Threat Detection in Social Media Networks Using Machine Learning Based Network Analysis

TL;DR

This paper presents a machine learning framework using neural networks to detect malicious activities in social media networks, addressing challenges like data imbalance and noise, and demonstrating high detection performance.

Contribution

It introduces a neural network-based threat detection model tailored for social media networks, improving upon traditional rule-based systems with a data-driven approach.

Findings

High detection accuracy and F1-score

Effective handling of data imbalance and noise

Potential to enhance existing intrusion detection systems

Abstract

The accelerated development of social media websites has posed intricate security issues in cyberspace, where these sites have increasingly become victims of criminal activities including attempts to intrude into them, abnormal traffic patterns, and organized attacks. The conventional rule-based security systems are not always scalable and dynamic to meet such a threat. This paper introduces a threat detection framework based on machine learning that can be used to classify malicious behavior in the social media network environment based on the nature of network traffic. Exploiting a rich network traffic dataset, the massive preprocessing and exploratory data analysis is conducted to overcome the problem of data imbalance, feature inconsistency, and noise. A model of artificial neural network (ANN) is then created to acquire intricate, non-linear tendencies of malicious actions. The proposed model is tested on conventional performance metrics, such as accuracy, accuracy, recall, F1-score, and ROC-AUC, and shows good detection and high levels of strength. The findings suggest that neural network-based solutions have the potential to be used effectively to identify the latent threat dynamics within the context of a large-scale social media network and that they can be employed to complement the existing intrusion detection system and better to conduct proactive cybersecurity operations.