Browsing by Author "Mishra, Alok"
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Item A COMPARATIVE STUDY OF CYBER SECURITY POLICIES(2017-06-02) Bderi,Haithem ABD Esharf; Mishra, AlokThe cyberspace is expanding faster than ever and with it cyber threats are also increasing making it imperative to have a strong cyber-security policy. Cyber-attacks don‘t only affect individual users and organization but can also cause national security issues. The different policies of different countries make it possible for hackers and intruders to carry cyber-attack while making it impossible for authorities to trace back offenders. It is important to develop a comprehensive Cyber-security policy to address all kinds of cyber threats so that every offender can be traced back and penalized accordingly. This research work examines and compares different attributes of cyber-security policies of selected countries. This research work identifies some important attributes which can help to develop an all-inclusive cyber security policy.Item A COMPARATIVE STUDY OF E-GOVERNMENT EVOLUTION IN AFRICA(2022-03-01) El-Asheibi, Nagat; Mishra, AlokStates are constantly striving to improve their services to their citizens, trying to reach them through the Internet in order to be able to explain their policies and be effective. The delivery of public information and services to citizens through the Internet channel is considered e-government. The e-government uses information technology to serve citizens, businesses and institutions. There are various factors that affect e-government. In general, researchers have examined e-government studies that have been put into practice by various African countries. The purpose of this study is to explore the possibilities offered by e-Government in Africa by documenting few initiatives on the continent that have developed innovative models that contribute to governments through the implementation. To achieve the aim of the thesis, we present former works and e-government evolution in Africa with discussion on the evolution of e-government in different African countries (Libya, Egypt, Botswana, Sudan, South Africa, Nigeria, Gambia, Ghana, Uganda, Kenya, and Mauritius).Item A COMPARATIVE STUDY OF PRIVACY-PRESERVING TECHNIQUES FOR THE CLOUD STORAGE(2022-01-20) Al-Qaisi, Thr; Mishra, AlokInformation and data privacy have become critical concepts in the cloud computing industry, especially as internet users seek to use the cloud environment to store their personal and sensitive data. Many cloud service providers currently offer premium and quality-based services for their users as the first initiative for building a vast cloud community. However, security and privacy violations began to emerge and evolve in the cyber world and threaten most of its infrastructure. Fortunately, much research has been achieved to develop the proper techniques to overcome data privacy's perilous challenges and find better methodologies for protecting cloud storage contents. In this work, our study focuses on comparing several forms of privacy-preserving techniques for cloud storage. The study includes a comprehensive analysis of privacy-preserving techniques and their common attributes for the aim of designing flexible, secure, and efficient solutions for the dilemma that faces data privacy. We also present an attainable solution for privacy-preserving of the cloud storage by proposing a multi layer encryption framework with the use of one-time password authentication technology and a multi-cloud storage structure.Item ASTUDY ON INTEGRATION OF AGILE WITH STRUCTURED SOFTWARE DEVELOPMENT PROCESSES(2017-01-07) Nura, Abdelmagid; Mishra, AlokNowadays, Agile methodologies (AMs) have interred SDLC in all companies. Many organizations have used AMs and traditional methods to enhance öethodologies as an optimal solution in the business area. First, thinks about changes during SDLC; also customer may change his mind. So here is a need for the combination methodologies. Second, in spite of the fact that AMs can be beneficial to organizations, there is a need for traditional methodologies in some phases of the SDLC as a mixed framework.Item DEEP LEARNING APPLICATIONS IN SEIZURE DETECTION(2022-02-24) Kadhim, Yezi Ali; Mishra, Alok; Garg, LalitIn this thesis, a new method is proposed based on deep auto encoder and power spectral density. First, the input data is analyzed using power spectral density for feature extraction by measuring the power spectral density of the signal for each row of data. The produced output becomes input to the first Auto encoder to reduce the dimension and extracted high level features. The output of first auto-encoder become input to the second auto-encoder also to reduce number of features and extracted high level features. In addition, these features are classified into two groups: normal and abnormal by using SoftMax classifier. Finally, the two auto-encoders and SoftMax stacked and trained by using backpropagation algorithm to improve the classification accuracy. The proposed method gives satisfactory results when compared with the common methods presented in this filed .Here, the number of Auto encoders depend on the behavior of the data as well as the dimension. The proposed method is tested with commonly used datasets in the epilepsy serius detection, and the results obtained are compared with other and most prominent works in this field in order to determine the strengths and weaknesses.Item FACTORS IN AGILE METHODS ADOPTION IN SMALL AND MEDIUM ENTERPRISES(2022-02-25) Abdalhamid, Samia; Mishra, Alok; Mishra, DeeptiRecently, agile methods have become more popular in the software development industry, but adopting Agile methods by software development organizations can be an easy process or a hard one depending on certain factors. So to make the process of adopting the Agile method successfully, there are some factors that can help organizations to adopt agile without fear of failure. There is not enough research in terms of adopting Agile in SMEs in particular. For this reason, we studied the factors of adopting Agile methods in small and medium software development organization to provide guidelines for success and failure factors. In this research, the use of agile methods is explored in small- and medium-scale software. Based on rigorous literature review number of models and hypotheses were developed and examined by data collected from 52 software organizations from 7 countries based on comprehensive questionnaire. As results some significant success factors were identified such as : Assigning essential features first. Frequent delivery of software, and the use of tools. In terms of failure factors, the most significant factor that can cause failure is too-large size of an organization.Item OBSERVATIONS ON EVOLUTION OF LEAN SOFTWARE DEVELOPMENT(2017-01-04) FARAJ, LLAHM OMAR; Mishra, Alok; Yazıcı, AliThis thesis reviews the observaitons on evolution of lean software development (LSD) and introduces Lena Method in detail. An observaiton on evalution of Lean Spftware development is presented and the method involving experimental authors who described the methodology in many phases. LSD is one of the powerful, agile software development (ASD). The objective of LSD is to create customer value and deliver fast within budget. LSD can improve business domain by adopting Lps according to the business need.Item STUDY OF WORD EMBEDDING RULES AND MACHINE LEARNING BASED TEXT CLASSIFICATION(2022-01-26) AUBAID, Asmaa; Mishra, Alok; GÖRÜR, AbdülkadirWith the growth of online information and the sudden growth in the number of electronic documents provided on the Web and in digital libraries, there is difficulty in categorizing text documents. Therefore, embedding, rule-based and machine learning approaches are the best solutions to this problem as the rule-based approach is considered to be one of the most flexible methods by which the black box of the process of the text classification technique can be shown. The details of a process of classification can be seen and it can add some tools or new instructions to obtain good results. This approach has high value for information retrieval, e-governments, information filtering, text databases, digital libraries, and other applications. The problem of the embedding technique and generating rule-based is very significant for text categorization. The general idea of any embedding technique is to determine the importance of keywords using a technique that can keep informative words and remove non-informative words, which can then help the text-categorization engine to categorize a document into a category. This thesis deals with the rule-based approach using the embedding technique for the word to vector (word2vec) and document to vector (doc2vec) approaches. It will use these two techniques to prepare keywords depending on the computation of similarity. After that, we use those keywords to apply the rule-based approach for a classifier to achieve to the best performance of the system by computing performance evaluation measures such as accuracy, recall, precision, and F-Measures. Experiments were performed on the Reuter 21578 and 20 Newsgroups datasets to classify the top ten categories of Reuter 21578 and 20 Newsgroups datasets. The Python language was used to create a rule-based approach followed by the overall effectiveness of the approach being measured with the F-Measure score, error rate, and accuracy. The results of rule-based with the embedding technique using the doc2vec model (d2vRule) in the case of the Reuter 21578 dataset were 79% precision, 75% recall, 76.75% F-Measures, 9.28% error rate and 90.72% accuracy measurements. For the 20 Newsgroups dataset, the results were 76% precision, 66.64% recall, 70.98% F-Measures, 9.93% error rate and 90.07% accuracy measurement. In addition, when the machine learning algorithms J-RIPPER (JRip), One Rule (OneR) and ZeroR were applied to the Reuter 21578 dataset, we obtained F-Measures and accuracy metrics of 0.713 − 0.752, 0.506 − 0.598 and 0.219 − 0.39 for JRip, One R and ZeroR, respectively. In addition, when applying those algorithms to our dataset, there was agreement and it appeared that our algorithm (d2vRule) performed better than these three algorithms mentioned above. Moreover, it provides a good classification process according to the evaluation metrics. On the other hand, when using the embedding technique with the word2vec model, it is predictable that these results depended on precision, recall and F-Measures approaches. Finally, it is clear that our rule-based approach is better than the results of machine learning, namely Naïve Bayes, Naive Bayes Updateable, Rules.DecisionTable, Lazy. IBL and Lazy.IBK. When it is validated for our rule-based (w2vRule), it can be seen that the rule-based (RB) classifier of a certain reference has the highest accuracy with 82.19% of correctly classified instances, while Decision Tree (DT), Support Vector Machine (SVM), Random Forest (RF), and Bayes Net (BN) have accuracies of 81.72%, 81.49%, 81.19%, and 77.85%, respectively, and the Temporal Specificity Score (TSS) classifier correctly classified 77.19% of instances referenced. However, our word-to-vector rule-based classifier (w2vRule) has an observed level of measurements in the case of the Reuter 21578 dataset were 73% precision, 77.71% recall, 75.09% F-Measures, 10.09% error rate and 89.91% accuracy. Therefore, it achieved the best result when we compared it with previous rule-based and machine learning classifiers.Item TOWARDS A UNIFIED AGENT ORIENTED SOFTWARE ENGINEERING METHODOLOGY(2022-02-21) Abdalla, Reem; Mishra, AlokThe computer science and software engineering society have become one of the most progressive and significant domains within science as they have managed to stand firmly in the information technology since the 1990s. Throughout recent years agent technologies have been promoted rapidly and a rising number of processes, frameworks, and notions recommended in related scientific research. In turn, agent technology has many implementations and uses in problem-solving in a variety of areas, including shopping simulations, surveillance, system diagnosis, and remedial procedures. Over the last years, in particular, there has been an increasing number of agent approaches proposed along with an ever-growing interest in their various implementations. These approaches are evolutionary and specifically designed for agents and their particular properties. Yet, a comprehensive and full fledged agent approach for developing related projects is still absent despite the presence of numerous agent-oriented methodologies. One of the moves towards compensating for this issue is to compile the models of various available methodologies, ones that are comparable to the evolution of the Unified Modeling Language in the domain of object-oriented analysis and design. As these to have become defacto standards in software development. In line with this purpose, the present thesis attempts to comprehend the relationship among seven main agent-oriented methodologies. More specifically, we intend to assess and compare these seven approaches by conducting a feature analysis through examining the advantages and disadvantages of each competing process, structural analysis, a case study, and meta-model evaluation methods. This effort is made to address the important characteristics of agent approaches. Since the main objective of this thesis is to take a step forward in forming a unified agent-oriented software engineering methodology, we will include the positive features and avoid the undesired ones within seven distinguished agent methodologies.