Comprehensive Testing Tool for Automatic Test Suite Generation, Prioritizatio...CSCJournals
Testing has been an essential part of software development life cycle. Automatic test case and test data generation has attracted many researchers in the recent past. Test suite generation is the concept given importance which considers multiple objectives in mind and ensures core coverage. The test cases thus generated can have dependencies such as open dependencies and closed dependencies. When there are dependencies, it is obvious that the order of execution of test cases can have impact on the percentage of flaws detected in the software under test. Therefore test case prioritization is another important research area that complements automatic test suite generation in objects oriented systems. Prior researches on test case prioritization focused on dependency structures. However, in this paper, we automate the extraction of dependency structures. We proposed a methodology that takes care of automatic test suite generation and test case prioritization for effective testing of object oriented software. We built a tool to demonstrate the proof of concept. The empirical study with 20 case studies revealed that the proposed tool and underlying methods can have significant impact on the software industry and associated clientele.
CRYPTANALYSIS AND FURTHER IMPROVEMENT OF A BIOMETRIC-BASED REMOTE USER AUTHEN...IJNSA Journal
Recently, Li et al. proposed a secure biometric-based remote user authentication scheme using smart cards to withstand the security flaws of Li-Hwang’s efficient biometric-based remote user authentication scheme using smart cards. Li et al.’s scheme is based on biometrics verification, smart card and one-way hash function, and it also uses the random nonce rather than a synchronized clock, and thus it is efficient in computational cost and more secure than Li-Hwang’s scheme. Unfortunately, in this paper we show that Li et al.’s scheme still has some security weaknesses in their design. In order to withstand those weaknesses in their scheme, we further propose an improvement of their scheme so that the improved scheme always provides proper authentication and as a result, it establishes a session key between the user and the server at the end of successful user authentication.
Comprehensive Testing Tool for Automatic Test Suite Generation, Prioritizatio...CSCJournals
Testing has been an essential part of software development life cycle. Automatic test case and test data generation has attracted many researchers in the recent past. Test suite generation is the concept given importance which considers multiple objectives in mind and ensures core coverage. The test cases thus generated can have dependencies such as open dependencies and closed dependencies. When there are dependencies, it is obvious that the order of execution of test cases can have impact on the percentage of flaws detected in the software under test. Therefore test case prioritization is another important research area that complements automatic test suite generation in objects oriented systems. Prior researches on test case prioritization focused on dependency structures. However, in this paper, we automate the extraction of dependency structures. We proposed a methodology that takes care of automatic test suite generation and test case prioritization for effective testing of object oriented software. We built a tool to demonstrate the proof of concept. The empirical study with 20 case studies revealed that the proposed tool and underlying methods can have significant impact on the software industry and associated clientele.
CRYPTANALYSIS AND FURTHER IMPROVEMENT OF A BIOMETRIC-BASED REMOTE USER AUTHEN...IJNSA Journal
Recently, Li et al. proposed a secure biometric-based remote user authentication scheme using smart cards to withstand the security flaws of Li-Hwang’s efficient biometric-based remote user authentication scheme using smart cards. Li et al.’s scheme is based on biometrics verification, smart card and one-way hash function, and it also uses the random nonce rather than a synchronized clock, and thus it is efficient in computational cost and more secure than Li-Hwang’s scheme. Unfortunately, in this paper we show that Li et al.’s scheme still has some security weaknesses in their design. In order to withstand those weaknesses in their scheme, we further propose an improvement of their scheme so that the improved scheme always provides proper authentication and as a result, it establishes a session key between the user and the server at the end of successful user authentication.
Survey of network anomaly detection using markov chainijcseit
Recently an internet threat has been increased. Our motive is detect the intrusion in the network in concise.
The real time issue such as DoS attack in banking, companies, industries and organization have been
increased significantly IDS has been used in both server and host side. The major challenge is to effectively
predict the periods of threats and protect the server from the unauthorized user. In this study, a novel
probabilistic approach is proposed effectively to detect the network intrusions. It uses a Markov chain for
probabilistic modelling of abnormal events in network systems. The degree of abnormality of the incoming
data is performed on the basis of the network states.
J48 and JRIP Rules for E-Governance DataCSCJournals
Data are any facts, numbers, or text that can be processed by a computer. Data Mining is an analytic process which designed to explore data usually large amounts of data. Data Mining is often considered to be \"a blend of statistics. In this paper we have used two data mining techniques for discovering classification rules and generating a decision tree. These techniques are J48 and JRIP. Data mining tools WEKA is used in this paper.
Evaluation of network intrusion detection using markov chainIJCI JOURNAL
Day today life internet threat has been increased significantly. There is a need to develop model in order to
maintain security of system. The most effective techniques are Intrusion Detection System (IDS).The
purpose of intrusion system through the security devices detect and deal with it. In this paper, a
mathematical approach is used effectively to predict and detect intrusion in the network. Here we discuss
about two algorithms ‘K-Means + Apriori’, a method which classify normal and abnormal activities in
computer network. In K-Means process, it partitions the training set into K-clusters using Euclidean
distance and introduce an outlier factor, then it build Apriori Algorithm to prune the data by removing
infrequent data in the database. Based on defined state the degree of incoming data is evaluated through
the experiment using sample DARPA2000 dataset, and achieves high detection performance in level of
attack in stages.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
This template was created for DSCE, Aeronautical students. You have to replace the institution details.
Create a separate document for each chapter, so that under numbering, you can change the sequence of chapter main heading according to chapter wise. i.e., 2.1, 2.2 etc.
Same procedure is applicable to Figure caption and Table caption.
This template can be used to generate, BE seminar report, M.Tech and Ph.D thesis also.
This template is created to assist UG students in generating their thesis without much hassle.
Contents are taken from VTU website. I don’t hold any copyright for this document.
Hareesha N G
Assistant Professor
DSCE, Bengaluru
this is VTU FINAL YEAR PROJECT REPORT full report is attached below.this alone with front pages attached Front pages report follows all the guidelines specified by vtu according to our college.
Development of software defect prediction system using artificial neural networkIJAAS Team
Software testing is an activity to enable a system is bug free during execution process. The software bug prediction is one of the most encouraging exercises of the testing phase of the software improvement life cycle. In any case, in this paper, a framework was created to anticipate the modules that deformity inclined in order to be utilized to all the more likely organize software quality affirmation exertion. Genetic Algorithm was used to extract relevant features from the acquired datasets to eliminate the possibility of overfitting and the relevant features were classified to defective or otherwise modules using the Artificial Neural Network. The system was executed in MATLAB (R2018a) Runtime environment utilizing a statistical toolkit and the performance of the system was assessed dependent on the accuracy, precision, recall, and the f-score to check the effectiveness of the system. In the finish of the led explores, the outcome indicated that ECLIPSE JDT CORE, ECLIPSE PDE UI, EQUINOX FRAMEWORK and LUCENE has the accuracy, precision, recall and the f-score of 86.93, 53.49, 79.31 and 63.89% respectively, 83.28, 31.91, 45.45 and 37.50% respectively, 83.43, 57.69, 45.45 and 50.84% respectively and 91.30, 33.33, 50.00 and 40.00% respectively. This paper presents an improved software predictive system for the software defect detections.
ANALYSIS OF MACHINE LEARNING ALGORITHMS WITH FEATURE SELECTION FOR INTRUSION ...IJNSA Journal
In recent times, various machine learning classifiers are used to improve network intrusion detection. The researchers have proposed many solutions for intrusion detection in the literature. The machine learning classifiers are trained on older datasets for intrusion detection, which limits their detection accuracy. So, there is a need to train the machine learning classifiers on the latest dataset. In this paper, UNSW-NB15, the latest dataset is used to train machine learning classifiers. The selected classifiers such as K-Nearest Neighbors (KNN), Stochastic Gradient Descent (SGD), Random Forest (RF), Logistic Regression (LR), and Naïve Bayes (NB) classifiers are used for training from the taxonomy of classifiers based on lazy and eager learners. In this paper, Chi-Square, a filter-based feature selection technique, is applied to the UNSW-NB15 dataset to reduce the irrelevant and redundant features. The performance of classifiers is measured in terms of Accuracy, Mean Squared Error (MSE), Precision, Recall, F1-Score, True Positive Rate (TPR) and False Positive Rate (FPR) with or without feature selection technique and comparative analysis of these machine learning classifiers is carried out.
Tích cóp được tiền để mua nhà đã là chuyện khó. Dùng số tiền đó để mua ngôi nhà sao cho xứng đáng với công sức tiết kiệm lâu nay, chuyện tưởng chừng như đơn giản nhưng không phải như vậy, nhất là với những người lần đầu xúc tiến chuyện mua nhà. Chúng tôi sẽ đem đến cho bạn những lựa chọn căn hộ bạn mong muốn, truy cập đến chúng tôi để chúng tôi giúp bạn http://anphongland.vn/
Ethical Competency is the importance of a fair and transparent approach in everything it does by adopting the highest standards of professionalism, honesty, integrity and ethical behavior in all its business processes and transactions.
Survey of network anomaly detection using markov chainijcseit
Recently an internet threat has been increased. Our motive is detect the intrusion in the network in concise.
The real time issue such as DoS attack in banking, companies, industries and organization have been
increased significantly IDS has been used in both server and host side. The major challenge is to effectively
predict the periods of threats and protect the server from the unauthorized user. In this study, a novel
probabilistic approach is proposed effectively to detect the network intrusions. It uses a Markov chain for
probabilistic modelling of abnormal events in network systems. The degree of abnormality of the incoming
data is performed on the basis of the network states.
J48 and JRIP Rules for E-Governance DataCSCJournals
Data are any facts, numbers, or text that can be processed by a computer. Data Mining is an analytic process which designed to explore data usually large amounts of data. Data Mining is often considered to be \"a blend of statistics. In this paper we have used two data mining techniques for discovering classification rules and generating a decision tree. These techniques are J48 and JRIP. Data mining tools WEKA is used in this paper.
Evaluation of network intrusion detection using markov chainIJCI JOURNAL
Day today life internet threat has been increased significantly. There is a need to develop model in order to
maintain security of system. The most effective techniques are Intrusion Detection System (IDS).The
purpose of intrusion system through the security devices detect and deal with it. In this paper, a
mathematical approach is used effectively to predict and detect intrusion in the network. Here we discuss
about two algorithms ‘K-Means + Apriori’, a method which classify normal and abnormal activities in
computer network. In K-Means process, it partitions the training set into K-clusters using Euclidean
distance and introduce an outlier factor, then it build Apriori Algorithm to prune the data by removing
infrequent data in the database. Based on defined state the degree of incoming data is evaluated through
the experiment using sample DARPA2000 dataset, and achieves high detection performance in level of
attack in stages.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
This template was created for DSCE, Aeronautical students. You have to replace the institution details.
Create a separate document for each chapter, so that under numbering, you can change the sequence of chapter main heading according to chapter wise. i.e., 2.1, 2.2 etc.
Same procedure is applicable to Figure caption and Table caption.
This template can be used to generate, BE seminar report, M.Tech and Ph.D thesis also.
This template is created to assist UG students in generating their thesis without much hassle.
Contents are taken from VTU website. I don’t hold any copyright for this document.
Hareesha N G
Assistant Professor
DSCE, Bengaluru
this is VTU FINAL YEAR PROJECT REPORT full report is attached below.this alone with front pages attached Front pages report follows all the guidelines specified by vtu according to our college.
Development of software defect prediction system using artificial neural networkIJAAS Team
Software testing is an activity to enable a system is bug free during execution process. The software bug prediction is one of the most encouraging exercises of the testing phase of the software improvement life cycle. In any case, in this paper, a framework was created to anticipate the modules that deformity inclined in order to be utilized to all the more likely organize software quality affirmation exertion. Genetic Algorithm was used to extract relevant features from the acquired datasets to eliminate the possibility of overfitting and the relevant features were classified to defective or otherwise modules using the Artificial Neural Network. The system was executed in MATLAB (R2018a) Runtime environment utilizing a statistical toolkit and the performance of the system was assessed dependent on the accuracy, precision, recall, and the f-score to check the effectiveness of the system. In the finish of the led explores, the outcome indicated that ECLIPSE JDT CORE, ECLIPSE PDE UI, EQUINOX FRAMEWORK and LUCENE has the accuracy, precision, recall and the f-score of 86.93, 53.49, 79.31 and 63.89% respectively, 83.28, 31.91, 45.45 and 37.50% respectively, 83.43, 57.69, 45.45 and 50.84% respectively and 91.30, 33.33, 50.00 and 40.00% respectively. This paper presents an improved software predictive system for the software defect detections.
ANALYSIS OF MACHINE LEARNING ALGORITHMS WITH FEATURE SELECTION FOR INTRUSION ...IJNSA Journal
In recent times, various machine learning classifiers are used to improve network intrusion detection. The researchers have proposed many solutions for intrusion detection in the literature. The machine learning classifiers are trained on older datasets for intrusion detection, which limits their detection accuracy. So, there is a need to train the machine learning classifiers on the latest dataset. In this paper, UNSW-NB15, the latest dataset is used to train machine learning classifiers. The selected classifiers such as K-Nearest Neighbors (KNN), Stochastic Gradient Descent (SGD), Random Forest (RF), Logistic Regression (LR), and Naïve Bayes (NB) classifiers are used for training from the taxonomy of classifiers based on lazy and eager learners. In this paper, Chi-Square, a filter-based feature selection technique, is applied to the UNSW-NB15 dataset to reduce the irrelevant and redundant features. The performance of classifiers is measured in terms of Accuracy, Mean Squared Error (MSE), Precision, Recall, F1-Score, True Positive Rate (TPR) and False Positive Rate (FPR) with or without feature selection technique and comparative analysis of these machine learning classifiers is carried out.
Tích cóp được tiền để mua nhà đã là chuyện khó. Dùng số tiền đó để mua ngôi nhà sao cho xứng đáng với công sức tiết kiệm lâu nay, chuyện tưởng chừng như đơn giản nhưng không phải như vậy, nhất là với những người lần đầu xúc tiến chuyện mua nhà. Chúng tôi sẽ đem đến cho bạn những lựa chọn căn hộ bạn mong muốn, truy cập đến chúng tôi để chúng tôi giúp bạn http://anphongland.vn/
Ethical Competency is the importance of a fair and transparent approach in everything it does by adopting the highest standards of professionalism, honesty, integrity and ethical behavior in all its business processes and transactions.
Làm giàu từ bất động sản không khó, chỉ cần bạn có "đất rẻ" để biến thành "đất vàng". Anphongland sẽ đem đến cho bạn nhiều lựa chọn để bạn có thể biến nó thành "đất vàng"
How do we differentiate Urban Outfitters from its main competitors? -By teaming up with Airbnb to design experiences that customers feel are personal and authentic.
This is a BSc final Project book on Student portal system application which is mobile based on android application. it will help students to write the project book in a proper way.
The object of our project is acquisition of Electro cardiogram signal from patient‟s body through wearable system, analyze whether it is normal or abnormal at patient‟s end, then transmit the wireless signal if found that it is abnormal. Transmission is to be done wirelessly through XBEE Technology and then higher level analysis is to be done on computer which is situated at base -station. To achieve our objective we have used microcontroller AT Mega 32 and for its programming we have used dynamic C with AVR Studio base. For higher level analysis we have made software using Java J2EE, Java Script and PHP
Call for Papers- Special Session: Applications of Computational Intelligence, Internet of Things and Cutting Edge Technologies
Christo Ananth, Dr.Akhatov Akmal Rustamovich, Dr.Muhtor Nasirov
Professor, Samarkand State University, Uzbekistan
Call for Papers- Special Issue: Applications of Artificial Intelligence and I...Christo Ananth
Call for Papers- Special Issue: Applications of Artificial Intelligence and Internet of Things in Process Control, International Journal of Electrical and Electronic Research (IJEER), Forex Publications, Scopus
Self-admitted technical debt classification using natural language processing...IJECEIAES
Recent studies show that it is possible to detect technical dept automatically from source code comments intentionally created by developers, a phenomenon known as self-admitted technical debt. This study proposes a system by which a comment or commit is classified as one of five dept types, namely, requirement, design, defect, test, and documentation. In addition to the traditional term frequency-inverse document frequency (TF-IDF), several word embeddings methods produced by different pre-trained language models were used for feature extraction, such as Word2Vec, GolVe, bidirectional encoder representations from transformers (BERT), and FastText. The generated features were used to train a set of classifiers including naive Bayes (NB), random forest (RF), support vector machines (SVM), and two configurations of convolutional neural network (CNN). Two datasets were used to train and test the proposed systems. Our collected dataset (A-dataset) includes a total of 1,513 comments and commits manually labeled. Additionally, a dataset, consisting of 4,071 labeled comments, used in previous studies (M-dataset) was also used in this study. The RF classifier achieved an accuracy of 0.822 with A-dataset and 0.820 with the M-dataset. CNN with A-dataset achieved an accuracy of 0.838 using BERT features. With M-dataset, the CNN achieves an accuracy of 0.809 and 0.812 with BERT and Word2Vec, respectively.