1.5k citations · 2.3k across the 133 of their papers we have counts for
11 papers · 1 filter
Analysis of Location Data Leakage in the Internet Traffic of Android-based Mobile Devices
Nir Sivan, Ron Bitton, Asaf Shabtai
In recent years we have witnessed a shift towards personalized, context-based applications and services for mobile device users. A key component of many of these services is the ab…
MDGAN: Boosting Anomaly Detection Using \\Multi-Discriminator Generative Adversarial Networks
Yotam Intrator, Gilad Katz, Asaf Shabtai
Anomaly detection is often considered a challenging field of machine learning due to the difficulty of obtaining anomalous samples for training and the need to obtain a sufficient…
Piping Botnet - Turning Green Technology into a Water Disaster
Ben Nassi, Moshe Sror, Ido Lavi +3
The current generation of IoT devices is being used by clients and consumers to regulate resources (such as water and electricity) obtained from critical infrastructure (such as ur…
Generation of Automatic and Realistic Artificial Profiles
Abigail Paradise, Dvir Cohen, Asaf Shabtai +1
Online social networks (OSNs) are abused by cyber criminals for various malicious activities. One of the most effective approaches for detecting malicious activity in OSNs involves…
Detecting Cyberattacks in Industrial Control Systems Using Convolutional Neural Networks
Moshe Kravchik, Asaf Shabtai
This paper presents a study on detecting cyberattacks on industrial control systems (ICS) using unsupervised deep neural networks, specifically, convolutional neural networks. The…
Shattered Trust: When Replacement Smartphone Components Attack
Omer Shwartz, Amir Cohen, Asaf Shabtai +1
Phone touchscreens, and other similar hardware components such as orientation sensors, wireless charging controllers, and NFC readers, are often produced by third-party manufacture…
Incentivized Delivery Network of IoT Software Updates Based on Trustless Proof-of-Distribution
Oded Leiba, Yechiav Yitzchak, Ron Bitton +2
The prevalence of IoT devices makes them an ideal target for attackers. To reduce the risk of attacks vendors routinely deliver security updates (patches) for their devices. The de…
N-BaIoT: Network-based Detection of IoT Botnet Attacks Using Deep Autoencoders
Yair Meidan, Michael Bohadana, Yael Mathov +4
The proliferation of IoT devices which can be more easily compromised than desktop computers has led to an increase in the occurrence of IoT based botnet attacks. In order to mitig…
Query-Efficient Black-Box Attack Against Sequence-Based Malware Classifiers
Ishai Rosenberg, Asaf Shabtai, Yuval Elovici +1
In this paper, we present a generic, query-efficient black-box attack against API call-based machine learning malware classifiers. We generate adversarial examples by modifying the…
Vesper: Using Echo-Analysis to Detect Man-in-the-Middle Attacks in LANs
Yisroel Mirsky, Naor Kalbo, Yuval Elovici +1
The Man-in-the-Middle (MitM) attack is a cyber-attack in which an attacker intercepts traffic, thus harming the confidentiality, integrity, and availability of the network. It rema…
Kitsune: An Ensemble of Autoencoders for Online Network Intrusion Detection
Yisroel Mirsky, Tomer Doitshman, Yuval Elovici +1
Neural networks have become an increasingly popular solution for network intrusion detection systems (NIDS). Their capability of learning complex patterns and behaviors make them a…