Browsing by Author "Misra, Sanjay"
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Article Citation Count: 20Adopting automated whitelist approach for detecting phishing attacks(Elsevier Advanced Technology, 2021) Mısra, Sanjay; Misra, Sanjay; Margaret, Ihotu Agbo; Fernandez-Sanz, Luis; Abdulhamid, Shafi'i Muhammad; Computer EngineeringPhishing is considered a great scourge in cyberspace. Presently, there are two major challenges known with the existing anti-phishing solutions. Low detection rate and lack of quick access time in a real-time environment. However, it has been established that blacklist solution methods offer quick and immediate access time but with a low detection rate. This research paper presents an automated white-list approach for detecting phishing attacks. The white-list is determined by carrying out a detailed analysis between the visual link and the actual link. The similarities of the known trusted site are calculated by juxtaposing the domain name with the contents of the whitelist and later match it with the IP address before a decision is made and further analyzing the actual link and the visual link by calculating the similarities of the known trusted site. The technique then takes a final decision on the extracted information from the hyperlink, which can also be obtained from the web address provided by the user. The experiments carried out provided a very high level of accuracy, specifically, when the dataset was relatively at the lowest level. Six different datasets were used to perform the experiments. The average accuracy obtained after the six experiments was 96.17% and the approach detects phishing sites with a 95.0% true positive rate. It was observed that the level of accuracy varies from one dataset to another. This result shows that the proposed method performs better than similar approaches benchmarked with. The efficiency of the approach was further established through its computation time, memory, bandwidth as well as other computational resources that were utilized with the minimum requirements when compared with other approaches. This solution has provided immense benefits over the existing solutions by reducing the memory requirements and computational complexity, among other benefits. It has also shown that the proposed method can provide more robust detection performances when compared to other techniques. (c) 2021 Elsevier Ltd. All rights reserved.Article Citation Count: 31Adoption of mobile applications for teaching-learning process in rural girls' schools in India: an empirical study(Springer, 2020) Mısra, Sanjay; Majumdar, Dipasree; Misra, Sanjay; Damasevicius, Robertas; Computer EngineeringThe purpose of this study is to identify the factors that can impact the adoption of mobile apps for teaching-learning process focusing on the girls' school in rural India. The hypotheses were proposed and a conceptual model has been developed. There is a survey work conducted to collect the data from different respondents using a convenience sampling method. The model has been validated statistically through PLS-SEM analysis covering feedbacks of 271 effective respondents. The study highlights the impact of different antecedents of the behavioural intention of the students of using mobile applications for teaching-learning process. The results also show that among other issues, price value has insignificant influence on the intention of the girl students of the rural India. During survey feedbacks have been obtained from the 271 respondents, which is meagre compared to vastness of the population and school of rural India. Only few predictors have been considered leaving possibilities of inclusion of other boundary conditions to enhance the explanative power more than that has been achieved in the proposed model with the explanative power of 81%. The model has provided laudable inputs to the educational policy makers and technology enablers and administrators to understand the impact of the mobile applications on the rural girls' school of India and facilitate the development of m-learning. Very few studies been conducted to explore the impact of mobile applications on the school education of rural India especially focusing on the girls' schools.Article Citation Count: 21Agriculture 4.0: An Implementation Framework for Food Security Attainment in Nigeria's Post-Covid-19 Era(Ieee-inst Electrical Electronics Engineers inc, 2021) Mısra, Sanjay; Misra, Sanjay; Fernandez-Sanz, Luis; Computer EngineeringThe challenge of Nigeria's food insecurity in the era of the Covid-19 pandemic, insecurity, climate change, population growth, food wastage, etc., is a demanding task. This study addresses Nigeria's food insecurity challenges by adopting agriculture 4.0 and commercial farming. Using data from six digital libraries, the Nigerian Bureau of Statistics, and other internet sources, we conducted a Systematic Literature Review (SLR using PRISMA) on Nigeria's agriculture, food security, and agriculture 4.0. Our results show Nigeria's current agricultural state, threats to food security, and modern digital agriculture technologies. We adapted our SLR findings to develop an implementation framework for agriculture 4.0 in solving Nigeria's food insecurity challenge in the post-Covid-19 era. Our proposed framework integrates precision agriculture in Nigeria's food production and the necessary enabling digital technologies in the agri-food supply chain. We analyzed the critical implementation considerations during each agri-food supply chain stage of farming inputs, farming scale, farming approach, farming operation, food processing, food preservation/storage, distribution/logistics, and the final consumers. This study will help researchers, investors, and the government address food security in Nigeria. The implementation of agriculture 4.0 will substantially contribute to SDG 2 (zero hunger), SDG 3 (good health and well-being), and SDG 8 (decent work and economic growth) of #Envision 2030 of the United Nations, for the benefit of Nigeria, Africa, and the entire world.Article Citation Count: 20Analysis of cultural and gender influences on teamwork performance for software requirements analysis in multinational environments(Wiley, 2012) Mısra, Sanjay; Misra, Sanjay; Computer EngineeringSoftware development is mainly a social activity where teams of developers should work as a coordinated unit to fulfill the needs of customers. Studies have shown the importance of teamwork ability as the main skill for software professionals both in local settings and in global software development. Teamwork performance can be evaluated according to different approaches but we need deeper analysis within software teams of differences in individuals' performance related to culture, nationality or even gender. We applied a simple evaluation experience named teamwork benefits awareness (TBA) to groups of last-year students of computing degrees with experience as junior IT professionals during intensive multinational workshops based on international software projects. TBA allowed to measure individual and team performance during a requirements analysis session based on a real project. Results segmented by nationality and gender are presented and analysed in comparison with the data collected from computing professionals in local settings. In general, no significant differences have been found out although interesting relations are suggested with two Hofstede's country indicators. TBA is also perceived as a good technique for highlighting both teamwork benefits as well as the nature of real situations of software requirements analysis and orientation to customer needs.Article Citation Count: 39Analyzing Human Resource Management Practices Within the GSD Context(Taylor & Francis inc, 2012) Mısra, Sanjay; Casado-Lumbreras, Cristina; Soto-Acosta, Pedro; Misra, Sanjay; Garcia-Penalvo, Francisco Jose; Computer EngineeringThe development of software across different countries (and time zones) differs substantially from software development in one single country or region. The management of processes and people, who work in globally distributed teams, requires a high level of coordination and collaboration which needs to be based on established human resource management practices. The People Capability Maturity Model (People-CMM) provides a complete framework that enables quality in human resource management to be improved. However, today, the adoption of the People-CMM within organizations using Global Software Development (GSD) is not an easy task. This paper uses an empirical study to analyze the implementation of the People-CMM within the GSD context. Results confirm that cultural and communication problems are the main challenges in the implementation of the People-CMM adoption within GSD scenarios.Article Citation Count: 16Applicability of Weyuker's Properties on OO Metrics: Some Misunderstandings(Comsis Consortium, 2008) Akman, Kamil İbrahim; Akman, Ibrahim; Mısra, Sanjay; Computer EngineeringWeyuker's properties have been suggested as a guiding tool in identification of a good and comprehensive complexity measure by several researchers. Weyuker proposed nine properties to evaluate complexity measure for traditional programming. However, they are extensively used for evaluating object-oriented (OO) metrics, although the object-oriented features are entirely different in nature. In this paper, two recently reported OO metrics were evaluated and, based on it; the usefulness and relevance of these properties for evaluation purpose for object-oriented systems is discussed.Review Citation Count: 13Assessing the Coverage of E-Health Services in Sub-Saharan Africa A Systematic Review and Analysis(Georg Thieme verlag Kg, 2017) Mısra, Sanjay; Adigun, Taiwo; Misra, Sanjay; Omoregbe, Nicholas; Computer EngineeringBackground: E-Health has attracted growing interests globally. The relative lack of facilities, skills, funds and information on existing e-Health initiatives has affected progress on e-Health in Africa. Objectives: To review publicly available literature on e-Health in sub-Saharan Africa (sSA) towards providing information on existing and ongoing e-Health initiatives in the region. Methods: Searches of relevant literature were conducted on Medline, EMBASE and Global Health, with search dates set from 1990 to 2016. We included studies on e-Health initiatives (prototypes, designs, or completed projects) targeting population groups in sSA. Results: Our search returned 2322 hits, with 26 studies retained. Included studies were conducted in 14 countries across the four sub-regions in sSA (Central, East, South and West) and spreading over a 12-year period, 2002-2014. Six types of e-Health interventions were reported, with 17 studies (65%) based on telemedicine, followed by mHealth with 5 studies (19%). Other e-Health types include expert system, electronic medical records, e-mails, and online health module. Specific medical specialties covered include dermatology (19%), pathology (12%) and radiology (8%). Successes were 'widely reported' (representing 50% overall acceptance or positive feedbacks in a study) in 10 studies (38%). The prominent challenges reported were technical problems, poor inter net and connectivity, participants' selection biases, contextual issues, and lack of funds. Conclusion: E-Health is evolving in sSA, but with poorly published evidence. While we call for more quality research in the region, it is also important that population-wide policies and on-going e-Health initiatives are contextually feasible, acceptable, and sustainable.Article Citation Count: 0Attitude of mobile telecommunication subscribers towards sim card registration in Lagos State, Southwestern Nigeria(Springer india, 2019) Mısra, Sanjay; Omoshule, A.; Misra, Sanjay; Maskeliunas, Rytis; Damasevicius, Robertas; Computer EngineeringDespite the concerted effort of the Nigeria Communication Commission (NCC) to ensure that Nigeria mobile phone subscribers register their SIM cards, there has been some level of apathy on the part of the mobile phone subscribers. This study investigated the attitude of mobile telecommunication subscribers towards SIM card registration in Lagos Metropolis, Nigeria. The theories of planned behaviour and reasoned action were adapted for the study because they provide the necessary constructs that help to investigate the attitudes of telecommunication subscribers. The purposive sampling technique was adopted in selecting five local government areas within Lagos. Random sampling method was used to select 300 mobile phone subscribers. In total, 290 responses were collected and were found usable. Data analysis was performed using statistical methods, and Spearman's correlation analysis was used to test relationship between the variables of interest. The results of the study revealed that SIM card users have positive attitude towards SIM card registration. Perceived usefulness and perceived ease of use significantly influenced subscribers attitude towards SIM card registration with both of them having negative significant relationship with attitude towards registration (r = -.116, r = -.132, p < 0.05) respectively.Article Citation Count: 6Automated Recovery and Visualization of Test-to-Code Traceability (TCT) Links: An Evaluation(Ieee-inst Electrical Electronics Engineers inc, 2021) Mısra, Sanjay; Gergely, Tamas; Misra, Sanjay; Fernandez-Sanz, Luis; Computer EngineeringIn the software development process, traceability links between unit tests and code are not explicitly maintained, and dependencies in most cases are manually identified. As a result, a large amount of effort and time is required during the comprehension process to establish the links between these artifacts. Although there are several methods that can infer such links based on different phenomenons, these methods usually produce different set of traceability links. This work expands upon previous traceability link recovery and visualization studies by implementing a combination of traceability recovery methods that automatically retrieve the links, and visualizing them to help developers to overview the links inferred by various recovery techniques, and also to select the right relations for analyses. The results of the usability study show that the visualization model presented herein can effectively support browsing, comprehension, and maintenance of Test-to Code Traceability (TCT) links in a system with enhanced efficiency, as well as visualization of TCT links from multiple sources is better than a visualization of single source of traceability links.Conference Object Citation Count: 2Autonomous Tuning for Constraint Programming via Artificial Bee Colony Optimization(Springer-verlag Berlin, 2015) Mısra, Sanjay; Crawford, Broderick; Mella, Felipe; Flores, Javier; Galleguillos, Cristian; Misra, Sanjay; Paredes, Fernando; Computer EngineeringConstraint Programming allows the resolution of complex problems, mainly combinatorial ones. These problems are defined by a set of variables that are subject to a domain of possible values and a set of constraints. The resolution of these problems is carried out by a constraint satisfaction solver which explores a search tree of potential solutions. This exploration is controlled by the enumeration strategy, which is responsible for choosing the order in which variables and values are selected to generate the potential solution. Autonomous Search provides the ability to the solver to self-tune its enumeration strategy in order to select the most appropriate one for each part of the search tree. This self-tuning process is commonly supported by an optimizer which attempts to maximize the quality of the search process, that is, to accelerate the resolution. In this work, we present a new optimizer for self-tuning in constraint programming based on artificial bee colonies. We report encouraging results where our autonomous tuning approach clearly improves the performance of the resolution process.Article Citation Count: 20Bug Severity Assessment in Cross Project Context and Identifying Training Candidates(World Scientific Publ Co Pte Ltd, 2017) Mısra, Sanjay; Misra, Sanjay; Sharma, Meera; Computer EngineeringThe automatic bug severity prediction will be useful in prioritising the development efforts, allocating resources and bug fixer. It needs historical data on which classifiers can be trained. In the absence of such historical data cross project prediction provides a good solution. In this paper, our objective is to automate the bug severity prediction by using a bug metric summary and to identify best training candidates in cross project context. The text mining technique has been used to extract the summary terms and trained the classifiers using these terms. About 63 training candidates have been designed by combining seven datasets of Eclipse projects to develop the severity prediction models. To deal with the imbalance bug data problem, we employed two approaches of ensemble by using two operators available in RapidMiner: Vote and Bagging. Results show that k-Nearest Neighbour (k-NN) performance is better than the Support Vector Machine (SVM) performance. Naive Bayes f-measure performance is poor, i.e. below 34.25%. In case of k-NN, developing training candidates by combining more than one training datasets helps in improving the performances (f-measure and accuracy). The two ensemble approaches have improved the f-measure performance up to 5% and 10% respectively for the severity levels having less number of bug reports in comparison of major severity level. We have further motivated the paper with a cross project bug severity prediction between Eclipse and Mozilla products. Results show that Mozilla products can be used to build reliable prediction models for Eclipse products and vice versa in case of SVM and k-NN classifiers.Article Citation Count: 37Career Abandonment Intentions among Software Workers(Wiley, 2014) Mısra, Sanjay; Casado-Lumbreras, Cristina; Misra, Sanjay; Soto-Acosta, Pedro; Computer EngineeringWithin the software development industry, human resources have been recognized as one of the most decisive and scarce resources. Today, the retention of skilled IT (information technology) personnel is a major issue for employers and recruiters as well, since IT career abandonment is a common practice and means not only the loss of personnel, knowledge, and skills, but also the loss of business opportunities. This article seeks to discover the main motivations young practitioners abandon the software career. To achieve this objective, two studies were conducted. The first study was qualitative (performed through semistructured interviews) and intended to discover the main variables affecting software career abandonment. The second study was quantitative, consisting of a Web-based survey developed from the output of the first study and administered to a sample of 148 IT practitioners. Results show that work-related, psychological, and emotional variable are the most relevant group of variables explaining IT career abandonment. More specifically, the three most important variables that motivate employees to abandon the career are effort-reward imbalance, perceived workload, and emotional exhaustion. In contrast, variables such as politics and infighting, uncool work, and insufficient resources influence to a lesser extent the decision to leave the career. (c) 2012 Wiley Periodicals, Inc.Conference Object Citation Count: 9A Case Study on Measuring the Size of Microservices(Springer international Publishing Ag, 2018) Koyuncu, Murat; Koyuncu, Murat; Mısra, Sanjay; Information Systems Engineering; Computer EngineeringIn cloud computing, the microservices has become the mostly used architectural style. However, there is still an ongoing debate about how big a microservice should be. In this case study, a monolith application is measured using Common Software Measurement International Consortium (COSMIC) Function Points. The same application is divided into pieces by following the Domain Driven Design (DDD) principles. The resulting cloud friendly microservices are measured again using COSMIC Function Points and the obtained results are compared.Article Citation Count: 78Cassava disease recognition from low-quality images using enhanced data augmentation model and deep learning(Wiley, 2021) Mısra, Sanjay; Damasevicius, Robertas; Misra, Sanjay; Maskeliunas, Rytis; Computer EngineeringImprovement of deep learning algorithms in smart agriculture is important to support the early detection of plant diseases, thereby improving crop yields. Data acquisition for machine learning applications is an expensive task due to the requirements of expert knowledge and professional equipment. The usability of any application in a real-world setting is often limited by unskilled users and the limitations of devices used for acquiring images for classification. We aim to improve the accuracy of deep learning models on low-quality test images using data augmentation techniques for neural network training. We generate synthetic images with a modified colour value distribution to expand the trainable image colour space and to train the neural network to recognize important colour-based features, which are less sensitive to the deficiencies of low-quality images such as those affected by blurring or motion. This paper introduces a novel image colour histogram transformation technique for generating synthetic images for data augmentation in image classification tasks. The approach is based on the convolution of the Chebyshev orthogonal functions with the probability distribution functions of image colour histograms. To validate our proposed model, we used four methods (resolution down-sampling, Gaussian blurring, motion blur, and overexposure) for reducing image quality from the Cassava leaf disease dataset. The results based on the modified MobileNetV2 neural network showed a statistically significant improvement of cassava leaf disease recognition accuracy on lower-quality testing images when compared with the baseline network. The model can be easily deployed for recognizing and detecting cassava leaf diseases in lower quality images, which is a major factor in practical data acquisition.Article Citation Count: 79Co-FAIS: Cooperative fuzzy artificial immune system for detecting intrusion in wireless sensor networks(Academic Press Ltd- Elsevier Science Ltd, 2014) Mısra, Sanjay; Anuar, Nor Badrul; Kiah, Miss Laiha Mat; Rohani, Vala Ali; Petkovic, Dalibor; Misra, Sanjay; Khan, Abdul Nasir; Computer EngineeringDue to the distributed nature of Denial-of-Service attacks, it is tremendously challenging to identify such malicious behavior using traditional intrusion detection systems in Wireless Sensor Networks (WSNs). In the current paper, a bio-inspired method is introduced, namely the cooperative-based fuzzy artificial immune system (Co-FATS). It is a modular-based defense strategy derived from the danger theory of the human immune system. The agents synchronize and work with one another to calculate the abnormality of sensor behavior in terms of context antigen value (CAV) or attackers and update the fuzzy activation threshold for security response. In such a multi-node circumstance, the sniffer module adapts to the sink node to audit data by analyzing the packet components and sending the log file to the next layer. The fuzzy misuse detector module (FMDM) integrates with a danger detector module to identify the sources of danger signals. The infected sources are transmitted to the fuzzy Q-learning vaccination modules (FQVM) in order for particular, required action to enhance system abilities. The Cooperative Decision Making Modules (Co-DMM) incorporates danger detector module with the fuzzy Q-learning vaccination module to produce optimum defense strategies. To evaluate the performance of the proposed model, the Low Energy Adaptive Clustering Hierarchy (LEACH) was simulated using a network simulator. The model was subsequently compared against other existing soft computing methods, such as fuzzy logic controller (FLC), artificial immune system (AIS), and fuzzy Q-learning (FQL), in terms of detection accuracy, counter-defense, network lifetime and energy consumption, to demonstrate its efficiency and viability. The proposed method improves detection accuracy and successful defense rate performance against attacks compared to conventional empirical methods. (C) 2014 Elsevier Ltd. All rights reserved.Article Citation Count: 126Co-LSTM: Convolutional LSTM model for sentiment analysis in social big data(Elsevier Sci Ltd, 2021) Mısra, Sanjay; Jena, Monalisa; Rath, Santanu Kumar; Misra, Sanjay; Computer EngineeringAnalysis of consumer reviews posted on social media is found to be essential for several business applications. Consumer reviews posted in social media are increasing at an exponential rate both in terms of number and relevance, which leads to big data. In this paper, a hybrid approach of two deep learning architectures namely Convolutional Neural Network (CNN) and Long Short Term Memory (LSTM) (RNN with memory) is suggested for sentiment classification of reviews posted at diverse domains. Deep convolutional networks have been highly effective in local feature selection, while recurrent networks (LSTM) often yield good results in the sequential analysis of a long text. The proposed Co-LSTM model is mainly aimed at two objectives in sentiment analysis. First, it is highly adaptable in examining big social data, keeping scalability in mind, and secondly, unlike the conventional machine learning approaches, it is free from any particular domain. The experiment has been carried out on four review datasets from diverse domains to train the model which can handle all kinds of dependencies that usually arises in a post. The experimental results show that the proposed ensemble model outperforms other machine learning approaches in terms of accuracy and other parameters.Article Citation Count: 6COBOL Systems Migration to SOA: Assessing Antipatterns and Complexity(Kaunas Univ Technology, 2019) Mısra, Sanjay; Zunino, Alejandro; Flores, Andres; Misra, Sanjay; Computer EngineeringSOA and Web Services allow users to easily expose business functions to build larger distributed systems. However, legacy systems - mostly in COBOL - are left aside unless applying a migration approach. The main approaches are direct and indirect migration. The former implies wrapping COBOL programs with a thin layer of a Web Service oriented language/platform. The latter needs reengineering COBOL functions to a modern language/platform. In our previous work, we presented an intermediate approach based on direct migration where developed Web Services are later refactored to improve the quality of their interfaces. Refactorings mainly capture good practices inherent to indirect migration. For this, antipatterns for WSDL documents (common bad practices) are detected to prevent issues related to WSDLs understanding and discoverability. In this paper, we assess antipatterns of Web Services' WSDL documents generated upon the three migration approaches. In addition, generated Web Services' interfaces are measured in complexity to attend both comprehension and interoperability. We apply a metric suite (by Baski & Misra) to measure complexity on services interfaces - i.e., WSDL documents. Migrations of two real COBOL systems upon the three approaches were assessed on antipatterns evidences and the complexity level of the generated SOA frontiers - a total of 431 WSDL documents.Article Citation Count: 1A Cognitive Model for Meetings in the Software Development Process(Wiley, 2014) Akman, Kamil İbrahim; Akman, Ibrahim; Mısra, Sanjay; Computer EngineeringMeetings are at the heart of the software development process (SDP) and can be of different types. The present article first proposes an abstract cognitive model for meetings, which represents how different types of meetings are affected by cognitive activities at different stages within the SDP. Second, and based on the analysis of meetings at different stages of SDP, it proposes the removal of such meetings from some of the stages within the program by using a cognitive evaluation model for meetings and their replacement, instead, with information and communication technology tools and techniques by means of a cognitive evaluation model. The abstract cognitive model and the evaluation model are validated empirically through experimentation, carried out through a detailed analysis of a target group composed of information technology professionals. (c) 2011 Wiley Periodicals, Inc.Conference Object Citation Count: 14Cognitive program complexity measure(Ieee Computer Soc, 2007) Mısra, Sanjay; Computer EngineeringIn cognitive informatics, the functional complexity of software depends on three factors: internal architecture, input, and output. In the earlier proposed metrics based on cognitive informatics, these above factors are not fully considered. This paper proposes an improved cognitive complexity measure. Accordingly, new formula is developed to calculate the cognitive complexity. An attempt has also been made to evaluate and validate the proposed measure through Weyuker's properties and a practical framework It has been found that seven of nine Weyuker's properties have been satisfied by the proposed cognitive complexity measure. It also satisfies most of the parameters required by the practical framework hence establishes as a well-structured one. Finally, a comparative study with similar measures has been made to prove its robustness.Article Citation Count: 2A Complexity Metrics Suite for Cascading Style Sheets(Mdpi, 2019) Mısra, Sanjay; Misra, Sanjay; Damasevicius, Robertas; Computer EngineeringWe perform a theoretical and empirical analysis of a set of Cascading Style Sheets (CSS) document complexity metrics. The metrics are validated using a practical framework that demonstrates their viability. The theoretical analysis is performed using the Weyuker's properties-a widely adopted approach to conducting empirical validations of metrics proposals. The empirical analysis is conducted using visual and statistical analysis of distribution of metric values, Cliff's delta, Chi-square and Liliefors statistical normality tests, and correlation analysis on our own dataset of CSS documents. The results show that five out of the nine metrics (56%) satisfy Weyuker's properties except for the Number of Attributes Defined per Rule Block (NADRB) metric, which satisfies six out of nine (67%) properties. In addition, the results from the statistical analysis show good statistical distribution characteristics (only the Number of Extended Rule Blocks (NERB) metric exceeds the rule-of-thumb threshold value of the Cliff's delta). The correlation between the metric values and the size of the CSS documents is insignificant, suggesting that the presented metrics are indeed complexity rather than size metrics. The practical application of the presented CSS complexity metric suite is to assess the risk of CSS documents. The proposed CSS complexity metrics suite allows identification of CSS files that require immediate attention of software maintenance personnel.