Tehnički vjesnik, Vol. 29 No. 5, 2022.
Izvorni znanstveni članak
https://doi.org/10.17559/TV-20211227132418
Website Phishing Technique Classification Detection with HSSJAYA Based MLP Training
Erkan Erdemir
; Department of Information Technologies, Tokat Vocational and Technical Anatolian High School (Tokat Mesleki ve Teknik Anadolu Lisesi), Gazi Osman Pasa Bulvari No: 48, 60030 Merkez/Tokat/Turkey
Adem Alpaslan Altun
; Department of Computer Engineering, Faculty of Technology, Konya Selcuk University, 42130 Selcuklu/Konya/Turkey
Sažetak
Website phishing technique is the process of stealing personal information (ID number, social media account information, credit card information etc.) of target users through fake websites that are similar to reality by users who do not have good intentions. There are multiple methods in detecting website phishing technique and one of them is multilayer perceptron (MLP), a type of artificial neural networks. The MLP occurs with at least three layers, the input, at least one hidden layer and the output. Data on the network must be trained by passing over neurons. There are multiple techniques in training the network, one of which is training with metaheuristic algorithms. Metaheuristic algorithms that aim to develop more effective hybrid algorithms by combining the good and successful aspects of more than one algorithm are algorithms inspired by nature. In this study, MLP was trained with Hybrid Salp Swarm Jaya (HSSJAYA) and used to determine whether websites are suspicious, phishing or legal. In order to compare the success of MLP trained with hybrid algorithm, Salp Swarm Algorithm (SSA) and Jaya (JAYA) were compared with MLPs trained with Cuckoo Algorithm (CS), Genetic Algorithm (GA) and Firefly Algorithm (FFA). As a result of the experimental and statistical analysis, it was determined that the MLP trained with HSSJAYA was successful in detecting the website phishing technique according to the results of other algorithms.
Ključne riječi
hybrid salp swarm jaya algorithm; metaheuristic; MLP; website phishing
Hrčak ID:
281686
URI
Datum izdavanja:
15.10.2022.
Posjeta: 1.204 *