This paper presented the main information, security problems and threats in open multi-agent distributed
e-learning information systems and Proposed various approaches to solve information security attacks in
virtual learning environment using service oriented architecture which based on multi-agent information
systems architecture, the solution on the multi-agent learning information system implementation based on
the implementation of two types of systems the first system with the centralized mobile agent information
security management and the second system with decentralized mobile agents security management, and
proposed the migration behavior simulation for their active software components (software agents) .
Information and communication Technology is a gateway through which large population of students has been addressed. Mobile learning technology the latest arrival highly changing the way the students learn, interact, access up to data information. It mainly satisfies the current and future generation which needs information at the earliest rather than later few touches. The World Wide Web acts as an interface in E- learning as well as in mobile learning (M-learning) environments. It supports and facilitates the delivery of teaching and learning materials. M-learning provides quality educational content with the help of semantic web technologies like Ontology. This study presents Mobile Learning framework for making efficient learning with a case study on cyber security.
A novel secure e contents system for multi-media interchange workflows in e-l...IJCNCJournal
Ā
The goal of e-learning is to benefit from the capabilities offered by new information technology (such as
remote digital communications, multimedia, internet, cell phones, teleconferences, etc.) and to enhance the
security of several government organizations so as to take into considerations almost all the contents of elearning
such as: information content, covering most of citizens or state firms or corporations queries.
Content provides a service to provide most if not all basic and business services; content of communicative
link provides the citizen and the state agencies together all the time and provides content security for all
workers on this network to work in securely environment. Access to information as well is safeguarded. The
main objective of this research is to build a novel multi-media security system (encrypting / decrypting
system) that will enable E-learning to exchange more secured multi-media data/information.
AN ADAPTIVE AND INTELLIGENT TUTOR BY EXPERT SYSTEMS FOR MOBILE DEVICESijmpict
Ā
Mobile Learning (M-Learning) is an emerging discipline in the area of education and educational technology. So researchers are trying to optimize and expanding its application in the field of education. The aim of this paper is to investigate the role of mobile devices and expert systems in disseminating and supporting the knowledge gained by intelligent tutors and to propose a system based on integration of intelligent M-Learning with expert systems. It acts as an intelligent tutor which can perform three processes - pre-test, learning concept and post-test - according to characteristic of the learner. The proposed system can improves the education efficiency highly as well as decreases costs. As a result, every time and everywhere (ETEW) simple and cheap learning would be provided via SMS, MMS and so on in this system. The global intention of M-Learning is to make learning āa way of beingā.
A SURVEY ON TECHNIQUES REQUIREMENTS FOR INTEGRATEING SAFETY AND SECURITY ENGI...IJCSES Journal
Ā
Nowadays, safety and security have become a requirement, integrated to each other, for information systems as a new generation of infrastructure systems distributed throughout networks. That opened the door for questions on whether these systems are safety-critical especially since they were tested in a closed, separated environment and are now deployed in an uncontrollable environment, namely the internet, where the number of threats is enormous. So it opened the door to talk about new development approach methods that take safety and security into consideration during the system development life cycle and most importantly, identifying hazard, risks and threats. We will conduct a survey exploring technical languages that were created by the scholars to combine safety and security requirement engineering and accident analysis technique languages.
Information and communication Technology is a gateway through which large population of students has been addressed. Mobile learning technology the latest arrival highly changing the way the students learn, interact, access up to data information. It mainly satisfies the current and future generation which needs information at the earliest rather than later few touches. The World Wide Web acts as an interface in E- learning as well as in mobile learning (M-learning) environments. It supports and facilitates the delivery of teaching and learning materials. M-learning provides quality educational content with the help of semantic web technologies like Ontology. This study presents Mobile Learning framework for making efficient learning with a case study on cyber security.
A novel secure e contents system for multi-media interchange workflows in e-l...IJCNCJournal
Ā
The goal of e-learning is to benefit from the capabilities offered by new information technology (such as
remote digital communications, multimedia, internet, cell phones, teleconferences, etc.) and to enhance the
security of several government organizations so as to take into considerations almost all the contents of elearning
such as: information content, covering most of citizens or state firms or corporations queries.
Content provides a service to provide most if not all basic and business services; content of communicative
link provides the citizen and the state agencies together all the time and provides content security for all
workers on this network to work in securely environment. Access to information as well is safeguarded. The
main objective of this research is to build a novel multi-media security system (encrypting / decrypting
system) that will enable E-learning to exchange more secured multi-media data/information.
AN ADAPTIVE AND INTELLIGENT TUTOR BY EXPERT SYSTEMS FOR MOBILE DEVICESijmpict
Ā
Mobile Learning (M-Learning) is an emerging discipline in the area of education and educational technology. So researchers are trying to optimize and expanding its application in the field of education. The aim of this paper is to investigate the role of mobile devices and expert systems in disseminating and supporting the knowledge gained by intelligent tutors and to propose a system based on integration of intelligent M-Learning with expert systems. It acts as an intelligent tutor which can perform three processes - pre-test, learning concept and post-test - according to characteristic of the learner. The proposed system can improves the education efficiency highly as well as decreases costs. As a result, every time and everywhere (ETEW) simple and cheap learning would be provided via SMS, MMS and so on in this system. The global intention of M-Learning is to make learning āa way of beingā.
A SURVEY ON TECHNIQUES REQUIREMENTS FOR INTEGRATEING SAFETY AND SECURITY ENGI...IJCSES Journal
Ā
Nowadays, safety and security have become a requirement, integrated to each other, for information systems as a new generation of infrastructure systems distributed throughout networks. That opened the door for questions on whether these systems are safety-critical especially since they were tested in a closed, separated environment and are now deployed in an uncontrollable environment, namely the internet, where the number of threats is enormous. So it opened the door to talk about new development approach methods that take safety and security into consideration during the system development life cycle and most importantly, identifying hazard, risks and threats. We will conduct a survey exploring technical languages that were created by the scholars to combine safety and security requirement engineering and accident analysis technique languages.
Learner Ontological Model for Intelligent Virtual Collaborative Learning Envi...ijceronline
Ā
An enacting approach to intelligent virtual collaborative learning model is explored through the lens of critical ontology. This ontological model enables to reuse of the domain knowledge and to make the knowledge explicitly available to the agent working as an Expert System, which uses the operational knowledge in collaborative learning environment. This ontological model used by the agent to identify the preliminary competency level of the user. This environment offers personalized education to each learner in accordance with his/her learning preferences, and learning capabilities. Here the factors considered to identify the learning capability taken are demographic profile, age, family profile, basic educational qualification and basic competency scale. The conception of heuristics is then used by the agent to determine the effectiveness of the learner by referring the different parameters of the learner available in the ontological model.To help getting over this, the paper describes the experience on using an ontological model for collaborative learning to relate and integrate the history of the learner by maintaining the history of learner in collaborative learning environment that will be used by the Multi-Objective Grey Situation Decision Making Theory to infer the understanding level of user and produces the conditional content to the user
NLP-based personal learning assistant for school education IJECEIAES
Ā
Computer-based knowledge and computation systems are becoming major sources of leverage for multiple industry segments. Hence, educational systems and learning processes across the world are on the cusp of a major digital transformation. This paper seeks to explore the concept of an artificial intelligence and natural language processing (NLP) based intelligent tutoring system (ITS) in the context of computer education in primary and secondary schools. One of the components of an ITS is a learning assistant, which can enable students to seek assistance as and when they need, wherever they are. As part of this research, a pilot prototype chatbot was developed, to serve as a learning assistant for the subject Scratch (Scratch is a graphical utility used to teach school children the concepts of programming). By the use of an open source natural language understanding (NLU) or NLP library, and a slackbased UI, student queries were input to the chatbot, to get the sought explanation as the answer. Through a two-stage testing process, the chatbotās NLP extraction and information retrieval performance were evaluated. The testing results showed that the ontology modelling for such a learning assistant was done relatively accurately, and shows its potential to be pursued as a cloud-based solution in future.
Predicting depression using deep learning and ensemble algorithms on raw twit...IJECEIAES
Ā
Social network and microblogging sites such as Twitter are widespread amongst all generations nowadays where people connect and share their feelings, emotions, pursuits etc. Depression, one of the most common mental disorder, is an acute state of sadness where person loses interest in all activities. If not treated immediately this can result in dire consequences such as death. In this era of virtual world, people are more comfortable in expressing their emotions in such sites as they have become a part and parcel of everyday lives. The research put forth thus, employs machine learning classifiers on the twitter data set to detect if a personās tweet indicates any sign of depression or not.
A Behavior Based Intrusion Detection System Using Machine Learning AlgorithmsCSCJournals
Ā
Humans are consistently referred to as the weakest link in information security. Human factors such as individual differences, cognitive abilities and personality traits can impact on behavior and play a significant role in information security. The purpose of this study is to identify, describe and classify the human factors affecting Information Security and develop a model to reduce the risk of insider misuse and assess the use and performance of the best-suited artificial intelligence techniques in detection of misuse. More specifically, this study provides a comprehensive view of the human related information security risks and threats, classification study of the human related threats in information security, a methodology developed to reduce the risk of human related threats by detecting insider misuse by a behavior-based intrusion detection system using machine learning algorithms, and the comparison of the numerical experiments for analysis of this approach. Specifically, by using the machine learning algorithm with the best learning performance, the detection rates of the attack types defined in the organized five dimensional human threats taxonomy were determined. Lastly, the possible human factors affecting information security as linked to the detection rates were sorted upon the evaluation of the taxonomy.
Recently, modern technologies have made a positive contribution to most institutions of the society. However, they have generated serious issues with regard to the data security. For example, in the educational sector, most educational institutions have huge amounts of various types of data, which require rigorous protection ways to ensure their security and integrity. This study aims at reviewing the most recent data security methods, particularly the existing common encryption algorithms as well as designing an electronic system based on efficient and trusted ones to protect academic and nonacademic digital data in educational institutions. The study applies the satisfaction questionnaire as instrument to evaluate the proposed system efficiency. The questionnaire has been presented to the evaluation team whose members are divided into two groups: experts and end users. The results of the evaluation process have indicated that, the satisfaction ratio of the proposed system is encouraging. The overall satisfaction percentage is 96.25%, which demonstrates that the proposed system is an acceptable and suitable choice for various security applications.
The world is witnessing the electronic revolution in many fields of life such as health, education, government and commerce. E-learning is considered one of the hot topics in the e-revolution as it brings with it rapid change and greater opportunities to increase learning ability in colleges and schools. The fields of Learning Management Systems (LMS) and Learning Content Management Systems (LCMS) are full of open source and commercial products, however LCMS systems in general inherit the drawbacks of information system such as weakness in user expected information retrieval and semantic modelling and searching of contents & courses. In this paper, we propose a new prototype of LCMS that uses the Semantic Web technologies and Ontology Reasoner with logical rules, as an inference engine to satisfy the constraints and criteria specified by a user, and retrieves relevant content from the domain ontology in an organized fashion. This enables construction of a user-specific course, by semantic querying for topics of interest. We present the development of an Ontology-oriented Inference-based Learning Content Management System OILCMS, its architecture, conception and strengths.
Classification of Malware Attacks Using Machine Learning In Decision TreeCSCJournals
Ā
Predicting cyberattacks using machine learning has become imperative since cyberattacks have increased exponentially due to the stealthy and sophisticated nature of adversaries. To have situational awareness and achieve defence in depth, using machine learning for threat prediction has become a prerequisite for cyber threat intelligence gathering. Some approaches to mitigating malware attacks include the use of spam filters, firewalls, and IDS/IPS configurations to detect attacks. However, threat actors are deploying adversarial machine learning techniques to exploit vulnerabilities. This paper explores the viability of using machine learning methods to predict malware attacks and build a classifier to automatically detect and label an event as āHas Detection or No Detectionā. The purpose is to predict the probability of malware penetration and the extent of manipulation on the network nodes for cyber threat intelligence. To demonstrate the applicability of our work, we use a decision tree (DT) algorithms to learn dataset for evaluation. The dataset was from Microsoft Malware threat prediction website Kaggle. We identify probably cyberattacks on smart grid, use attack scenarios to determine penetrations and manipulations. The results show that ML methods can be applied in smart grid cyber supply chain environment to detect cyberattacks and predict future trends.
An educational bluetooth quizzing application in androidijwmn
Ā
Bluetooth is one of the most prevalent technologies available on mobile phones. One of the key questions
how to harness this technology in an educational manner in universities and schools. This paper is about a
Bluetooth quizzing system which will be used to administer quizzes to students of a university. The
Bluetooth quizzing application consists of a server and client mobile Android application. It will utilize a
queuing system to allow many clients to connect simultaneously to the server. When clients connect, they
can register or choose the option to complete a quiz that the lecturer selected. Results are automatically
sent when quiz is done from the client application. Data analysis can then be done to review the progress of
students.
Obfuscated computer virus detection using machine learning algorithmjournalBEEI
Ā
Nowadays, computer virus attacks are getting very advanced. New obfuscated computer virus created by computer virus writers will generate a new shape of computer virus automatically for every single iteration and download. This constantly evolving computer virus has caused significant threat to information security of computer users, organizations and even government. However, signature based detection technique which is used by the conventional anti-computer virus software in the market fails to identify it as signatures are unavailable. This research proposed an alternative approach to the traditional signature based detection method and investigated the use of machine learning technique for obfuscated computer virus detection. In this work, text strings are used and have been extracted from virus program codes as the features to generate a suitable classifier model that can correctly classify obfuscated virus files. Text string feature is used as it is informative and potentially only use small amount of memory space. Results show that unknown files can be correctly classified with 99.5% accuracy using SMO classifier model. Thus, it is believed that current computer virus defense can be strengthening through machine learning approach.
A Multimedia Data Mining Framework for Monitoring E-Examination Environmentijma
Ā
Academic dishonesty has been a growing concern in e-learning environment due to the fact that eexamination takes place under supervised and unsupervised learning environment despite its huge advantages. The e-examination environment has faced various security breaches such as academic dishonesty (impersonation), identity theft, unauthorised access and illegal assistance as a result of inefficient measures employed. Hence, an efficient framework which will aid the monitoring of the eexamination is needed. This paper reviews the process of mining multimedia data and propose a framework for monitoring the e-examination environment in order to extract images and audio features. The framework has four major phases: data pre-processing, mining, association and post processing. The
pre-processing phases carries out the extraction and transformation of multimedia data features, the mining phase does the classification and clustering of these features, the association does pattern matching while the post processing carries out the knowledge interpretation and reporting. The approach presented in this study will allow for efficient and accurate monitoring of e-examination environment which will help provide adequate security and reduce unethical behaviour in e-examination environment.
The Path and Thinking of Education Reform Driven by Blockchain Technology
Liping Li.
Abstract.
Ā Blockchain is changing the ideas and patterns of global finance, business and public management. In the field of education and teaching, bock chain also shows good application prospects. In order to study the path and method of the application of block chain technology in education reform, this paper analyzes the core technology of the block chain and its advantage in education and teaching, combining with teaching practice, this paper explains the application of block chain in educational innovation in many ways such as block chain transcript, learning certification, individualized learning, learning ledger, teaching resource management, monitoring and evaluation of teaching quality, etc. The article also gives the framework of the block chain teaching platform and puts forward some problems and thoughts of the block chain application used in education and teaching.
Development of Intelligent Multi-agents System for Collaborative e-learning S...journalBEEI
Ā
The aim of this paper is the introduction of intelligence in e-learning collaborative system. In such system, the tutor plays an important role to facilitate collaboration between users and boost less active among them to get more involved for good pedagogical action. However, the problem lies in the large number of platform users, and the tutor tasks become difficult if not impossible. Therefore, we used fuzzy logic technics in order to solve this problem by automating tutor tasks and creating an artificial agent. This agent is elaborate in basing on the learners activities, especially the assessment of their collaborative behaviors. After the implementation of intelligent collaborative system by using Moodle platform, we have tested it. The reader will discover our approach and relevant results.
SENSITIVITY ANALYSIS OF INFORMATION RETRIEVAL METRICS ijcsit
Ā
Average Precision, Recall and Precision are the main metrics of Information Retrieval (IR) systems performance. Using Mathematical and empirical analysis, in this paper, we show the properties of those metrics. Mathematically, it is demonstrated that all those parameters are very sensitive to relevance judgment which is not usually very reliable. We show that position shifting downwards of the relevant document within the ranked list is followed by Average Precision decreasing. The variation of Average Precision parameter value is highly present in the positions 1 to 10, while from the 10th position on, this variation is negligible. In addition, we try to estimate the regularity of the Average Precision value changes, when we assume that we are switching the arbitrary number of relevance judgments within the existing ranked list, from non-relevant to relevant. Empirically, it is shown hat 6 relevant documents at the end of the 20 document list, have approximately same Average Precision value as a single relevant document at the beginning of this list, while Recall and Precision values increase linearly, regardless of the document position in the list. Also, we show that in the case of Serbian-to-English human translation query followed by English-to-Serbian machine translation, relevance judgment is significantly changed and therefore, all the parameters for measuring the IR system performance are also subject to change.
Clustering of Deep WebPages: A Comparative Studyijcsit
Ā
The internethas massive amount of information. This information is stored in the form of zillions of
webpages. The information that can be retrieved by search engines is huge, and this information constitutes
the āsurface webā.But the remaining information, which is not indexed by search engines ā the ādeep webā,
is much bigger in size than the āsurface webā, and remains unexploited yet.
Several machine learning techniques have been commonly employed to access deep web content. Under
machine learning, topic models provide a simple way to analyze large volumes of unlabeled text. A ātopicāis
a cluster of words that frequently occur together and topic models can connect words with similar
meanings and distinguish between words with multiple meanings. In this paper, we cluster deep web
databases employing several methods, and then perform a comparative study. In the first method, we apply
Latent Semantic Analysis (LSA) over the dataset. In the second method, we use a generative probabilistic
model called Latent Dirichlet Allocation(LDA) for modeling content representative of deep web
databases.Both these techniques are implemented after preprocessing the set of web pages to extract page
contents and form contents.Further, we propose another version of Latent Dirichlet Allocation (LDA) to the
dataset. Experimental results show that the proposed method outperforms the existing clustering methods.
Learner Ontological Model for Intelligent Virtual Collaborative Learning Envi...ijceronline
Ā
An enacting approach to intelligent virtual collaborative learning model is explored through the lens of critical ontology. This ontological model enables to reuse of the domain knowledge and to make the knowledge explicitly available to the agent working as an Expert System, which uses the operational knowledge in collaborative learning environment. This ontological model used by the agent to identify the preliminary competency level of the user. This environment offers personalized education to each learner in accordance with his/her learning preferences, and learning capabilities. Here the factors considered to identify the learning capability taken are demographic profile, age, family profile, basic educational qualification and basic competency scale. The conception of heuristics is then used by the agent to determine the effectiveness of the learner by referring the different parameters of the learner available in the ontological model.To help getting over this, the paper describes the experience on using an ontological model for collaborative learning to relate and integrate the history of the learner by maintaining the history of learner in collaborative learning environment that will be used by the Multi-Objective Grey Situation Decision Making Theory to infer the understanding level of user and produces the conditional content to the user
NLP-based personal learning assistant for school education IJECEIAES
Ā
Computer-based knowledge and computation systems are becoming major sources of leverage for multiple industry segments. Hence, educational systems and learning processes across the world are on the cusp of a major digital transformation. This paper seeks to explore the concept of an artificial intelligence and natural language processing (NLP) based intelligent tutoring system (ITS) in the context of computer education in primary and secondary schools. One of the components of an ITS is a learning assistant, which can enable students to seek assistance as and when they need, wherever they are. As part of this research, a pilot prototype chatbot was developed, to serve as a learning assistant for the subject Scratch (Scratch is a graphical utility used to teach school children the concepts of programming). By the use of an open source natural language understanding (NLU) or NLP library, and a slackbased UI, student queries were input to the chatbot, to get the sought explanation as the answer. Through a two-stage testing process, the chatbotās NLP extraction and information retrieval performance were evaluated. The testing results showed that the ontology modelling for such a learning assistant was done relatively accurately, and shows its potential to be pursued as a cloud-based solution in future.
Predicting depression using deep learning and ensemble algorithms on raw twit...IJECEIAES
Ā
Social network and microblogging sites such as Twitter are widespread amongst all generations nowadays where people connect and share their feelings, emotions, pursuits etc. Depression, one of the most common mental disorder, is an acute state of sadness where person loses interest in all activities. If not treated immediately this can result in dire consequences such as death. In this era of virtual world, people are more comfortable in expressing their emotions in such sites as they have become a part and parcel of everyday lives. The research put forth thus, employs machine learning classifiers on the twitter data set to detect if a personās tweet indicates any sign of depression or not.
A Behavior Based Intrusion Detection System Using Machine Learning AlgorithmsCSCJournals
Ā
Humans are consistently referred to as the weakest link in information security. Human factors such as individual differences, cognitive abilities and personality traits can impact on behavior and play a significant role in information security. The purpose of this study is to identify, describe and classify the human factors affecting Information Security and develop a model to reduce the risk of insider misuse and assess the use and performance of the best-suited artificial intelligence techniques in detection of misuse. More specifically, this study provides a comprehensive view of the human related information security risks and threats, classification study of the human related threats in information security, a methodology developed to reduce the risk of human related threats by detecting insider misuse by a behavior-based intrusion detection system using machine learning algorithms, and the comparison of the numerical experiments for analysis of this approach. Specifically, by using the machine learning algorithm with the best learning performance, the detection rates of the attack types defined in the organized five dimensional human threats taxonomy were determined. Lastly, the possible human factors affecting information security as linked to the detection rates were sorted upon the evaluation of the taxonomy.
Recently, modern technologies have made a positive contribution to most institutions of the society. However, they have generated serious issues with regard to the data security. For example, in the educational sector, most educational institutions have huge amounts of various types of data, which require rigorous protection ways to ensure their security and integrity. This study aims at reviewing the most recent data security methods, particularly the existing common encryption algorithms as well as designing an electronic system based on efficient and trusted ones to protect academic and nonacademic digital data in educational institutions. The study applies the satisfaction questionnaire as instrument to evaluate the proposed system efficiency. The questionnaire has been presented to the evaluation team whose members are divided into two groups: experts and end users. The results of the evaluation process have indicated that, the satisfaction ratio of the proposed system is encouraging. The overall satisfaction percentage is 96.25%, which demonstrates that the proposed system is an acceptable and suitable choice for various security applications.
The world is witnessing the electronic revolution in many fields of life such as health, education, government and commerce. E-learning is considered one of the hot topics in the e-revolution as it brings with it rapid change and greater opportunities to increase learning ability in colleges and schools. The fields of Learning Management Systems (LMS) and Learning Content Management Systems (LCMS) are full of open source and commercial products, however LCMS systems in general inherit the drawbacks of information system such as weakness in user expected information retrieval and semantic modelling and searching of contents & courses. In this paper, we propose a new prototype of LCMS that uses the Semantic Web technologies and Ontology Reasoner with logical rules, as an inference engine to satisfy the constraints and criteria specified by a user, and retrieves relevant content from the domain ontology in an organized fashion. This enables construction of a user-specific course, by semantic querying for topics of interest. We present the development of an Ontology-oriented Inference-based Learning Content Management System OILCMS, its architecture, conception and strengths.
Classification of Malware Attacks Using Machine Learning In Decision TreeCSCJournals
Ā
Predicting cyberattacks using machine learning has become imperative since cyberattacks have increased exponentially due to the stealthy and sophisticated nature of adversaries. To have situational awareness and achieve defence in depth, using machine learning for threat prediction has become a prerequisite for cyber threat intelligence gathering. Some approaches to mitigating malware attacks include the use of spam filters, firewalls, and IDS/IPS configurations to detect attacks. However, threat actors are deploying adversarial machine learning techniques to exploit vulnerabilities. This paper explores the viability of using machine learning methods to predict malware attacks and build a classifier to automatically detect and label an event as āHas Detection or No Detectionā. The purpose is to predict the probability of malware penetration and the extent of manipulation on the network nodes for cyber threat intelligence. To demonstrate the applicability of our work, we use a decision tree (DT) algorithms to learn dataset for evaluation. The dataset was from Microsoft Malware threat prediction website Kaggle. We identify probably cyberattacks on smart grid, use attack scenarios to determine penetrations and manipulations. The results show that ML methods can be applied in smart grid cyber supply chain environment to detect cyberattacks and predict future trends.
An educational bluetooth quizzing application in androidijwmn
Ā
Bluetooth is one of the most prevalent technologies available on mobile phones. One of the key questions
how to harness this technology in an educational manner in universities and schools. This paper is about a
Bluetooth quizzing system which will be used to administer quizzes to students of a university. The
Bluetooth quizzing application consists of a server and client mobile Android application. It will utilize a
queuing system to allow many clients to connect simultaneously to the server. When clients connect, they
can register or choose the option to complete a quiz that the lecturer selected. Results are automatically
sent when quiz is done from the client application. Data analysis can then be done to review the progress of
students.
Obfuscated computer virus detection using machine learning algorithmjournalBEEI
Ā
Nowadays, computer virus attacks are getting very advanced. New obfuscated computer virus created by computer virus writers will generate a new shape of computer virus automatically for every single iteration and download. This constantly evolving computer virus has caused significant threat to information security of computer users, organizations and even government. However, signature based detection technique which is used by the conventional anti-computer virus software in the market fails to identify it as signatures are unavailable. This research proposed an alternative approach to the traditional signature based detection method and investigated the use of machine learning technique for obfuscated computer virus detection. In this work, text strings are used and have been extracted from virus program codes as the features to generate a suitable classifier model that can correctly classify obfuscated virus files. Text string feature is used as it is informative and potentially only use small amount of memory space. Results show that unknown files can be correctly classified with 99.5% accuracy using SMO classifier model. Thus, it is believed that current computer virus defense can be strengthening through machine learning approach.
A Multimedia Data Mining Framework for Monitoring E-Examination Environmentijma
Ā
Academic dishonesty has been a growing concern in e-learning environment due to the fact that eexamination takes place under supervised and unsupervised learning environment despite its huge advantages. The e-examination environment has faced various security breaches such as academic dishonesty (impersonation), identity theft, unauthorised access and illegal assistance as a result of inefficient measures employed. Hence, an efficient framework which will aid the monitoring of the eexamination is needed. This paper reviews the process of mining multimedia data and propose a framework for monitoring the e-examination environment in order to extract images and audio features. The framework has four major phases: data pre-processing, mining, association and post processing. The
pre-processing phases carries out the extraction and transformation of multimedia data features, the mining phase does the classification and clustering of these features, the association does pattern matching while the post processing carries out the knowledge interpretation and reporting. The approach presented in this study will allow for efficient and accurate monitoring of e-examination environment which will help provide adequate security and reduce unethical behaviour in e-examination environment.
The Path and Thinking of Education Reform Driven by Blockchain Technology
Liping Li.
Abstract.
Ā Blockchain is changing the ideas and patterns of global finance, business and public management. In the field of education and teaching, bock chain also shows good application prospects. In order to study the path and method of the application of block chain technology in education reform, this paper analyzes the core technology of the block chain and its advantage in education and teaching, combining with teaching practice, this paper explains the application of block chain in educational innovation in many ways such as block chain transcript, learning certification, individualized learning, learning ledger, teaching resource management, monitoring and evaluation of teaching quality, etc. The article also gives the framework of the block chain teaching platform and puts forward some problems and thoughts of the block chain application used in education and teaching.
Development of Intelligent Multi-agents System for Collaborative e-learning S...journalBEEI
Ā
The aim of this paper is the introduction of intelligence in e-learning collaborative system. In such system, the tutor plays an important role to facilitate collaboration between users and boost less active among them to get more involved for good pedagogical action. However, the problem lies in the large number of platform users, and the tutor tasks become difficult if not impossible. Therefore, we used fuzzy logic technics in order to solve this problem by automating tutor tasks and creating an artificial agent. This agent is elaborate in basing on the learners activities, especially the assessment of their collaborative behaviors. After the implementation of intelligent collaborative system by using Moodle platform, we have tested it. The reader will discover our approach and relevant results.
SENSITIVITY ANALYSIS OF INFORMATION RETRIEVAL METRICS ijcsit
Ā
Average Precision, Recall and Precision are the main metrics of Information Retrieval (IR) systems performance. Using Mathematical and empirical analysis, in this paper, we show the properties of those metrics. Mathematically, it is demonstrated that all those parameters are very sensitive to relevance judgment which is not usually very reliable. We show that position shifting downwards of the relevant document within the ranked list is followed by Average Precision decreasing. The variation of Average Precision parameter value is highly present in the positions 1 to 10, while from the 10th position on, this variation is negligible. In addition, we try to estimate the regularity of the Average Precision value changes, when we assume that we are switching the arbitrary number of relevance judgments within the existing ranked list, from non-relevant to relevant. Empirically, it is shown hat 6 relevant documents at the end of the 20 document list, have approximately same Average Precision value as a single relevant document at the beginning of this list, while Recall and Precision values increase linearly, regardless of the document position in the list. Also, we show that in the case of Serbian-to-English human translation query followed by English-to-Serbian machine translation, relevance judgment is significantly changed and therefore, all the parameters for measuring the IR system performance are also subject to change.
Clustering of Deep WebPages: A Comparative Studyijcsit
Ā
The internethas massive amount of information. This information is stored in the form of zillions of
webpages. The information that can be retrieved by search engines is huge, and this information constitutes
the āsurface webā.But the remaining information, which is not indexed by search engines ā the ādeep webā,
is much bigger in size than the āsurface webā, and remains unexploited yet.
Several machine learning techniques have been commonly employed to access deep web content. Under
machine learning, topic models provide a simple way to analyze large volumes of unlabeled text. A ātopicāis
a cluster of words that frequently occur together and topic models can connect words with similar
meanings and distinguish between words with multiple meanings. In this paper, we cluster deep web
databases employing several methods, and then perform a comparative study. In the first method, we apply
Latent Semantic Analysis (LSA) over the dataset. In the second method, we use a generative probabilistic
model called Latent Dirichlet Allocation(LDA) for modeling content representative of deep web
databases.Both these techniques are implemented after preprocessing the set of web pages to extract page
contents and form contents.Further, we propose another version of Latent Dirichlet Allocation (LDA) to the
dataset. Experimental results show that the proposed method outperforms the existing clustering methods.
Data mining model for the data retrieval from central server configurationijcsit
Ā
A server, which is to keep track of heavy document traffic, is unable to filter the documents that are most
relevant and updated for continuous text search queries. This paper focuses on handling continuous text
extraction sustaining high document traffic. The main objective is to retrieve recent updated documents
that are most relevant to the query by applying sliding window technique. Our solution indexes the
streamed documents in the main memory with structure based on the principles of inverted file, and
processes document arrival and expiration events with incremental threshold-based method. It also ensures
elimination of duplicate document retrieval using unsupervised duplicate detection. The documents are
ranked based on user feedback and given higher priority for retrieval.
A novel methodology for constructing rule based naĆÆve bayesian classifiersijcsit
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Classification is an important data mining technique that is used by many applications. Several types of classifiers have been described in the research literature. Example classifiers are decision tree classifiers, rule-based classifiers, and neural networks classifiers. Another popular classification technique is naĆÆve Bayesian classification. NaĆÆve Bayesian classification is a probabilistic classification approach that uses
Bayesian Theorem to predict the classes of unclassified records. A drawback of NaĆÆve Bayesian
Classification is that every time a new data record is to be classified, the entire dataset needs to be scanned
in order to apply a set of equations that perform the classification. Scanning the dataset is normally a very
costly step especially if the dataset is very large. To alleviate this problem, a new approach for using naĆÆve
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Ā
Systemās reusability and cost are very important in software product line design area. Developersā goal is
to increase system reusability and decreasing cost and efforts for building components from scratch for
each software configuration. This can be reached by developing software product line (SPL). To handle
SPL engineering process, several approaches with several techniques were developed. One of these
approaches is called separated approach. It requires separating the commonalities and variability for
systemās components to allow configuration selection based on user defined features. Textual notationbased
approaches have been used for their formal syntax and semantics to represent system features and
implementations. But these approaches are still weak in mixing features (conceptual level) and classes
(physical level) that guarantee smooth and automatic configuration generation for software releases. The
absence of methodology supporting the mixing process is a real weakness. In this paper, we enhanced
SPLās reusability by introducing some meta-features, classified according to their functionalities. As a first
consequence, mixing class and feature concepts is supported in a simple way using class interfaces and
inherent features for smooth move from feature model to class model. And as a second consequence, the
mixing process is supported by a textual design and implementation methodology, mixing class and feature
models by combining their concepts in a single language. The supported configuration generation process
is simple, coherent, and complete.
T OWARDS A S YSTEM D YNAMICS M ODELING M E- THOD B ASED ON DEMATELijcsit
Ā
If System Dynamics (SD) models are constructed based
solely on decision makers' mental models and u
n-
derstanding of the context subject to study, then the resulting systems must necessarily bear some d
e
gree of
deficiency due to the subjective, limited, and internally inconsistent mental models which led to t
he conce
p-
tion of these systems. As such, a systematic method for constructing SD models could be esse
n
tially helpful
in overcoming the biases dictated by the human mind's limited understanding and conceptualization of
complex systems. This paper proposes a
novel combined method to su
p
port SD model construction. The
classical Dec
i
sion Making Trial and Evaluation Laboratory (DEMATEL) technique is used to define causal
relationships among variables of a system, and to construct the corresponding Impact Relatio
n Maps
(IRMs). The novelty of this paper stems from the use of the resulting total influence m
a
trix to derive the
system dynamic's Causal Loop Diagram (CLD) and then define variable weights in the stock
-
flow chart
equations. This new method allows to overc
ome the subjectivity bias of SD
mode
ling while projecting D
E-
MATEL in a more d
y
namic simulation environment, which could significantly improve the strategic choices
made by an
a
lysts and policy makers
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activities to clouds. Researchers of virtual learning are also looking for the ways to use clouds through
mobile platforms. This paper offers a model to accompany the benefits of āMobile Intelligent Learningā
technology and āCloud Computingā. The architecture of purposed system is based on multi-layer
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users to enjoy an intelligent learning every-time and every-where, reduces training costs and hardware
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Today, applications in mobile multi-agent systems require a high degree of confidence that running code inside the system will not be malicious. Also any malicious agents must be identified and contained. Since the inception of mobile agents, the intruder has been addressed using a multitude of techniques, but many of these implementations have only addressed concerns from the position of either the platform or the agents. Very few approaches have undertaken the problem of mobile agent security from both perspectives simultaneously. Furthermore, no middleware exists to facilitate provisioning of the required security qualities of mobile agent software while extensively focusing on easing the software development burden. The aim is to build a distributed secure system using multi-agents by applying the principles of software engineering. The objectives of this paper is to introduce multi agent systems that enhance security rules through the access right to building a distributed secure system integrating with principles of software engineering system life cycle, as well as satisfy the security access right for both platform and agents to improve the three characteristics of agents adaptively, mobility and flexibility. This project based on the platform of PHP and MYSQL (Database) which can be presented in a website. The implementation and test are applied in both Linux and Windows platforms, including Linux Red Hat 8, Linux Ubuntu 6.06 LTS and Microsoft Windows XP Professional. Since PHP and MySQL are available in almost all operating systems, the result could be tested the platform as long as PHP and MySQL configuration is available. PHP5 and the MySQL (database) software are used to build a secure website. Multiple techniques of security and authentications have been used by multi-agents system. Secure database is encrypted by using md5. Also satisfy the characteristics for security requirements: confidentiality (protection from disclosure to unauthorized persons), integrity (maintaining data consistency) and authentication (assurance of identity of person or originator of data).
INFORMATION AND COMMUNICATION SECURITY MECHANISMS FOR MICROSERVICES-BASED SYS...IJNSA Journal
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Security has become paramount in modern software services as more and more security breaches emerge, impacting final users and organizations alike. Trends like the Microservice Architecture bring new security challenges related to communication, system design, development, and operation. The literature presents a plethora of security-related solutions for microservices-based systems, but the spread of information difficult practitioners' adoption of novel security related solutions. In this study, we aim to present a catalogue and discussion of security solutions based on algorithms, protocols, standards, or implementations; supporting principles or characteristics of information security, considering the three possible states of data, according to the McCumber Cube. Our research follows a Systematic Literature Review, synthesizing the results with a meta-aggregation process. We identified a total of 30 primary studies, yielding 75 security solutions for the communication of microservices.
AN OVERVIEW OF CLOUD COMPUTING FOR E-LEARNING WITH ITS KEY BENEFITSijistjournal
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Education is a necessary human virtue and essential for society because it reflects the personality of the human being in our society. The effective way of teaching gives the quality of education and advance learning such as e-learning to the learners and also a high quality of teaching to the tutors. Information Technology (IT) plays a significant role in field of education. Now days, E-learning and M-learning have become very popular trends of the education technology riot. E-Learning is the new tool related to the virtualized distance learning by means of electronic communication mechanisms, specifically the Internet to enhance the traditional learning system. An E-learning system generally needs a lot of software and hardware resources. Today, many educational institutions cannot afford such investments and environments therefore cloud computing is the finest solution. The Cloud Computing environment rises swiftly as a natural platform to provide support to e-Learning systems. Hence, this paper presents the impact on using cloud computing for e-learning which contains an innovative environment resulting from both virtual and personal learning environments. This paper introduces concepts of e-learning and cloud computing infrastructure with their key benefits.
Mobile devices have been playing vital roles in modern dayeducation delivery as students can access or
download learning materials on their smartphones and tablets, they can also install educational apps and
study anytime, anywhere. The need to provide adequate security forportable devices being used for
learning cannot be underestimated. In this paper, we present a mobile security enhancement app,
designed and developedfor Android smart mobile devices in order to promote security awareness among
students. The app can alsoidentify major and the most significant security weaknesses, scan or check for
vulnerabilities in m-learning devices and report any security threat.
Mobile devices have been playing vital roles in modern dayeducation delivery as students can access or
download learning materials on their smartphones and tablets, they can also install educational apps and
study anytime, anywhere. The need to provide adequate security forportable devices being used for
learning cannot be underestimated. In this paper, we present a mobile security enhancement app,
designed and developedfor Android smart mobile devices in order to promote security awareness among
students. The app can alsoidentify major and the most significant security weaknesses, scan or check for
vulnerabilities in m-learning devices and report any security threat
Mobile devices have been playing vital roles in modern dayeducation delivery as students can access or
download learning materials on their smartphones and tablets, they can also install educational apps and
study anytime, anywhere. The need to provide adequate security forportable devices being used for
learning cannot be underestimated. In this paper, we present a mobile security enhancement app,
designed and developedfor Android smart mobile devices in order to promote security awareness among
students. The app can alsoidentify major and the most significant security weaknesses, scan or check for
vulnerabilities in m-learning devices and report any security threat.
This paper aims to provide main advance in the delivering techniques which are adapting to learner using multiagent system. Including models and the corresponding methods.It focuses on both datamining and e-learning. Multiagent system is a computer programming based system which is composed by multiple interacting computer programs.MAS can be used to solve the program that are complex or seems impossible for an indivisual program to solve.Multiagent system composed of various entities that have different information or diverging interest.In multiagent system agents are computer program that act on behalf of the users to solve a computer program.
Secured cloud support for global softwareijseajournal
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This paper presents core problem solution to security of Global Software Development Requirement
Information. Currently the major issue deals with hacking of sensitive client information which may lead to
major financial as well as social loss. To avoid this system provides cloud security by encryption of data as
well as deployment of tool over the cloud will provide significant security to whole global content
management system. The core findings are presented in terms of how hacker hacks such systems and what
counter steps need to follow. Our algorithmic development provide random information storage at various
cloud nodes to secure our client requirement data files.
Technological development have altered the way we communicate, learn, think, share, and spread information. Mobile technologies are those that make use of wireless technologies to gain some sort of data. As mobile connectedness continues to spread across the world, the value of employing mobile technologies in the arena of learning and teaching seems to be both self-evident and unavoidable The fast deployment of mobile devices and wireless networks in university campuses makes higher education a good environment to integrate learners-centered m-learning . this paper discusses mobile learning technologies that are being used for educational purposes and the effect they have on teaching and learning methods.
A USER PROFILE BASED ACCESS CONTROL MODEL AND ARCHITECTUREIJCNC
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Personalization and adaptation to the user profile capability are the hottest issues to ensure ambient
assisted living and context awareness in nowadays environments. With the growing healthcare and
wellbeing context aware applications, modeling security policies becomes an important issue in the
design of future access control models. This requires rich semantics using ontology modeling for the
management of services provided to dependant people. However, current access control models remain
unsuitable due to lack of personalization, adaptability and smartness to the handicap situation.
Defending against label-flipping attacks in federated learning systems using ...IAESIJAI
Ā
The user experience can be greatly improved by using learning models that have been trained using data from mobile devices and other internet of things (IoT) devices. Numerous efforts have been made to implement federated learning (FL) algorithms in order to facilitate the success of machine learning models. Researchers have been working on various privacy-preserving methodologies, such as deep neural networks (DNN), support vector machines (SVM), logistic regression, and gradient boosted decision trees, to support a wider range of machine learning models. The capacity for computing and storage has increased over time, emphasizing the growing significance of data mining in engineering. Artificial intelligence and machine learning have recently achieved remarkable progress. We carried out research on data poisoning attacks in the FL system and proposed defence technique using uniform manifold approximation and projection (UMAP). We compare the efficiency by using UMAP, principal component analysis (PCA), Kernel principal component analysis (KPCA) and k-mean clustering algorithm. We make clear in the paper that UMAP performs better than PCA, KPCA and k-mean, and gives excellent performance in detection and mitigating against data-poisoning attacks.
Technological development have altered the way we communicate, learn, think, share, and spread information. Mobile technologies are those that make use of wireless technologies to gain some sort of data. As mobile connectedness continues to spread across the world, the value of employing mobile technologies in the arena of learning and teaching seems to be both self-evident and unavoidable The fast deployment of mobile devices and wireless networks in university campuses makes higher education a good environment to integrate learners-centered m-learning. This paper discusses mobile learning technologies that are being used for educational purposes and the effect they have on teaching and learning methods.
AN EFFECTIVE METHOD FOR INFORMATION SECURITY AWARENESS RAISING INITIATIVESijcsit
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activities and provide E-Services for their customers. In the process, whether they know it or not, those
organizations are also opening themselves up to the risk of information security breaches. Therefore
protecting an organizationās ICT infrastructure, IT systems, and Data is a vital issue that is often
underestimated. Research has shown that one of the most significant threats to information security comes
not from external attack but rather from the system's users, because they are familiar with the
infrastructure and have access to its resources, but may be unaware of the risks. Moreover, using only
technological solutions to protect an organizationās assets is not enough; there is a need to consider the
human factor by raising usersā security awareness. Our contribution to this problem is to propose an
Information Security Awareness Program that aims at raising and maintaining the level of usersā security
awareness. This paper puts forward a general model for an information security awareness program and
describes how it could be incorporated into an organizationās website through the process of development
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UiPath Test Automation using UiPath Test Suite series, part 3
Ā
Information security approach in open distributed multi agent virtual learning environment
1. International Journal of Computer Science & Information Technology (IJCSIT) Vol 6, No 1, February 2014
DOI : 10.5121/ijcsit.2014.6102 15
Information Security Approach in Open
Distributed Multi-Agent Virtual Learning
Environment
Dr. Zahi A.M. Abu Sarhan 1
and As'ad Mahmoud As'ad Alnaser2
1
Department of Computer Information Systems, Applied Science Private University,
Amman, Jordan
2
Department of Computer Science, Al-Balqa' Applied University, Ajlun University
College, Ajlun, Jordan
ABSTRACT
This paper presented the main information, security problems and threats in open multi-agent distributed
e-learning information systems and Proposed various approaches to solve information security attacks in
virtual learning environment using service oriented architecture which based on multi-agent information
systems architecture, the solution on the multi-agent learning information system implementation based on
the implementation of two types of systems the first system with the centralized mobile agent information
security management and the second system with decentralized mobile agents security management, and
proposed the migration behavior simulation for their active software components (software agents) .
KEYWORDS
Information security, Distributed multi-agent system, Virtual learning environment. Agent migration.
1. INTRODUCTION
Relevance research in the field of distributed artificial intelligence and multi-agent systems
(MAS), according to [1], on the complexity of modern organizational and technical systems,
variety, tasks distribution and the huge volume information flows and critical information
processing time. The theoretical researches in MAS field mainly carried out in the following
areas: Agents theory, Agents collective behavior, agents and MAS architecture; methods,
languages and agents communication tools, agents implementation languages; agents migration
support tools within network. The greatest difficulty in theoretical studies and practical
implementations of modern MAS are the issues related to agentās information security and
information resources, which they operate in open multi-agent virtual learning environments.
Providing information security is an important task that must be solved when developing MAS,
focused on the usage in various fields.
Software agent is computer system, which is found in some environment and is capable of
autonomous action in this environment in order to meet its design objectives [2]. Software agents
have characteristics that make them suitable for complex functions. Such features include:
autonomy, interaction, reactivity, activity, intelligence and mobility [3].
E-learning represents the use of electronic media and information and communication
technological innovations in education and learning processes. E-learning is generally
2. International Journal of Computer Science & Information Technology (IJCSIT) Vol 6, No 1, February 2014
16
comprehensive of all forms of academic technological innovation in study and education. E-
learning contains various types of media that deliver text, sound, pictures, computer animation,
and streaming video, and contains technology programs and procedures such as sound or movie
record, computer-based learning, as well as regional intranet/extranet and web-based learning.
Information and interaction systems, whether free-standing or depending on either regional
networks or the Internet in networked learning, underlay many e-learning procedures [4].
E-learning can occur in or out of the classroom. It can be self-paced, asynchronous learning or
may be instructor-led, synchronous learning. E-learning is suited to distance learning and flexible
learning, but it can also be used in conjunction with face-to-face teaching, in such case the term
blended learning is commonly used [4].
Virtual learning environments (VLE) have become a frequent tool in higher education
organizations for supporting and assisting both study and education. They create a platform for
instructors and students to access educational materials, read reports, interacts with others, send
and receive assignments, get involved in conversations and group work. These days, there are
plenty of commercial VLE techniques available in the market. Each of them offers its own
features and performance [5].
2. PROBLEMS AND INFORMATION SECURITY THREATS IN OPEN MAS
Ensuring the information security problem in MAS can be presented in several ways. First, it is
necessary to provide nodes protection against hidden attacks by malicious programs or spyware
agents. Second, we need to protect agents themselves from exposure applications running on the
network nodes. Third, it is necessary to ensure the protection MAS agents from attacks spyware
agents, migrating between network nodes. The first problem can be successfully solved by using
strong authentication methods executable agents code, agents program code integrity monitoring
and access restrictions either by software agents, or information or services that they provide. The
second problem is one of the major unsolved problems today. The reason for this is the existence
of a large set of malware that can unauthorized way affect the agents operation process and
manipulate the confidential information, on which the agents operate. The third problem solution
based is on special security protocols which create exchanging messages between agents in multi-
agent environment.
Security threats in distributed MAS include: passive unauthorized message exchanging
interception within communications process between agents, the integrity breach of the
transmitted data over the network, unauthorized access to the data, denial of service, intercept
requests with their subsequent modification and playback, the rejection of fact receiving or
sending data. The decentralized nature of building distributed MAS, none single center, the
components heterogeneity, the potential communication with any node make multi-agent
environment maximum vulnerable to any kind of these threats [6].
3. EXISTING INFORMATION SECURITY SOLUTIONS IN OPEN MAS
Ensuring information security under consideration class of systems can be organized as complex
of famous solutions. The most efficient and flexible at present solutions for agentās information
security, and MAS are:
ā¢ Agents protected states method [7];
ā¢ Mobile cryptography methods [8];
3. International Journal of Computer Science & Information Technology (IJCSIT) Vol 6, No 1, February 2014
17
ā¢ Police Office security model[9];
ā¢ Buddy Model of security for mobile agents [10];
ā¢ Methods of the organization of self-organizing systems trusting relationship [11];
ā¢ Methods based on using algorithms for confidential communications and proxy
performing, the functions and limitations of restricting access to resources and services
based on the methods of identification and authentication [12].
Despite such a wide range of existing solutions, none of these approaches provided a
comprehensive solution of agentās information security problems from harmful sites and spyware
in open MAS.
4. MULTI-AGENT VIRTUAL LEARNING ENVIRONMENT
A virtual learning environment (VLE) is a software system designed to support teaching and
learning. VLEs generally function on the World Wide Web, and, therefore, they can be utilized
both on and off-campus, provided that the users are authorized and can access the Internet. This
surmount over the restriction of traditional face-to-face educating, and guarantees that learning is
neither limited to location nor time. VLEs become more popular and included in many college
organizations all over the world. It is not only because of their versatility, but also because they
provide an extensive range of tools or features, such as content distribution, evaluation, emails
[13].
Based on the learning process components the representation of VLE can be presented as shown
in figure 1.
Learner-Content
Interaction Agent
Techer-Content
Interaction Agent
Learner-Learner Interaction
agent
Learner-Teacher
Interaction Agent
Teacher-Teacher Interaction
agent
Content-Content Interaction
agent
Figure1. Virtual learning environment based on multi-agents architecture.
4. International Journal of Computer Science & Information Technology (IJCSIT) Vol 6, No 1, February 2014
18
5. OPEN MULTI-AGENT VIRTUAL LEARNING ENVIRONMENT STRUCTURE AND
FORMAL REPRESENTATION
The main part of this work focuses on solving agents information security problems. As example
of ensuring information security in e-learning systems, OMAVLE (Open Multi-Agent Virtual
Learning Environment).
In terms of overall functioning logic e-learning has a multi-agent realization. Agent-based
orientation is expressed in the fact that in its real subject e-learning activity is represented by one
or more mobile software agents that represent e-Learning-activities and implement procedures for
an automated search agent partners for cooperation.
In general, the model OMAVLE can be assigned as a theoretic-set of relations and can be
represented as the next set of sets:
{ } { } { } { } { } { } { }OMAS S A U VLP IR O ATTR= U U U U U U ;
Where { }S - set the system users (E-Learning subjects); { }A - set of agents in the system,
representing the interests of users in a virtual learning environment; { } { } { }U SH CH= U where U
set of the system nodes, in which agents operate, { }SH - multiple server hosts, { }CH - multiple
client hosts; { }VLP - set of virtual learning-platforms (VLP), within which the combined agents
of joint activities with similar interests and goals; { }IR - set of information system resources;
{ }O - relations between model objects sets; { }ATTR - set of model objects attributes;
There are two main types of operational agents in the system{ } { } { }A MA CA= U , where { }MA -
the migrating mobile agents between network nodes; { }CA - the control agents (moderators), that
operating within the VLP and coordinating the processes of mobile agents interaction and
migration.
On the set of objects model the following relationship, that defines the structure of OMAELS, can
be defined:
{ } { } { } { } { } { }O SMA SHVLP MAVLP CAVLP CAMA= āŖ āŖ āŖ āŖ ;
Where { } { } { }SMA S MAā Ć
- the availability relation of each virtual learning subject
representative - agent; { } { } { }SHVLP SH MAā Ć
- The existence relation of each system server
node of VLP; { } { } { }MAVLP MA VLPā Ć
- The existence relation of each VLP agents of joint
activities with common interest areas; { } { } { }CAVLP CA VLPā Ć
The membership relation of each
virtual platform with its control agent (agent-moderator);{ } { } { }CAMA CA MAā Ć
- The
membership relation of each control agent from agent joint activities set that it coordinates their
interaction.
5. International Journal of Computer Science & Information Technology (IJCSIT) Vol 6, No 1, February 2014
19
Each mobile agent can be described with the following parameters set:
{ } { } { } { } { },MA Id Id ST D SSMPMA MA MA= āŖ āŖ āŖ
Where IdMA - The mobile agent unique identifier; IdMP - The server node unique identifier
from which mobile agent migrates, { }STMA - The mobile agent states set; { }DMA - data set,
which mobile agent operates; { } { } { },SS C Pk Sk= āŖ - mobile agent internal security system; { }C -
The set of data encryption cryptographic methods with open and/or private key; Pk - public key
known only by mobile agent and its control agent (the public keys refresh rate determined by the
control agent); Sk - private (secret) key known only by mobile agent (the secret key refresh rate
determined by mobile agent).
6. PROBLEM SOLUTION FOR INFORMATION SECURITY IN OMAVLE
Novelty of what proposed in this paper is problem solving for ensuring information security in
open distributed MAS which is a combination of two approaches to the OMAVLE formation
[14].
The first approach is based on the concept of a closed network lies in the development of a multi-
agent virtual electronic learning environment with independent agent platforms based on the
technology [15], within which agents operate with other agents that have similar interests and
goals (collecting agents with the similar interests private groups), and the using of agents state
protection method in order to prevent hidden malware and spyware agents attacks. Formulation
VLP based on agents consensus where each agent shared information with other agents with the
same interest and same goals, this virtual learning platform can be collected form single node in
network or from multiple nods and this VLP begins allotted platform [16] (private group of
agents with the same interests, implemented on any of the nodes in the system).
The second Proposed approach, based on the idea which described in [14] which involves the
implementation of an open multi-agent environment specialized software component - the mobile
agents security system (MASS), providing the cryptographic techniques and mechanisms
implementation to protect the system agents of various computer attacks types from malicious
software, and using simulation tools for analysis, forecasting and studying the dynamic agents
behavior in the system.
As a simulation tool can be used system-dynamic complexes or agent-based models. For
Extending Multi-Agent Security System (MASS) functionality integrated into MASS structure,
developed specific software components, that provides support for inter-agent (between agents)
interaction and agents self-organization, as well as implementing protection mechanisms that
protect the system agents from various types of computer attacks as malware. These components
include:
ā¢ Registry Server;
ā¢ Agents Name server;
ā¢ Public key encryption Server;
ā¢ Data encryption module;
ā¢ Special register;
ā¢ Agent Control System.
6. International Journal of Computer Science & Information Technology (IJCSIT) Vol 6, No 1, February 2014
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Registry Server contains information about the operated system nodes, and controls the new
nodes and new agentās connections to the system. Agent Name Server collects information about
all system agents.
Formation and maintenance distributed agents registry carried out on the basis of their binding to
the dendritic domain conceptual models. Public key encryptions Server jointly with data
encryption module are the core of agentās information security system, agents, agents
representative and system nodes. It implements agent identification and authentication procedure
and information cryptographic protection methods with public key. The key server stores a set of
individual public keys to encrypt the information that system agents operate within each other
interaction and with running applications on the network nodes.
In this paper, as a data encryption with public key method proposed to use classical asymmetric
key cryptographic encryption algorithm with RSA public key [17, 18] and its modifications [19].
For ensuring the integrity and confidentiality of their requests and to protect information about
participations, the agents use electronic signature and known private key encryption methods.
Special register contains full information about all VLP registered in the system, and their
constituent agents coalitions. MASS integrates with agents control system, representing software
components set that implement the agents operation and interaction internal logic, inter-agent
communication protocols.
7. MULTI-AGENT SECURITY SYSTEM MANAGEMENT FUNCTIONING
ALGORITHM.
The study proposed two embodiments of MASSM: the first system with centralized mobile
agentās security management, and the second system with decentralized mobile agentās security
management.
When a new learner connects to the system, the system generates for hem his virtual
representative (mobile agent), this mobile agent acting as learner interest. The agent is generated
by the server host and performed the following actions:
ā¢ Searching learning application and/or learning partner that satisfies given constraints in the
system data base distributed heterogeneous server hosts;
ā¢ Forming the virtual learning structures (agentsā coalition) to implement specific leaning task.
To the agents assigned not only searching and placement information tasks, but also analysis
and processing functions. The agent provides the gathered and formed information to its
owner to make a decision.
After generating a new agent in the system, the information about him and his owner will be
registered in the appropriate system registry. At the time of generating control agent assigned to
each new mobile agent unique identifier and name that will be registered in the agents name
server, and determined the public key for agents data encryption and decryption, private (secret)
key generated by the agent themselves at the registration moment in the system. The public key
is known only by agent manager from the native system host (node) where the mobile agent was
created. Having passed the registration stage created agent starts interacting with other agents
within the agent-based representation of the host where it was generated, the agent begins
improve its knowledge about the system, exactly, the agent begins collect all available
information about already registered agents in the system, system components and virtual
learning platforms, which problem orientation coincides with the agents interests area.
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In the case of systems with a centralized mobile agentās security management in an open multi-
agent virtual learning platform as shown in figure 2 is implemented on a dedicated server, which
functional structure shown in Figure 3.
E-LVE 1 E-LVE N
Internet, Lan,
WAN
MASMS
Request - Response Request - Response
ā¦ā¦ā¦..
ā¦ā¦ā¦..
Figure 2. Open multi-agent VLE with the centralized mobile agentās security system management.
Agents functioning control and analysis system
System agents Public key
encryption Server
Agents Name server Special register
Registry Server
Data encryption module
Agents functioning Control and
Analysis system
Agents control system Simulation subsystem
System Monitor
Agents Destruction Manager
Agents Control Manager Agents Migration Manager
Interaction Manager
Figure 3.The functional structure of Mobile agent security server.
Security Server provides mobile agents centralized information storage about all agents in the
system, accessible hosts, virtual learning platforms, agentās public keys which can access only the
system control agents. In the security server must be realized data encryption and decryption
module, and the system monitoring, agentās behavior analysing and modeling in the system,
which is also available for agent control in the system. Let us consider algorithm functioning the
main components OMAVLS utilizing this approach to implement MASS, as in Figure 4.
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User Host Server (HS) Mobile Agent (MA) Control Agent (CA) Security Server (SS)
Register
Create MA
Inform CA
Generate Key Pair
Send PK CA
Register MA
Lunch MA
Requist
Encrypt Data MA
Query DB
Neogate with other
MA
Migration Request
Verification
Migration Point
Send Result
Confirm
Migrate To HostInform CA
Send MA id And
HS id
Verify MA id And
HS id
Send Result
Lunch MA
Requist MA PK
Send MA PK
Dencrypt Data MA
Neogate with MA
Encrypt Data MA
Query HS DB
Migrate next host
Return home
Dencrypt Data MA
Response
Generate new Key
Pair
Send new PK CA
Update PK MA
Figure 4. Algorithm interaction main components OMAVLE with centralized mobile agent security system
management.
Suppose that some mobile agent iMA plans to migrate from the virtual learning platform iVLP ,
located on the host iSH , to another virtual learning platform kVLP , which functioning on the host
kSH . iMA agent sends a request to its control agent iCA to carry out migration to kVLP on host
9. International Journal of Computer Science & Information Technology (IJCSIT) Vol 6, No 1, February 2014
23
kSH . When the control agent iCA received a request from the agent iMA , accesses the mobile
agents security server (MASS) acts as the certifying canter lead, MASS requesting information to
verify the existence of kSH and kVLP respectively. In positive response case the control agent
iCA allows the agent iMA to carry out migration to the host kSH and initiates an agent iMA
moving process via Agents Migration Manager. At the entrance to the agent-based representation
of host kSH , is a protected memory area (the agent-based representation environment of the
receiver host), where loads the software code and migratory agent data which is accessible only
by the receiver host kSH control agents, agent iMA imposes his certificate to the control agent
kCA on platform kVLP , in which he wants to be member in. The certificate is an electronic
document that contains an agent electronic key, agent information (The mobile agent unique
identifier MAId ; The server host unique identifier (address) MPId from which he migrated, etc.),
countersignature certificate authority iCA and information about the certificate validity period.
The control agent iCA platform kVLP refers to the central mobile agent security server and checks
the information contained in the agent iMA certificate. If the agent and the host are registered in
the system, and the certificate is authentic, the agent iMA will be loaded into main memory host
kSH , and kSH host resources within the platforms kVLP address space become available for
agent iMA .
Agent iMA can gather all necessary information and can negotiate with agent belonging to host
kVLP . Otherwise, the agent iMA will be blocked, and the access to all resources kSH host will be
prohibited. However, the control agent iCA puts the agent iMA in "black list" and informs all
known agents about presence "foreign" agent in the system.
Since all the operated data by agent iMA which encrypted with private key and unknown to any
agent within the node kSH , the control agent iCA accesses the mobile agent security server and
requests the public key to decrypt the agent iMA data, searching is carried out by agent ID IdMA .
After receiving the public key and decrypt agent iMA data, the agent data become available to all
agents in platform kVLP . Before entering the agent iMA into the node kVLP The control agent iCA
provides it with needed information about all the agents operating within platform kVLP , thereby
the agent iMA knowledge about the system already replenished. After returning agent iMA to his
"native" host, it generates a new key pair ,( )MA MAi i
Sk Pk , and its control agent iCA updates its
public key, which is stored on the mobile agent security server.
In the case of decentralized mobile agents security system management figure 5 MASS in open
multi-agent virtual learning environment was implemented on each server node of the system
(portals), where users register their learning requisites. With this solution, MASS is part of the
agent-based representation on the server node and performs a similar function as the mobile
agents security server: stores information about agents in the system, available hosts, virtual
learning platforms, agents public key which can access only the system control agent,
implementing procedures of agents data encryption and decryption, monitoring, analysing and
modeling agents behavior in the system. Consider the functional structure of mobile agent
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security host figure 6 and the main components interaction principles of OMAVLS with this
implementation approach MASS figure 7.
E-LVE 1 E-LVE N
E-LVE 2
Internet, Lan,
WAN
Request - Response Request - Response
Request - Response
Figure 5.Open multi-agent VLE with the decentralized mobile agentās security c system.
Agents functioning control and analysis system
System agents Public key
encryption Server
Agents Name server Special register
Registry Server
Data encryption module
Agents functioning Control and
Analysis system
Agents control system Simulation subsystem
System Monitor
Agents Destruction Manager
Agents Control Manager Agents Migration Manager
Interaction Manager
Figure 6. The functional structure of Mobile agent security host.
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User Host Server (HS) Mobile Agent (MA) Control Agent (CA) Security system Host
Register
Create MA
Inform CA
Generate Key Pair
Send PK CA
Register MA
Lunch MA
Requist
Encrypt Data MA
Query DB
Neogatiate with
other MA
Migration Request
Verification
Migration Point
Send Result
Confirm
Migrate To HostInform CA
Send MA id And
HS id
Verify MA id And
HS id
Send Result
Lunch MA
Requist MA PK
Send MA PK Dencrypt Data MA
Neogate with MA
Encrypt Data MAQuery HS DB
Migrate next hostReturn home
Dencrypt Data MA
Response
Generate new Key
Pair
Send new PK CA
Update PK MA
Verify CA ID
Figure 7. Algorithm interaction main components OMAVLE with decentralize mobile agent security
system management.
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Suppose that some mobile agent iMA plans to migrate from the virtual learning platform iVLP ,
located on the host iSH , to another virtual learning platform kVLP , which functioning on the host
kSH . iMA agent sends a request to its control agent iCA to carry out migration to kVLP on host
kSH . When the control agent iCA received a request from the agent iMA , accesses the mobile
agents security system in agent representation, and request information to verify the existence of
kSH and kVLP respectively. In positive response case the control agent iCA allows the agent
iMA to carry out migration to the host kSH and initiates an agent iMA moving process via Agents
Migration Manager. At the entrance to the agent-based representation of host kSH , agent iMA
imposes his certificate to the control agent kCA on platform kVLP , in which he wants to be
member in. The control agent kCA on platform kVLP based on the information contained in the
certificate checks the existence of node iSH and agent iMA in the local system register and in the
MASS. If the agent and the host are registered in the system, the control agent kCA access the
control agent iCA on the host iSH from which migrated agent iMA this center acts as certificate
center, and prompting to confirm the existence of an agent iMA and the fact that he was permitted
to migrate to the host kSH . If the control agent iCA confirms the existence of agent iMA and the
fact of migration to host kSH , the control agent kCA , the agent iMA will be loaded into host kSH
main memory, and gives him access to all resources within the host kSH address space platforms
kVLP . Agent iMA can gather all necessary information and can negotiate with agent belonging to
host kVLP . Otherwise, the agent iMA will be blocked, and the access to all resources kSH host will
be prohibited. However, the control agent iCA puts the agent iMA in "black list" and informs all
known agents about presence "foreign" agent in the system.
Since all the operated data by agent iMA which encrypted with private key and unknown to any
agent within the host kSH , the control agent kCA accesses the control agent iCA and requests
the public key to decrypt the agent iMA data, control agent iCA provides agent kCA with public
key for agent iMA . After receiving the public key and decrypt agent iMA data, the agent data
become available to all agents in platform kVLP . However, the control agent kCA assigns a
special label to agent iMA and stores information about it in the agents safe registry replicated
within the system. Thus the trust level in the agent iMA by other agents increases. After returning
agent iMA to his "native" host, it generates a new key pair , )( MA MAi i
Sk Pk , and its control agent
iCA updates its public key, which is stored on the mobile agent security server.
Obviously, the implementation of the system OMAVLS with decentralized security management
improves its reliability and resistance to internal and external information security threats, and also
allows to organize effective agents and system components protection from purposeful influence
malware and spyware agents. The advantages of this embodiment of the MASS, despite the
relatively high communication channels loading and redundancy of stored data, are flexibility,
adaptability and balancing information security load between servers, system nodes and the control
agents.
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8. CONCLUSIONS
During the study the main challenges and threats to various kinds of information security problem-
oriented in open distributed multi-agent information systems were analyze. The modern
approaches aimed to solve problems related to ensuring agents information security and multi-
agent systems, Develop the operation principles and the general structure of information security in
OMAVLE, Propose various information security approaches in OMAVLE based on the system
implementation with centralized and decentralized security management, as well as the behaviour
simulations of their active components (agents).
The proposed approaches constitute the subsystem information security basis and implemented as
a complex programs within the e-learning activities informational support representing OMAVLE.
Mobile software agents and proposed arrangements for information security management
implemented software tools in development agents environment.
ACKNOWLEDGEMENT
The authors are grateful to the Applied Science University, Amman, Jordan, for the full financial
support granted to this research.
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Authors
Dr. Zahi A. M. Abu Sarhan Received the M.S. and PhD degrees in Computerized
Control Automated Systems and Progressive Information Technologies from Kharkov
National University of Radio Electronics, Kharkov in 1998 and 2004, respectively.
During 2004-2008, I was an Assistant Professor at the Economics and Administrative
science/ MIS Department at Applied Science University. Since 2008, I am an Assistant
Professor at the Faculty of Information technology, Applied Science University in
Jordan. Research interests include: Information system reengineering, Service oriented
architecture, software agents, agents theory, agents behavior.
As'ad Mahmoud As'ad Alnaser received a Ph.D in computer engineering from
National Technical University of Ukraine āKyiv Polytechnic Instituteā. I am currently
an assistant professor of the Department of Computer Science at Al-Balqa' Applied
University, Ajlun University College. My research areas include wireless and mobile
networks, Internet protocols, and Image processing.