Systematics Review on Detecting Cyberattack Threat by Social Network Analysis and Machine Learning

Abstract

AbstractThis literature review gives an up-to-date overview of studies aimed at analyzing the information contained in social media messages, which reflect malicious activity that threatens cyberspace. This work presented studies aimed at detecting and predicting cyberattacks with the intent of altering, controlling, manipulating, damaging, or affecting victims’ digital services, computing equipment, and communications equipment of the victims. The method used in this systematic literature review is based on the model proposed by Petersen et al. The conclusion from the studies showed that the use of machine learning algorithms, deep learning, and natural language processing tools contributes to better detection of threats in social media. For future research, it is necessary to continue the implementation of the most recent tools of machine learning and deep learning and natural language processing, to improve the effectiveness of the results. The findings of this systematic review will enable the researcher to develop methodologies and mechanisms that could help detect and prevent future cyberattacks.KeywordsSystematics literature reviewCyberattack detectionSocial media analysisTwitter posting analysis