A Fuzzy Classifier-Based Penetration Testing for Web Applications

The biggest challenge of Web application is the inestimable losses arising from security flaws. Two approaches were advanced by a number of scholars to provide security to Web space. One of such approach is vulnerability assessment, which is a conscious effort to isolate, identify and recognize potentials vulnerabilities exploited by attackers. The second being the estimation and determination of level of risks/threats posed to Web applications by vul- nerabilities obvious to the developer (or tester); this is generally referred to as penetration testing. Recently, there is Vulnerability Assessment and Penetration Testing (VAPT) that combined these two schemes to improve safety and effec- tively combat the menace of attackers on Web applications. This paper proposed Fuzzy Classifier-based Vulnerability and Assessment Testing (FCVAPT) model to provide security for sensitive data/information in Web applications. Cross Site Scripting (XSS) and Structured Query Language (SQL) injections were selected for evaluation of proposed FCVAPT model. FCVAPT model’s classification performance for MSE, MAPE and RMSE were 33.33, 14.81% and 5.77% respectively. FCVAPT is considerably effective for detecting vulnerability and ascertaining the nature of threats/risks available to Web applications

Comparative Evaluation of Mobile Forensic Tools

The rapid rise in the technology today has brought to limelight mobile devices which are now being used as a tool to commit crime. Therefore, proper steps need to be ensured for Confidentiality, Integrity, Authenticity and legal acquisition of any form of digital evidence from the mobile devices. This study evaluates some mobile forensic tools that were developed mainly for mobile devices memory and SIM cards. An experiment was designed with five android phones with different Operating System. Four tools were used to find out the capability and efficiency of the tools when used on the sampled phones. This would help the forensic investigator to know the type of tools that will be suitable for each phone to be investigated for acquiring digital evidence. The evaluation result showed that AccessData FTK imager and Paraben device seizure performs better than Encase and Mobiledit. The experimental result shows that, Encase could detect the unallocated space on the mobile deice but could retrieve an deleted data

A Fuzzy Classifier-Based Penetration Testing for Web Applications

The biggest challenge of Web application is the inestimable losses arising from security flaws. Two approaches were advanced by a number of scholars to provide security to Web space. One of such approach is vulnerability assessment, which is a conscious effort to isolate, identify and recognize potentials vulnerabilities exploited by attackers. The second being the estimation and determination of level of risks/threats posed to Web applications by vul- nerabilities obvious to the developer (or tester); this is generally referred to as penetration testing. Recently, there is Vulnerability Assessment and Penetration Testing (VAPT) that combined these two schemes to improve safety and effec- tively combat the menace of attackers on Web applications. This paper proposed Fuzzy Classifier-based Vulnerability and Assessment Testing (FCVAPT) model to provide security for sensitive data/information in Web applications. Cross Site Scripting (XSS) and Structured Query Language (SQL) injections were selected for evaluation of proposed FCVAPT model. FCVAPT model’s classification performance for MSE, MAPE and RMSE were 33.33, 14.81% and 5.77% respectively. FCVAPT is considerably effective for detecting vulnerability and ascertaining the nature of threats/risks available to Web applications

IMF Mode Demixing in EMD for Jitter Analysis

We propose a novel noise cancellation method based on the scale-adaptive remixing and demixing of Intrinsic Mode Functions (IMFs) constructed using Empirical Mode Decomposition (EMD). The method addresses the problem of mode mixing in the EMD by performing mode demixing. An illustrative example using noisy random binary sequence is presented. The proposed approach allows achieving better denoising results than the classic first IMF discarding approach

Android Malware Detection: A Survey

In the world today, smartphones are evolving every day and with this evolution, security becomes a big issue. Security is an important aspect of the human existence and in a world, with inadequate security, it becomes an issue for the safety of the smartphone users. One of the biggest security threats to smartphones is the issue of malware. The study carried out a survey on malware detection techniques towards identifying gaps, and to provide the basis for improving and effective measure for unknown android malware. The results showed that machine learning is a more promising approach with higher detection accuracy. Upcoming researchers should look into deep learning approach with the use of a large dataset in order to achieve a better accuracy

Serious game iDO: Towards better education in dementia care

We describe the iDO serious game developed during implementation of the Innovative Digital Training Opportunities on Dementia for Direct CareWorkers (IDO) project. The project targets formal and informal caregivers of persons with dementia in order to improve caregiver knowledge and competences skills with a non-traditional source of training. This paper describes the steps faced to define the iDO caregiver behavior improvement model, design of game mechanics, development of game art and game characters, and implementation of gameplay. Furthermore, it aimed to assess the direct impact of the game on caregivers (n = 48) and seniors with early signs of dementia (n = 14) in Lithuania measured with the Geriatric Depression Scale (GDS) and Dementia Attitudes Scale (DAS). The caregivers' GDS scores showed a decrease in negative answers from 13.4% (pre-game survey) to 5.2% (post-game survey). The seniors' GDS scores showed a decrease in negative answers from 24.9% (pre-game survey) to 10.9% (post-game survey). The overall DAS scores increased from 6.07 in the pre-game survey to 6.41 in the post-game survey, statistically significant for both caregivers and seniors (p < 0.001), respectively. We conclude that the game aroused positive moods and attitudes for future caregivers of persons with dementia, indicating a more relaxed status and a decreased fear in accomplishing the caring process