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Igino Corona
Researcher at University of Cagliari
Publications - 32
Citations - 4511
Igino Corona is an academic researcher from University of Cagliari. The author has contributed to research in topics: Malware & Evasion (network security). The author has an hindex of 18, co-authored 32 publications receiving 3637 citations.
Papers
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Book ChapterDOI
Evasion attacks against machine learning at test time
Battista Biggio,Igino Corona,Davide Maiorca,Blaine Nelson,Nedim Srndic,Pavel Laskov,Giorgio Giacinto,Fabio Roli +7 more
TL;DR: This work presents a simple but effective gradient-based approach that can be exploited to systematically assess the security of several, widely-used classification algorithms against evasion attacks.
Book ChapterDOI
Evasion Attacks against Machine Learning at Test Time
Battista Biggio,Igino Corona,Davide Maiorca,Blaine Nelson,Nedim Srndic,Pavel Laskov,Giorgio Giacinto,Fabio Roli +7 more
TL;DR: In this paper, the authors present a simple but effective gradient-based approach that can be exploited to systematically assess the security of several, widely-used classification algorithms against evasion attacks.
Proceedings ArticleDOI
Detecting Malicious Flux Service Networks through Passive Analysis of Recursive DNS Traces
TL;DR: A novel, passive approach based on passive analysis of recursive DNS traffic traces collected from multiple large networks able to detect malicious flux service networks in-the-wild, i.e., as they are accessed by users who fall victims of malicious content advertised through blog spam, instant messaging spam, social website spam, etc., beside email spam.
Journal ArticleDOI
Yes, Machine Learning Can Be More Secure! A Case Study on Android Malware Detection
Ambra Demontis,Marco Melis,Battista Biggio,Davide Maiorca,Daniel Arp,Konrad Rieck,Igino Corona,Giorgio Giacinto,Fabio Roli +8 more
TL;DR: In this article, the authors propose a scalable secure learning paradigm that mitigates the impact of evasion attacks, while only slightly worsening the detection rate in the absence of an attack.
Journal ArticleDOI
Adversarial attacks against intrusion detection systems: Taxonomy, solutions and open issues
TL;DR: This paper will provide a general taxonomy of attack tactics against IDSs, an extensive description of how such attacks can be implemented by exploiting IDS weaknesses at different abstraction levels, and highlight the most promising research directions for the design of adversary-aware, harder-to-defeat IDS solutions.