Security Test Case Prioritization through Ant Colony Optimization Algorithm

Security testing is a critical concern for organizations worldwide due to the potential financial setbacks and damage to reputation caused by insecure software systems.One of the challenges in software security testing is test case prioritization,which aims to reduce redundancy in fault occurrences when executing test suites.By effectively applying test case prioritization,both the time and cost required for developing secure software can be reduced.This paper proposes a test case prioritization technique based on the Ant Colony Optimization(ACO)algorithm,a metaheuristic approach.The performance of the ACO-based technique is evaluated using the Average Percentage of Fault Detection(APFD)metric,comparing it with traditional techniques.It has been applied to a Mobile Payment Wallet application to validate the proposed approach.The results demonstrate that the proposed technique outperforms the traditional techniques in terms of the APFD metric.The ACO-based technique achieves an APFD of approximately 76%,two percent higher than the second-best optimal ordering technique.These findings suggest that metaheuristic-based prioritization techniques can effectively identify the best test cases,saving time and improving software security overall.

A Trailblazing Framework of Security Assessment for Traffic Data Management

Connected and autonomous vehicles are seeing their dawn at this moment.They provide numerous benefits to vehicle owners,manufacturers,vehicle service providers,insurance companies,etc.These vehicles generate a large amount of data,which makes privacy and security a major challenge to their success.The complicated machine-led mechanics of connected and autonomous vehicles increase the risks of privacy invasion and cyber security violations for their users by making them more susceptible to data exploitation and vulnerable to cyber-attacks than any of their predecessors.This could have a negative impact on how well-liked CAVs are with the general public,give them a poor name at this early stage of their development,put obstacles in the way of their adoption and expanded use,and complicate the economic models for their future operations.On the other hand,congestion is still a bottleneck for traffic management and planning.This research paper presents a blockchain-based framework that protects the privacy of vehicle owners and provides data security by storing vehicular data on the blockchain,which will be used further for congestion detection and mitigation.Numerous devices placed along the road are used to communicate with passing cars and collect their data.The collected data will be compiled periodically to find the average travel time of vehicles and traffic density on a particular road segment.Furthermore,this data will be stored in the memory pool,where other devices will also store their data.After a predetermined amount of time,the memory pool will be mined,and data will be uploaded to the blockchain in the form of blocks that will be used to store traffic statistics.The information is then used in two different ways.First,the blockchain’s final block will provide real-time traffic data,triggering an intelligent traffic signal system to reduce congestion.Secondly,the data stored on the blockchain will provide historical,statistical data that can facilitate the analysis of traffic conditions according to past behavior.

Estimating the Impact of COVID-19 Pandemic on the Research Community in the Kingdom of Saudi Arabia

Ever since its outbreak inWuhan,COVID-19 has cloaked the entireworld in a pall of despondency and uncertainty.The present study describes the exploratory analysis of all COVID cases in Saudi Arabia.Besides,the study has executed the forecastingmodel for predicting the possible number of COVID-19 cases in Saudi Arabia till a defined period.Towards this intent,the study analyzed different age groups of patients(child,adult,elderly)who were affected by COVID-19.The analysis was done city-wise and also included the number of recoveries recorded in different cities.Furthermore,the study also discusses the impact of COVID-19 on the economy.For conducting the stated analysis,the authors have created a list of factors that are known to cause the spread of COVID-19.As an effective countermeasure to contain the spread of Coronavirus in Saudi Arabia,this study also proposes to identify the most effective Computer Science technique that can be used by healthcare professionals.For this,the study employs the Fuzzy-Analytic Hierarchy Process integrated with the Technique for Order Performance by Similar to Ideal Solution(F.AHP.TOPSIS).After prioritizing the various Computer Science techniques,the ranking order that was obtained for the different techniques/tools to contain COVID-19 was:A4>A1>A2>A5>A3.Since the Blockchain technique obtained the highest priority,the study recommends that it must be used extensively as an efficacious and accurate means to combat COVID-19.

Managing Security-Risks for Improving Security-Durability of Institutional Web-Applications: Design Perspective

The advanced technological need,exacerbated by the flexible time constraints,leads to several more design level unexplored vulnerabilities.Security is an extremely vital component in software development;we must take charge of security and therefore analysis of software security risk assumes utmost significance.In order to handle the cyber-security risk of the web application and protect individuals,information and properties effectively,one must consider what needs to be secured,what are the perceived threats and the protection of assets.Security preparation plans,implements,tracks,updates and consistently develops safety risk management activities.Risk management must be interpreted as the major component for tackling security efficiently.In particular,during application development,security is considered as an add-on but not the main issue.It is important for the researchers to stress on the consideration of protection right from the earlier developmental stages of the software.This approach will help in designing software which can itself combat threats and does not depend on external security programs.Therefore,it is essential to evaluate the impact of security risks during software design.In this paper the researchers have used the hybrid Fuzzy AHPTOPSIS method to evaluate the risks for improving security durability of different Institutional Web Applications.In addition,the e-component of security risk is measured on software durability,and vice versa.The paper’s findings will prove to be valuable for enhancing the security durability of different web applications.

Estimating Usable-Security Through Hesitant Fuzzy Linguistic Term Sets Based Technique

The apparent contradiction between usability and security has been discussed in the literature for several years.This continuous trade-off requires be acknowledging and handling whenever security solutions are introduced.However,some progressive analysts point out that present security solutions are usually very difficult for several users,and they have expressed a willingness to simplify the security product user experience.Usable security is still mostly unexplored territory in computer science.Which we are all aware with security and usability on many levels,usable security has received little operational attention.Companies have recently focused primarily on usable security.As consumers prefer to discard unsatisfactory solutions,attaining well-balanced degrees of both is a prerequisite for adequate security.Usability should be examined from the viewpoint of security to be properly assessed.The aim of this research study is to explore and discuss universally accepted and solutionindependent factors influencing the perceived usable-security of institutional websites.An integrated Hesitant Fuzzy Linguistic term sets based technique was chosen as the methodology,and the experts and academicians opinion were collected.The use of predetermined selection criteria resulted in the compilation of statistical findings and were used to determine the usable-security of five different instituational websites.

Prediction of COVID-19 Pandemic Spread in Kingdom of Saudi Arabia

A significant increase in the number of coronavirus cases can easily be noticed in most of the countries around the world.Inspite of the consistent preventive initiatives being taken to contain the spread of this virus,the unabated increase in the cases is both alarming and intriguing.The role of mathematical models in predicting and estimating the spread of the virus,and identifying various preventive factors dependencies has been found important and effective in most of the previous pandemics like Severe Acute Respiratory Syndrome(SARS)2003.In this research work,authors have proposed the Susceptible-Infectected-Removed(SIR)model variation in order to forecast the pattern of coronavirus disease(COVID-19)spread for the upcoming eight weeks in perspective of Saudi Arabia.The study has been performed by using SIR model with a proposed simplification using average progression for further estimation ofβandγvalues for better curve fittings ratios.The predictive results of this study clearly show that under the current public health interventions,there will be an increase in the COVID-19 cases in Saudi Arabia in the next four weeks.Hence,a set of strong health primitives and precautionary measures are recommended in order to avoid and prevent the further spread of COVID-19 in Saudi Arabia.