Authors : Neda Najaafi, Mohammadsaeid Zahedi, Fatemeh Mokhtari Esfidvjani and Arash Hedayati
Abstract: In e-commerce, the issue of security and trust has always been one of the most important principles. With the advancement of internet science, e-commerce has also become more advanced, always striving for greater security and trust. Of course, security and trust are not new issues in the area of e-commerce and a variety of techniques have been provided to improve the performance of this business. If an e-commerce business fails to meet the customer’s expectations in terms of security and trust, it would be doomed to fail. Security in e-commerce is the protection of existing assets and information against attacks and unauthorized access to that e-commerce. In this study, it has been tried to prevent such attacks by preventive techniques and strategies and also by providing an artificial immune system based on agents and computational intelligence techniques including fuzzy control and Genetic algorithms. The rules generated by fuzzy logic are taught by Genetic algorithm and finally through these rules, the input patterns are categorized. In this study, the activities are classified into two categories of safe and unsafe and the incorrect boundaries between these activities are reduced by the proposed technique.
Neda Najaafi, Mohammadsaeid Zahedi, Fatemeh Mokhtari Esfidvjani and Arash Hedayati, 2020. A Genetic Fuzzy Model for Investigating Security and Trust in E-Commerce with Genetic Algorithm. Journal of Engineering and Applied Sciences, 15: 1445-1450.