39 citations · 82 across the 13 of their papers we have counts for
17 papers
When Entropy Is Not Enough: Multi-Modal Classification of Encrypted and Compressed Data Fragments
Fabio De Gaspari, Dorjan Hitaj, Samuele Salaris +1
Reliable identification of encrypted data fragments is essential in cybersecurity, with applications to ransomware detection, digital forensics, and large-scale data analysis. Dist…
MAYA: Addressing Inconsistencies in Generative Password Guessing through a Unified Benchmark
William Corrias, Fabio De Gaspari, Dorjan Hitaj +1
Recent advances in generative models have led to their application in password guessing, with the aim of replicating the complexity, structure, and patterns of human-created passwo…
Adversarial Challenges in Network Intrusion Detection Systems: Research Insights and Future Prospects
Sabrine Ennaji, Fabio De Gaspari, Dorjan Hitaj +2
Machine learning has brought significant advances in cybersecurity, particularly in the development of Intrusion Detection Systems (IDS). These improvements are mainly attributed t…
Have You Poisoned My Data? Defending Neural Networks against Data Poisoning
Fabio De Gaspari, Dorjan Hitaj, Luigi V. Mancini
The unprecedented availability of training data fueled the rapid development of powerful neural networks in recent years. However, the need for such large amounts of data leads to…
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…
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…