Social Engineering Attack Detection Using Machine Learning: Text Phishing Attack

Online Social Network Phishing Attack

Rule-Based Phishing Attack Detection

The World Wide Web has become the hotbed of a multi-billion dollar underground economy among cyber criminals whose victims range from individual Internet users to large corporations and even government organizations. As phishing attacks are increasingly being used by criminals to facilitate their cyber schemes, it is important to develop effective phishing detection tools. In this paper, we pro...

Application Layer DDOS Attack Detection Using Hybrid Machine Learning Approach

Application Layer Distributed Denial of Service (App-DDoS) attack has become a major threat to web security. Attack detection is difficult as they mimic genuine user request. This paper proposes a clustering based correlation approach for detecting application layer DDoS attack on HTTP protocol. Proposed approach has two main modules ----Flow monitoring module and User behavior monitoring modul...

Emotion Detection in Persian Text; A Machine Learning Model

This study aimed to develop a computational model for recognition of emotion in Persian text as a supervised machine learning problem. We considered Pluthchik emotion model as supervised learning criteria and Support Vector Machine (SVM) as baseline classifier. We also used NRC lexicon and contextual features as training data and components of the model. One hundred selected texts including pol...

Cyber Attack Detection and Classification Using Parallel Support Vector Machine

Cyber attack is becoming a critical issue of organizational information systems. A number of cyber attack detection and classification methods have been introduced with different levels of success that is used as a countermeasure to preserve data integrity and system availability from attacks. The classification of attacks against computer network is becoming a harder problem to solve in the fi...