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ABOUT IJS |
Information Security is an important aspect of protecting the information society from a wide variety of threats. International Journal of Security (IJS) is a peer review open access online journal that published scientific research related to computer security and cryptography and also reaches out to other branches of the information security sciences. IJS aim to provide research and development results of lasting significance in the theory, design, implementation, analysis, and application of secure computer systems.
The journal is intended to provide scientific knowledge in the field of access control and audit, attacks, security mechanisms, and security service, authentication, authorization, code security including mobile code security, confidentiality, privacy, integrity, design or analysis of security protocols and network and internet security.
IJS provides a platform to computer security experts, practitioners, executives, information security managers, academics, security consultants, executives, administrators, policy makers and graduate students to publish original, innovative and time-critical articles and other information describing research and good practices of important technical work in information security, whether theoretical, applicable, or related to implementation. IJS is also a platform for the sharing of ideas about the meaning and implications of security and privacy, particularly those with important consequences for the technical community. IJS welcome contributions towards the precise understanding of security policies through modeling, as well as the design and analysis of mechanisms for enforcing them, and the architectural principles of software and hardware system implementing them.
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RANDOMLY SELECTED PUBLICATIONS |
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iBaTs: Interactive Bash Shell Adaptive Tutoring System |
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Narasimha Karpoor Shashidhar, Cihan Varol, Keerthi Koneru |
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Department of Computer Science,
Sam Houston State University, Huntsville - United States of America |
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A Survey of Security and Forensic Features In Popular eDiscovery Software Suites |
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Sundar Krishnan, Ashar Neyaz, Narasimha Shashidhar |
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Sam Houston State University - United States of America |
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Classification of Malware Attacks Using Machine Learning
In Decision Tree |
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Abel Yeboah-Ofori |
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School of Architecture, Computing & Engineering, University of East London, London, E16 2GA - United Kingdom |
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A Bring Your Own Device Risk Assessment Model |
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Oonge S. Omboga, Muhambe, T. Mukisa , Ratemo, M. Cyprian |
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School of Computing Department of Information Technology, Maseno University, Maseno, P.O. Box 333-40105 - Kenya |
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