulnerability and defense.Afterwards we build an ontology according to the taxonomy.In the ontology,attack related concepts included in the five dimensions and relationships between them are formalized and analyzed in detail.We also populate our attack ontology with information from national vulnerability database(NVD)about the vulnerabilities,such as common vulnerabilities and exposures(CVE),common weakness enumeration(CWE),common vulnerability scoring system(CVSS),and common platform enumeration(CPE).Finally we propose an ontology-based framework for security assessment of network and computer systems,and describe the utilization of ontology in the security assessment and the method for evaluating attack efect on the system when it is under attack.

Impact analysis of false data injection attacks on power system static security assessment

Static security assessment(SSA) is an important procedure to ensure the static security of the power system.Researches recently show that cyber-attacks might be a critical hazard to the secure and economic operations of the power system. In this paper, the influences of false data injection attack(FDIA) on the power system SSA are studied. FDIA is a major kind of cyber-attacks that can inject malicious data into meters, cause false state estimation results, and evade being detected by bad data detection. It is firstly shown that the SSA results could be manipulated by launching a successful FDIA, which can lead to incorrect or unnecessary corrective actions. Then,two kinds of targeted scenarios are proposed, i.e., fake secure signal attack and fake insecure signal attack. The former attack will deceive the system operator to believe that the system operates in a secure condition when it is actually not. The latter attack will deceive the system operator to make corrective actions, such as generator rescheduling, load shedding, etc. when it is unnecessary and costly. The implementation of the proposed analysis is validated with the IEEE-39 benchmark system.

Data-driven Probabilistic Static Security Assessment for Power System Operation Using High-order Moments

In this letter,a new formulation of Lebesgue integration is used to evaluate the probabilistic static security of power system operation with uncertain renewable energy generation.The risk of power flow solutions violating any pre-defined operation security limits is obtained by integrating a semialgebraic set composed of polynomials.With the high-order moments of historical data of renewable energy generation,the integration is reformulated as a generalized moment problem which is then relaxed to a semi-definite program(SDP).Finally,the effectiveness of the proposed method is verified by numerical examples.

Selecting decision trees for power system security assessment

Power systems transport an increasing amount of electricity,and in the future,involve more distributed renewables and dynamic interactions of the equipment.The system response to disturbances must be secure and predictable to avoid power blackouts.The system response can be simulated in the time domain.However,this dynamic security assessment(DSA)is not computationally tractable in real-time.Particularly promising is to train decision trees(DTs)from machine learning as interpretable classifiers to predict whether the systemwide responses to disturbances are secure.In most research,selecting the best DT model focuses on predictive accuracy.However,it is insufficient to focus solely on predictive accuracy.Missed alarms and false alarms have drastically different costs,and as security assessment is a critical task,interpretability is crucial for operators.In this work,the multiple objectives of interpretability,varying costs,and accuracies are considered for DT model selection.We propose a rigorous workflow to select the best classifier.In addition,we present two graphical approaches for visual inspection to illustrate the selection sensitivity to probability and impacts of disturbances.We propose cost curves to inspect selection combining all three objectives for the first time.Case studies on the IEEE 68 bus system and the French system show that the proposed approach allows for better DT-selections,with an 80%increase in interpretability,5%reduction in expected operating cost,while making almost zero accuracy compromises.The proposed approach scales well with larger systems and can be used for models beyond DTs.Hence,this work provides insights into criteria for model selection in a promising application for methods from artificial intelligence(AI).

Information Security Evaluation of Industrial Control Systems Using Probabilistic Linguistic MCDM Method

Industrial control systems(ICSs)are widely used in various fields,and the information security problems of ICSs are increasingly serious.The existing evaluation methods fail to describe the uncertain evaluation information and group evaluation information of experts.Thus,this paper introduces the probabilistic linguistic term sets(PLTSs)to model the evaluation information of experts.Meanwhile,we propose a probabilistic linguistic multi-criteria decision-making(PL-MCDM)method to solve the information security assessment problem of ICSs.Firstly,we propose a novel subscript equivalence distance measure of PLTSs to improve the existing methods.Secondly,we use the Best Worst Method(BWM)method and Criteria Importance Through Inter-criteria Correlation(CRITIC)method to obtain the subjective weights and objective weights,which are used to derive the combined weights.Thirdly,we use the subscript equivalence distance measure method and the combined weight method to improve the probabilistic linguistic Visekriterijumska Optimizacija I Kompromisno Resenje(PL-VIKOR)method.Finally,we apply the proposed method to solve the information security assessment problem of ICSs.When comparing with the existing methods such as the probabilistic linguistic Tomada deDecisão Iterativa Multicritério(PL-TODIM)method and probabilistic linguistic Technique for Order Preference by Similarity to Ideal Solution(PL-TOPSIS)method,the case example shows that the proposed method can provide more reasonable ranking results.By evaluating and ranking the information security level of different ICSs,managers can identify problems in time and guide their work better.

Security Risk Assessment of Cyber Physical Power System Based on Rough Set and Gene Expression Programming

Risk assessment is essential for the safe and reliable operation of cyber physical power system. Traditional security risk assessment methods do not take integration of cyber system and physical system of power grid into account. In order to solve this problem, security risk assessment algorithm of cyber physical power system based on rough set and gene expression programming is proposed. Firstly, fast attribution reduction based on binary search algorithm is presented. Secondly, security risk assessment function for cyber physical power system is mined based on gene expression programming. Lastly, security risk levels of cyber physical power system are predicted and analyzed by the above function model. Experimental results show that security risk assessment function model based on the proposed algorithm has high efficiency of function mining, accuracy of security risk level prediction and strong practicality.

Resource Allocation for Network Security Risk Assessment：A Non-Cooperative Differential Game Based Approach

In this paper, we propose a non-cooperative differential game theory based resource allocation approach for the network security risk assessment. For the risk assessment, the resource will be used for risk assess, including response cost and response negative cost. The whole assessment process is considered as a differential game for optimal resource control. The proposed scheme can be obtained through the Nash Equilibrium. It is proved that the game theory based algorithm is applicable and the optimal resource level can be achieved based on the proposed algorithm.

Integrity Assessment of Medical Devices for Improving Hospital Services

The present study examines the various techniques being used to maintain the integrity of the medical devices,and develops a quantitative framework to list these in the sequence of priority.To achieve the intended objective,the study employs the combined procedure of Fuzzy Analytic Network Process(ANP)and Fuzzy Technical for Order Preference by Similarities to Ideal Solution(TOPSIS).We selected fuzzy based decision making techniques for assessing the integrity of medical devices.The suggested methodology was then used for classifying the suitable techniques used to evaluate the integrity of medical devices.Different techniques or the procedures of integrity assessment were ranked according to their satisfaction weights.The rating of the options determined the order of priority for the procedures.As per the findings of the study,among all the options,A1 was assessed to be the most likely option.This means that the integrity of medical devices of A2 is the highest amongst all the chosen alternatives.This analysis will be a corroborative guideline for manufacturers and developers to quantitatively test the integrity of medical devices in order to engineer efficacious devices.The evaluations undertaken with the assistance of the planned procedure are accurate and conclusive.Hence instead of conducting a manual valuation,this experimental study is a better and reliable option for assessing the integrity of the medical devices.

Fuzzy Risk Assessment Method for Airborne Network Security Based on AHP-TOPSIS

With the exponential increase in information security risks,ensuring the safety of aircraft heavily relies on the accurate performance of risk assessment.However,experts possess a limited understanding of fundamental security elements,such as assets,threats,and vulnerabilities,due to the confidentiality of airborne networks,resulting in cognitive uncertainty.Therefore,the Pythagorean fuzzy Analytic Hierarchy Process(AHP)Technique for Order Preference by Similarity to an Ideal Solution(TOPSIS)is proposed to address the expert cognitive uncertainty during information security risk assessment for airborne networks.First,Pythagorean fuzzy AHP is employed to construct an index system and quantify the pairwise comparison matrix for determining the index weights,which is used to solve the expert cognitive uncertainty in the process of evaluating the index system weight of airborne networks.Second,Pythagorean fuzzy the TOPSIS to an Ideal Solution is utilized to assess the risk prioritization of airborne networks using the Pythagorean fuzzy weighted distance measure,which is used to address the cognitive uncertainty in the evaluation process of various indicators in airborne network threat scenarios.Finally,a comparative analysis was conducted.The proposed method demonstrated the highest Kendall coordination coefficient of 0.952.This finding indicates superior consistency and confirms the efficacy of the method in addressing expert cognition during information security risk assessment for airborne networks.

A Novel Risk Assessment Model for Privacy Security in Internet of Things

Aiming at the issues of privacy security in Internet of Things （IoT） applications, we propose an effective risk assessment model to handle probabilistic causality of evaluation factors and derive weights of influence-relation of propagation paths. The model undertakes probabilistic inference and generates values of risk probability for assets and propagation paths by using Bayesian causal relation-network and prior probability. According to Bayes- ian network （BN） structure, the risk analysts can easily find out relevant risk propagation paths and calculate weight values of each path by using decision-making trial and evaluation laboratory （DEMATEL）. This model is applied to determine the risk level of assets and each risk propagation path as well as implement countermeasure of recommendation in accordance with evaluation results. The simulation analysis shows that this model efficiently revises recommendation of countermeasures for decision-makers and mitigates risk to an acceptable range, in addition, it provides the theoretical basis for decision-making of privacy security risk assessment （PSRA） for further development in lot area.

Preventive Control for Power System Transient Security Based on XGBoost and DCOPF with Consideration of Model Interpretability

This paper proposes a new approach for online power system transient security assessment(TSA)and preventive control based on XGBoost and DC optimal power flow(DCOPF).The novelty of this proposal is that it applies the XGBoost and data selection method based on the 1-norm distance in local feature importance evaluation which can provide a certain model interpretability.The method of SMOTE+ENN is adopted for data rebalancing.The contingency-oriented XGBoost model is trained with databases generated by time domain simulations to represent the transient security constraint in the DCOPF model,which has a relatively fast speed of calculation.The transient security constrained generation rescheduling is implemented with the differential evolution algorithm,which is utilized to optimize the rescheduled generation in the preventive control.Feasibility and effectiveness of the proposed approach are demonstrated on an IEEE 39-bus test system and a 500-bus operational model for South Carolina,USA.

A Potential Security Threat and Its Solution in Coupled Urban Power-traffic Networks with High Penetration of Electric Vehicles

The growing penetration of electric vehicles(EVs)and the popularity of fast charging stations(FCSs)have greatly strengthened the coupling of the urban power network(PN)and traffic network(TN).In this paper,a potential security threat of the PN-TN coupling is revealed.Different from traditional loads,a regional FCS outage can lead to both the spatial and temporal redistribution of EV charging loads due to EV mobility,which further leads to a power flow redistribution.To assess the resulting potential threats,an integrated PN-TN modeling framework is developed,where the PN is described by a direct current optimal power flow model,and the TN is depicted by an energy-constraint traffic assignment problem.To protect the privacy of the two networks,an FCS outage distribution factor is proposed to describe the spatial-temporal redistribution ratio of the charging load among the remaining I FCSs.Moreover,to protect the security of the coupled networks,a price-based preventive regulation method,based on the spatial demand elasticity of the EV charging load,is developed to reallocate the charging load as a solution for insecure situations.Numerical simulation results validate the existence of the PN-TN coupling threat and demonstrate the effectiveness of the regulation method to exploit the spatial flexibility of EV loads.

Real-time Online Analysis of Power Grid

The unprecedented operational complexity and se-curity risks in operating the Chinese UHV AC/DC power grid calls for a new generation of real-time(sec-order)online analysis systems to provide decision support.Our recent Digital Twin based online analysis research and development work to address the needs is presented.In addition,a high-level solution architec-ture for the future real-time online analysis systems is proposed for realizing:a)The delay of the virtual model to mirror the physical power grid is in sub-sec range;b)The downstream online analysis applications could have sec-order responsiveness.

Towards an integrated risk analysis security framework according to a systematic analysis of existing proposals

The information society depends increasingly on risk assessment and management systems as means to adequately protect its key information assets.The availability of these systems is now vital for the protection and evolution of companies.However,several factors have led to an increasing need for more accurate risk analysis approaches.These are:the speed at which technologies evolve,their global impact and the growing requirement for companies to collaborate.Risk analysis processes must consequently adapt to these new circumstances and new technological paradigms.The objective of this paper is,therefore,to present the results of an exhaustive analysis of the techniques and methods offered by the scientific community with the aim of identifying their main weaknesses and providing a new risk assessment and management process.This analysis was carried out using the systematic review protocol and found that these proposals do not fully meet these new needs.The paper also presents a summary of MARISMA,the risk analysis and management framework designed by our research group.The basis of our framework is the main existing risk standards and proposals,and it seeks to address the weaknesses found in these proposals.MARISMA is in a process of continuous improvement,as is being applied by customers in several European and American countries.It consists of a risk data management module,a methodology for its systematic application and a tool that automates the process.