Network Behavioral Analysis for Zero-Day Malware Detection – A Case Study

Autor:	Oussama Boudar, Marc André Allaire, Karim Ganame, Ghassen Zagdene
Rok vydání:	2017
Předmět:	Behavioral analysis Computer science Ransomware Malware Data breach computer.software_genre Computer security computer Zero (linguistics) Cyber threats
Zdroj:	Lecture Notes in Computer Science ISBN: 9783319691541 ISDDC
Popis:	The number of cyber threats is constantly increasing. In 2013, 200,000 malicious tools were identified each day by antivirus vendors. This figure rose to 800,000 per day in 2014 and then to 1.8 million per day in 2016! The bar of 3 million per day will be crossed in 2017. Traditional security tools (mainly signature-based) show their limits and are less and less effective to detect these new cyber threats. Detecting never-seen-before or zero-day malware, including ransomware, efficiently requires a new approach in cyber security management. This requires a move from signature-based detection to behavior-based detection. We have developed a data breach detection system named CDS using Machine Learning techniques which is able to identify zero-day malware by analyzing the network traffic.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::74ae4da606cd91ed5cdd87a33a4b0f30 https://doi.org/10.1007/978-3-319-69155-8_13 Zobrazit plný text záznamu