21 citations · 70 across the 19 of their papers we have counts for
19 papers
Cloudy with a Chance of Anomalies: Dynamic Graph Neural Network for Early Detection of Cloud Services' User Anomalies
Revital Marbel, Yanir Cohen, Ran Dubin +2
Ensuring the security of cloud environments is imperative for sustaining organizational growth and operational efficiency. As the ubiquity of cloud services continues to rise, the…
Enhancing Encrypted Internet Traffic Classification Through Advanced Data Augmentation Techniques
Yehonatan Zion, Porat Aharon, Ran Dubin +2
The increasing popularity of online services has made Internet Traffic Classification a critical field of study. However, the rapid development of internet protocols and encryption…
RoBERTa-Augmented Synthesis for Detecting Malicious API Requests
Udi Aharon, Revital Marbel, Ran Dubin +2
Web applications and APIs face constant threats from malicious actors seeking to exploit vulnerabilities for illicit gains. To defend against these threats, it is essential to have…
A Classification-by-Retrieval Framework for Few-Shot Anomaly Detection to Detect API Injection Attacks
Udi Aharon, Ran Dubin, Amit Dvir +1
Application Programming Interface (API) Injection attacks refer to the unauthorized or malicious use of APIs, which are often exploited to gain access to sensitive data or manipula…
CBR -- Boosting Adaptive Classification By Retrieval of Encrypted Network Traffic with Out-of-distribution
Amir Lukach, Ran Dubin, Amit Dvir +1
Encrypted network traffic Classification tackles the problem from different approaches and with different goals. One of the common approaches is using Machine learning or Deep Lear…
Open-Source Framework for Encrypted Internet and Malicious Traffic Classification
Ofek Bader, Adi Lichy, Amit Dvir +2
Internet traffic classification plays a key role in network visibility, Quality of Services (QoS), intrusion detection, Quality of Experience (QoE) and traffic-trend analyses. In o…
Problem-Space Evasion Attacks in the Android OS: a Survey
Harel Berger, Chen Hajaj, Amit Dvir
Android is the most popular OS worldwide. Therefore, it is a target for various kinds of malware. As a countermeasure, the security community works day and night to develop appropr…
When a RF Beats a CNN and GRU, Together -- A Comparison of Deep Learning and Classical Machine Learning Approaches for Encrypted Malware Traffic Classification
Adi Lichy, Ofek Bader, Ran Dubin +2
Internet traffic classification is widely used to facilitate network management. It plays a crucial role in Quality of Services (QoS), Quality of Experience (QoE), network visibili…
Do You Think You Can Hold Me? The Real Challenge of Problem-Space Evasion Attacks
Harel Berger, Amit Dvir, Chen Hajaj +1
Android malware is a spreading disease in the virtual world. Anti-virus and detection systems continuously undergo patches and updates to defend against these threats. Most of the…
A Rotating Proposer Mechanism for Team Formation
Jian Low, Chen Hajaj, Yevgeniy Vorobeychik
We present a rotating proposer mechanism for team formation, which implements a Pareto efficient subgame perfect Nash equilibrium of an extensive-form team formation game.
MaMaDroid2.0 -- The Holes of Control Flow Graphs
Harel Berger, Chen Hajaj, Enrico Mariconti +1
Android malware is a continuously expanding threat to billions of mobile users around the globe. Detection systems are updated constantly to address these threats. However, a backl…
Less is More: Robust and Novel Features for Malicious Domain Detection
Chen Hajaj, Nitay Hason, Nissim Harel +1
Malicious domains are increasingly common and pose a severe cybersecurity threat. Specifically, many types of current cyber attacks use URLs for attack communications (e.g., C\&C,…
A Thousand Words are Worth More Than One Recording: NLP Based Speaker Change Point Detection
O. H. Anidjar, C. Hajaj, A. Dvir +1
Speaker Diarization (SD) consists of splitting or segmenting an input audio burst according to speaker identities. In this paper, we focus on the crucial task of the SD problem whi…
When the Guard failed the Droid: A case study of Android malware
Harel Berger, Chen Hajaj, Amit Dvir
Android malware is a persistent threat to billions of users around the world. As a countermeasure, Android malware detection systems are occasionally implemented. However, these sy…
Adversarial Coordination on Social Networks
Chen Hajaj, Sixie Yu, Zlatko Joveski +1
Decentralized coordination is one of the fundamental challenges for societies and organizations. While extensively explored from a variety of perspectives, one issue which has rece…
Adversarial Task Assignment
Chen Hajaj, Yevgeniy Vorobeychik
The problem of assigning tasks to workers is of long-standing fundamental importance. Examples of this include the classical problem of assigning computing tasks to nodes in a dist…
Adversarial Task Allocation
Chen Hajaj, Yevgeniy Vorobeychik
The problem of allocating tasks to workers is of long standing fundamental importance. Examples of this include the classical problem of assigning computing tasks to nodes in a dis…
Improving Robustness of ML Classifiers against Realizable Evasion Attacks Using Conserved Features
Liang Tong, Bo Li, Chen Hajaj +3
Machine learning (ML) techniques are increasingly common in security applications, such as malware and intrusion detection. However, ML models are often susceptible to evasion atta…
Improving Comparison Shopping Agents' Competence through Selective Price Disclosure
Chen Hajaj, Noam Hazon, David Sarne
The plethora of comparison shopping agents (CSAs) in today's markets enables buyers to query more than a single CSA when shopping, and an inter-CSAs competition naturally arises. W…