PhiDMA – A phishing detection model with multi-filter approach

A location-allocation model in the multi-level supply chain with multi-objective evolutionary approach

In the current competitive conditions, all the manufacturers’ efforts are focused on increasing the customer satisfaction as well as reducing the production and delivery costs; thus, there is an increasing concentration on the structure and principles of supply chain (SC). Accordingly, the present research investigated simultaneous optimization of the total costs of a chain and customer satisfa...

Improved Phishing Detection using Model-Based Features

Phishing emails are a real threat to internet communication and web economy. Criminals are trying to convince unsuspecting online users to reveal passwords, account numbers, social security numbers or other personal information. Filtering approaches using blacklists are not completely effective as about every minute a new phishing scam is created. We investigate the statistical filtering of phi...

Detection of Phishing Attacks: A Machine Learning Approach

Melanoma detection with a deep learning model

Background: Skin cancer is one of the most common forms of cancer in the world and melanoma is the deadliest type of skin cancer. Both melanoma and melanocytic nevi begin in melanocytes (cells that produce melanin). However, melanocytic nevi are benign whereas melanoma is malignant. This work proposes a deep learning model for classification of these two lesions.    Methods: In this analytic s...

Trustworthiness testing of phishing websites: A behavior model-based approach

Phishing attacks allure website users to visit fake web pages and provide their personal information. However, testing of phishing websites is challenging. Unlike traditional web-based program testing, we do not know the response of form submissions in advance. There exists lack of efforts to help anti-phishing professionals who manually verify a reported phishing site and take further actions....