6533b870fe1ef96bd12cfb1d

RESEARCH PRODUCT

Twitter Analysis for Real-Time Malware Discovery

Marco MoranaGiuseppe Lo ReFederico ConconeAlessandra De Paola

subject

Settore ING-INF/05 - Sistemi Di Elaborazione Delle Informazioni021110 strategic defence & security studiesSocial networkSocial SensingComputer sciencebusiness.industry0211 other engineering and technologies02 engineering and technologycomputer.software_genreMalware AlertsSocial Sensing; Twitter Analysis; Malware AlertsWorld Wide WebBayes' theoremTwitter Analysi0202 electrical engineering electronic engineering information engineeringMalware020201 artificial intelligence & image processingbusinesscomputerClassifier (UML)

description

In recent years, the increasing number of cyber-attacks has gained the development of innovative tools to quickly detect new threats. A recent approach to this problem is to analyze the content of Social Networks to discover the rising of new malicious software. Twitter is a popular social network which allows millions of users to share their opinions on what happens all over the world. The subscribers can insert messages, called tweet, that are usually related to international news. In this work, we present a system for real-time malware alerting using a set of tweets captured through the Twitter API’s, and analyzed by means of a Bayes naïve classifier. Then, groups of tweets discussing the same topic, e.g, a new malware infection, are summarized in order to produce an alert. Tests have been performed to evaluate the performance of the system and results show the effectiveness of our implementation.

yearjournalcountryeditionlanguage
2017-09-01
http://hdl.handle.net/10447/250720