39 citations · 177 across the 20 of their papers we have counts for
24 papers
OliVaR: Improving Olive Variety Recognition using Deep Neural Networks
Hristofor Miho, Giulio Pagnotta, Dorjan Hitaj +6
The easy and accurate identification of varieties is fundamental in agriculture, especially in the olive sector, where more than 1200 olive varieties are currently known worldwide.…
DOLOS: A Novel Architecture for Moving Target Defense
Giulio Pagnotta, Fabio De Gaspari, Dorjan Hitaj +3
Moving Target Defense and Cyber Deception emerged in recent years as two key proactive cyber defense approaches, contrasting with the static nature of the traditional reactive cybe…
Minerva: A File-Based Ransomware Detector
Dorjan Hitaj, Giulio Pagnotta, Fabio De Gaspari +2
Ransomware attacks have caused billions of dollars in damages in recent years, and are expected to cause billions more in the future. Consequently, significant effort has been devo…
TATTOOED: A Robust Deep Neural Network Watermarking Scheme based on Spread-Spectrum Channel Coding
Giulio Pagnotta, Dorjan Hitaj, Briland Hitaj +2
Watermarking of deep neural networks (DNNs) has gained significant traction in recent years, with numerous (watermarking) strategies being proposed as mechanisms that can help veri…
FedComm: Federated Learning as a Medium for Covert Communication
Dorjan Hitaj, Giulio Pagnotta, Briland Hitaj +2
Proposed as a solution to mitigate the privacy implications related to the adoption of deep learning, Federated Learning (FL) enables large numbers of participants to successfully…
MalPhase: Fine-Grained Malware Detection Using Network Flow Data
Michal Piskozub, Fabio De Gaspari, Frederick Barr-Smith +2
Economic incentives encourage malware authors to constantly develop new, increasingly complex malware to steal sensitive data or blackmail individuals and companies into paying lar…
PassFlow: Guessing Passwords with Generative Flows
Giulio Pagnotta, Dorjan Hitaj, Fabio De Gaspari +1
Recent advances in generative machine learning models rekindled research interest in the area of password guessing. Data-driven password guessing approaches based on GANs, language…
Reliable Detection of Compressed and Encrypted Data
Fabio De Gaspari, Dorjan Hitaj, Giulio Pagnotta +2
Several cybersecurity domains, such as ransomware detection, forensics and data analysis, require methods to reliably identify encrypted data fragments. Typically, current approach…
Evaluating the Robustness of Geometry-Aware Instance-Reweighted Adversarial Training
Dorjan Hitaj, Giulio Pagnotta, Iacopo Masi +1
In this technical report, we evaluate the adversarial robustness of a very recent method called "Geometry-aware Instance-reweighted Adversarial Training"[7]. GAIRAT reports state-o…
Capture the Bot: Using Adversarial Examples to Improve CAPTCHA Robustness to Bot Attacks
Dorjan Hitaj, Briland Hitaj, Sushil Jajodia +1
To this date, CAPTCHAs have served as the first line of defense preventing unauthorized access by (malicious) bots to web-based services, while at the same time maintaining a troub…
EnCoD: Distinguishing Compressed and Encrypted File Fragments
Fabio De Gaspari, Dorjan Hitaj, Giulio Pagnotta +2
Reliable identification of encrypted file fragments is a requirement for several security applications, including ransomware detection, digital forensics, and traffic analysis. A p…
The Naked Sun: Malicious Cooperation Between Benign-Looking Processes
Fabio De Gaspari, Dorjan Hitaj, Giulio Pagnotta +2
Recent progress in machine learning has generated promising results in behavioral malware detection. Behavioral modeling identifies malicious processes via features derived by thei…
Have You Stolen My Model? Evasion Attacks Against Deep Neural Network Watermarking Techniques
Dorjan Hitaj, Luigi V. Mancini
Deep neural networks have had enormous impact on various domains of computer science, considerably outperforming previous state of the art machine learning techniques. To achieve t…
RADIS: Remote Attestation of Distributed IoT Services
Mauro Conti, Edlira Dushku, Luigi V. Mancini
Remote attestation is a security technique through which a remote trusted party (i.e., Verifier) checks the trustworthiness of a potentially untrusted device (i.e., Prover). In the…
Towards an Active, Autonomous and Intelligent Cyber Defense of Military Systems: the NATO AICA Reference Architecture
Paul Theron, Alexander Kott, Martin Drašar +5
Within the future Global Information Grid, complex massively interconnected systems, isolated defense vehicles, sensors and effectors, and infrastructures and systems demanding ext…
Autonomous Intelligent Cyber-defense Agent (AICA) Reference Architecture. Release 2.0
Alexander Kott, Paul Théron, Martin Drašar +9
This report - a major revision of its previous release - describes a reference architecture for intelligent software agents performing active, largely autonomous cyber-defense acti…
OSSINT - Open Source Social Network Intelligence An efficient and effective way to uncover "private" information in OSN profiles
Giuseppe Cascavilla, Filipe Beato, Andrea Burattin +2
Online Social Networks (OSNs), such as Facebook, provide users with tools to share information along with a set of privacy controls preferences to regulate the spread of informatio…
Know Your Enemy: Stealth Configuration-Information Gathering in SDN
Mauro Conti, Fabio De Gaspari, Luigi V. Mancini
Software Defined Networking (SDN) is a network architecture that aims at providing high flexibility through the separation of the network logic from the forwarding functions. The i…
No Place to Hide that Bytes won't Reveal: Sniffing Location-Based Encrypted Traffic to Track a User's Position
Giuseppe Ateniese, Briland Hitaj, Luigi V. Mancini +2
News reports of the last few years indicated that several intelligence agencies are able to monitor large networks or entire portions of the Internet backbone. Such a powerful adve…
Can't you hear me knocking: Identification of user actions on Android apps via traffic analysis
Mauro Conti, Luigi V. Mancini, Riccardo Spolaor +1
While smartphone usage become more and more pervasive, people start also asking to which extent such devices can be maliciously exploited as "tracking devices". The concern is not…
No NAT'd User left Behind: Fingerprinting Users behind NAT from NetFlow Records alone
Nino Vincenzo Verde, Giuseppe Ateniese, Emanuele Gabrielli +2
It is generally recognized that the traffic generated by an individual connected to a network acts as his biometric signature. Several tools exploit this fact to fingerprint and mo…
Hacking Smart Machines with Smarter Ones: How to Extract Meaningful Data from Machine Learning Classifiers
Giuseppe Ateniese, Giovanni Felici, Luigi V. Mancini +3
Machine Learning (ML) algorithms are used to train computers to perform a variety of complex tasks and improve with experience. Computers learn how to recognize patterns, make unin…
Mapping the File Systems Genome: rationales, technique, results and applications
Roberto Di Pietro, Luigi V. Mancini, Antonio Villani +1
This paper provides evidence of a feature of Hard-Disk Drives (HDDs), that we call File System Genome. Such a feature is originated by the areas where (on the HDD) the file blocks…
The Smallville Effect: Social Ties Make Mobile Networks More Secure Against the Node Capture Attack
Mauro Conti, Roberto Di Pietro, Andrea Gabrielli +2
Mobile Ad Hoc networks, due to the unattended nature of the network itself and the dispersed location of nodes, are subject to several unique security issues. One of the most vexed…