27 citations · 40 across the 8 of their papers we have counts for
11 papers
Do You Trust Your Model? Emerging Malware Threats in the Deep Learning Ecosystem
Dorjan Hitaj, Giulio Pagnotta, Fabio De Gaspari +4
Training high-quality deep learning models is a challenging task due to computational and technical requirements. A growing number of individuals, institutions, and companies incre…
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…
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…
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…