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Computer Science

D-Index
45
Citations
10202
World Ranking
7111
National Ranking
3119

Overview

Roberto Perdisci is affiliated with the University of Georgia in the United States and has contributed extensively to the field of computer science, with a particular focus on information systems, signal processing, computer networks and communications, artificial intelligence, and electrical and electronic engineering. Their research spans several subfields along with multiple topics related to network security and advanced technologies.

Their main fields of study include:

  • Computer Science

The primary subfields of study are:

  • Information Systems
  • Signal Processing
  • Computer Networks and Communications
  • Artificial Intelligence
  • Electrical and Electronic Engineering

Perdisci's work addresses a range of topics within cybersecurity and data protection, notably including:

  • Advanced Malware Detection Techniques
  • Network Security and Intrusion Detection
  • Spam and Phishing Detection
  • Internet Traffic Analysis and Secure E-voting
  • Human Mobility and Location-Based Analysis
  • Privacy-Preserving Technologies in Data
  • Privacy, Security, and Data Protection

Their publication record features papers published predominantly on arXiv (Cornell University), with notable contributions also appearing in venues such as Digital Threats Research and Practice, the Annual Computer Security Applications Conference, and the IEEE Internet of Things Journal. Key recent papers include:

  • "Measuring Abuse in Web Push Advertising," 2020, arXiv (Cornell University)
  • "SENet: Visual Detection of Online Social Engineering Attack Campaigns," 2024, arXiv (Cornell University)
  • "Towards a Practical Differentially Private Collaborative Phone Blacklisting System," 2020, Annual Computer Security Applications Conference
  • "Building a Collaborative Phone Blacklisting System with Local Differential Privacy," 2020, arXiv (Cornell University)
  • "IXmon: Detecting and Analyzing DRDoS Attacks at Internet Exchange Points," 2020, arXiv (Cornell University)

Frequent collaborators in their research include:

  • Karthika Subramani
  • Mustaque Ahamad
  • Martina Lindorfer
  • Alexandros Kapravelos
  • Gianluca Stringhini

Best Publications

  • BotMiner: clustering analysis of network traffic for protocol- and structure-independent botnet detection

    Guofei Gu;Roberto Perdisci;Junjie Zhang;Wenke Lee

  • From throw-away traffic to bots: detecting the rise of DGA-based malware

    Manos Antonakakis;Roberto Perdisci;Yacin Nadji;Nikolaos Vasiloglou

  • Building a dynamic reputation system for DNS

    Manos Antonakakis;Roberto Perdisci;David Dagon;Wenke Lee

  • Behavioral clustering of HTTP-based malware and signature generation using malicious network traces

    Roberto Perdisci;Wenke Lee;Nick Feamster

  • Detecting malware domains at the upper DNS hierarchy

    Manos Antonakakis;Roberto Perdisci;Wenke Lee;Nikolaos Vasiloglou

  • McPAD: A multiple classifier system for accurate payload-based anomaly detection

    Roberto Perdisci;Davide Ariu;Prahlad Fogla;Giorgio Giacinto

  • Method and system for detecting malicious and/or botnet-related domain names

    Roberto Perdisci;Wenke Lee

  • Polymorphic blending attacks

    Prahlad Fogla;Monirul Sharif;Roberto Perdisci;Oleg Kolesnikov

  • Using an Ensemble of One-Class SVM Classifiers to Harden Payload-based Anomaly Detection Systems

    Roberto Perdisci;Guofei Gu;Wenke Lee

  • Misleading worm signature generators using deliberate noise injection

    R. Perdisci;D. Dagon;Wenke Lee;P. Fogla

  • Intrusion detection in computer networks by a modular ensemble of one-class classifiers

    Giorgio Giacinto;Roberto Perdisci;Mauro Del Rio;Fabio Roli

  • Method and system for detecting dga-based malware

    Manos Antonakakis;Roberto Perdisci;Wenke Lee;Ii Nikolaos Vasiloglou

  • Detecting Malicious Flux Service Networks through Passive Analysis of Recursive DNS Traces

    Roberto Perdisci;Igino Corona;David Dagon;Wenke Lee

  • Classification of packed executables for accurate computer virus detection

    Roberto Perdisci;Andrea Lanzi;Wenke Lee

  • McBoost: Boosting Scalability in Malware Collection and Analysis Using Statistical Classification of Executables

    R. Perdisci;A. Lanzi;Wenke Lee

  • HTTPOS: Sealing Information Leaks with Browser-side Obfuscation of Encrypted Flows.

    Xiapu Luo;Peng Zhou;Edmond W. W. Chan;Wenke Lee

  • Detecting stealthy P2P botnets using statistical traffic fingerprints

    Junjie Zhang;Roberto Perdisci;Wenke Lee;Unum Sarfraz

  • Alarm clustering for intrusion detection systems in computer networks

    Roberto Perdisci;Giorgio Giacinto;Fabio Roli

  • Early Detection of Malicious Flux Networks via Large-Scale Passive DNS Traffic Analysis

    R. Perdisci;I. Corona;G. Giacinto

  • SURF: detecting and measuring search poisoning

    Long Lu;Roberto Perdisci;Wenke Lee

  • Notos: Building a Dynamic Reputation System for DNS

    Manos Antonakakis;Roberto Perdisci;David Dagon;Wenke Lee

Frequent Co-Authors

Wenke Lee
Wenke Lee Georgia Institute of Technology
Giorgio Giacinto
Giorgio Giacinto University of Cagliari
David Dagon
David Dagon Georgia Institute of Technology
Xiapu Luo
Xiapu Luo Hong Kong Polytechnic University
Junjie Zhang
Junjie Zhang Oak Ridge National Laboratory
Fabio Roli
Fabio Roli University of Genoa
Nick Feamster
Nick Feamster University of Chicago
Mustaque Ahamad
Mustaque Ahamad Georgia Institute of Technology
Guofei Gu
Guofei Gu Texas A&M University
Fabian Monrose
Fabian Monrose University of North Carolina at Chapel Hill

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