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BYOD Security: A New Business Challenge
A taxonomy specifically classifying BYOD security challenges is introduced alongside comprehensive frameworks and solutions which are also analysed to gauge their limitations.
A Linear Genetic Programming Approach for Modeling Electricity Demand Prediction in Victoria
Test results show that while the linear genetic programming method delivered satisfactory results, the neuro fuzzy system performed best for this particular application problem, in terms of accuracy and computation time, as compared to LGP and neural networks.
Intelligent Financial Fraud Detection Practices: An Investigation
This paper presents a comprehensive investigation on financial fraud detection practices using such data mining methods, with a particular focus on computational intelligence-based techniques.
Genetic Programming: A Review of Some Concerns
This paper surveys the major research works in GP from a critical angle and concludes with a general discussion on "code growth" and other critical aspects of GP techniques, while attempting to highlight on future research directions to tackle such problems.
Evolutionary Approaches to Expensive Optimisation
This paper discusses some of the key issues involved with use of approximation in evolutionary algorithm, possible best practices and solutions, and how to ensure reliable approximation.
Countering Social Engineering Through Social Media: An Enterprise Security Perspective
Concerns of social engineering through social media within the enterprise are examined and countermeasures undertaken to stem ensuing risk are explored.
Surrogate based EA for expensive optimization problems
An evolutionary algorithm framework which involves use of surrogate models for fitness function evaluation and a enhanced model which incorporates a multiple-model based learning approach for the support vector machine approximator to counter effects of noise are presented.