activity
20172023
most citedSurvey of Machine Learning Techniques for Malware Analysis

571 citations · 578 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CR2023

Towards a Near-real-time Protocol Tunneling Detector based on Machine Learning Techniques

Filippo Sobrero, Beatrice Clavarezza, Daniele Ucci +1

In the very last years, cybersecurity attacks have increased at an unprecedented pace, becoming ever more sophisticated and costly. Their impact has involved both private/public co…

cs.CR2021★ 4 cited

Towards an Automated Pipeline for Detecting and Classifying Malware through Machine Learning

Nicola Loi, Claudio Borile, Daniele Ucci

The constant growth in the number of malware - software or code fragment potentially harmful for computers and information networks - and the use of sophisticated evasion and obfus…

cs.CR2020★ 2 cited

Building a Collaborative Phone Blacklisting System with Local Differential Privacy

Daniele Ucci, Roberto Perdisci, Jaewoo Lee +1

Spam phone calls have been rapidly growing from nuisance to an increasingly effective scam delivery tool. To counter this increasingly successful attack vector, a number of commerc…

cs.CR2017★ 571 cited

Survey of Machine Learning Techniques for Malware Analysis

Daniele Ucci, Leonardo Aniello, Roberto Baldoni

Coping with malware is getting more and more challenging, given their relentless growth in complexity and volume. One of the most common approaches in literature is using machine l…

cs.CR2017★ 1 cited

Android Malware Family Classification Based on Resource Consumption over Time

Luca Massarelli, Leonardo Aniello, Claudio Ciccotelli +3

The vast majority of today's mobile malware targets Android devices. This has pushed the research effort in Android malware analysis in the last years. An important task of malware…