Black-box web application vulnerability scanners are automated tools that probe web applications for security vulnerabilities In order to assess the current state of the art, we obtained access to eight leading tools and carried out a study of: (i) the class of vulnerabilities tested by these scanners, (ii) their effectiveness against target vulnerabilities, and (iii) the relevance of the target vulnerabilities to vulnerabilities found in the wild To conduct our study we used a custom web application vulnerable to known and projected vulnerabilities, and previous versions of widely used web applications containing known vulnerabilities Our results show the promise and effectiveness of automated tools, as a group, and also some limitations In particular, "stored" forms of Cross Site Scripting (XSS) and SQL Injection (SQLI) vulnerabilities are not currently found by many tools Because our goal is to assess the potential of future research, not to evaluate specific vendors, we do not report comparative data or make any recommendations about purchase of specific tools

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State of the art automated black-box web application vulnerability testing

A novel metaheuristic optimizer inspired by behavior of jellyfish in ocean

Recently, numerous meta-heuristic-based approaches are deliberated to reduce the computational complexities of several existing approaches that include tricky derivations, very large memory space requirement, initial value sensitivity, etc. However, several optimization algorithms namely firefly algorithm, sine–cosine algorithm, and particle swarm optimization algorithm have few drawbacks such as computational complexity and convergence speed. So to overcome such shortcomings, this paper aims in developing a novel chaotic sine–cosine firefly (CSCF) algorithm with numerous variants to solve optimization problems. Here, the chaotic form of two algorithms namely the sine–cosine algorithm and the firefly algorithms is integrated to improve the convergence speed and efficiency thus minimizing several complexity issues. Moreover, the proposed CSCF approach is operated under various chaotic phases and the optimal chaotic variants containing the best chaotic mapping are selected. Then numerous chaotic benchmark functions are utilized to examine the system performance of the CSCF algorithm. Finally, the simulation results for the problems based on engineering design are demonstrated to prove the efficiency, robustness and effectiveness of the proposed algorithm.

CSCF: a chaotic sine cosine firefly algorithm for practical application problems

Patterns of temperature fluctuations in nature affect numerous biological processes, yet, empirical studies often utilize constant temperature treatments. This can limit our understanding of how thermally sensitive species respond to ecologically relevant temperatures. Research on turtles with temperature-dependent sex determination (TSD) provides good examples of this, since nest temperatures from many populations rarely exceed those necessary to produce females under constant laboratory conditions. We hypothesized that exposure to brief periods of warm temperatures (i.e., heat waves) are integral to sex determination in species with TSD, which requires tests that move beyond constant temperatures. We exposed Trachemys scripta embryos from multiple populations and across the nesting season to heat waves of variable durations and quantified sex ratios. We found that embryos from all populations were highly sensitive to brief exposures to female producing temperatures; only 7.9 days of exposure produced a 50:50 sex ratio, but the response varied across the nesting season. From these findings, a model was developed to estimate sex ratios from field temperature traces, and this model outperformed traditional methods. Overall, these results enhance our understanding of TSD and emphasize the importance of using biologically relevant temperatures when studying thermally sensitive processes.

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Short heatwaves during fluctuating incubation regimes produce females under temperature-dependent sex determination with implications for sex ratios in nature.

Recently, numerous meta-heuristic based approaches are deliberated to reduce the computational complexities of several existing approaches that include tricky derivations, very large memory space requirement, initial value sensitivity etc. However, several optimization algorithms namely firefly algorithm, sine cosine algorithm, particle swarm optimization algorithm have few drawbacks such as computational complexity, convergence speed etc. So to overcome such shortcomings, this paper aims in developing a novel Chaotic Sine Cosine Firefly (CSCF) algorithm with numerous variants to solve optimization problems. Here, the chaotic form of two algorithms namely the sine cosine algorithm (SCA) and the Firefly (FF) algorithms are integrated to improve the convergence speed and efficiency thus minimizing several complexity issues. Moreover, the proposed CSCF approach is operated under various chaotic phases and the optimal chaotic variants containing the best chaotic mapping is selected. Then numerous chaotic benchmark functions are utilized to examine the system performance of the CSCF algorithm. Finally, the simulation results for the problems based on engineering design are demonstrated to prove the efficiency, robustness and effectiveness of the proposed algorithm.

CSCF: a chaotic sine cosine firefly Algorithm for practical application problems

Datasets on statistical analysis and performance evaluation of backtracking search optimisation algorithm compared with its counterpart algorithms.

Operational framework for recent advances in backtracking search optimisation algorithm: A systematic review and performance evaluation

Office automation is an initiative used to digitally deliver services to citizens, private and public sectors. It is used to digitally collect, store, create, and manipulate office information as a need of accomplishing basic tasks. Azya Office Automation has been implemented as a pilot project in Kurdistan Institution for Strategic Studies and Scientific Research (KISSR) since 2013. The efficiency of governance in Kurdistan Institution for Strategic Studies and Scientific Research has been improved, thanks to its implementation. The aims of this research paper is to evaluate user satisfaction of this software and identify its significant predictors using EGOVSAT Model. The user satisfaction of this model encompasses five main parts, which are utility, reliability, efficiency, customization, and flexibility. For that purpose, a detailed survey is conducted to measure the level of user satisfaction. A total of sixteen questions have distributed among forty one users of the software in KISSR. In order to evaluate the software, three measurement have been used which are reliability test, regression analysis and correlation analysis. The results indicate that the software is successful to a decent extent based on user satisfaction feedbacks obtained by using EGOVSAT Model.

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Bryar A. Hassan

Papers

CSCF: a chaotic sine cosine firefly algorithm for practical application problems

CSCF: a chaotic sine cosine firefly Algorithm for practical application problems

Datasets on statistical analysis and performance evaluation of backtracking search optimisation algorithm compared with its counterpart algorithms.

Operational framework for recent advances in backtracking search optimisation algorithm: A systematic review and performance evaluation

Evaluating e-Government Services in Kurdistan Institution for Strategic Studies and Scientific Research Using the EGOVSAT Model