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Construction of customizable SOA security framework using artificial neural networks
Mohamed Ibrahim, B1, Mohd Fadzil Hassan2.
The Web Services technology for the implementation of Service Oriented Architecture
(SOA) is the preferred choice in the current era of Enterprise Application Integration
(EAI). As Web Services architecture is dynamic and loosely coupled, security aspects
must be considered thoroughly at the time of designing. It is prone for attacks as it
uses XML format for data exchange, which is a plain text. A novel security component
named “Intelligent Security Engine (ISE)” is introduced into the proposed framework
which incorporates Artificial Neural Networks (ANN) Learning Techniques for
supervised knowledge acquisition on security threats of SOA. Thus, the proposed
security framework is capable in the identification of future security vulnerabilities of
SOA and can work effectively even for in-secured cross organizational EAI
environment.
Affiliation:
- Research Scholar & Software Solution Architect, Malaysia
- Universiti Teknologi PETRONAS, Malaysia
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Indexation |
Indexed by |
MyJurnal (2021) |
H-Index
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6 |
Immediacy Index
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0.000 |
Rank |
0 |
Indexed by |
Scopus 2020 |
Impact Factor
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CiteScore (1.4) |
Rank |
Q3 (Engineering (all)) |
Additional Information |
SJR (0.191) |
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