1.5k citations · 2.4k across the 38 of their papers we have counts for
25 papers · 1 filter
Deep-Fake CAPTCHA: Mitigating Next-Generation Social Engineering Attacks
Guy Frankovits, Lior Yasur, Fred M. Grabovski +1
This paper presents DF-CAPTCHA, an active defense against real-time deepfake impersonation in voice and video calls. Instead of passively searching for artifacts, DF-CAPTCHA prompt…
Detokenization Leaks: Reconstructing Local LLM Outputs From Cache Traces
Roy Weiss, Benyamin Konstantinov, Eitam Sheetrit +2
We present a new attack that reconstructs the text generated by locally hosted LLMs by observing CPU cache activity during detokenization. Unlike prior attacks that rely on deploym…
A Few Steps Further: Why Defenses Against Malicious Finetuning Erode Under Continued Training
Itay Zloczower, Eyal Lenga, Gilad Gressel +1
Model providers increasingly release the weights of large language models. Although these models are safety-aligned before release, their safeguards can often be removed by fine-tu…
Who Owns This Agent? Tracing AI Agents Back to Their Owners
Ruben Chocron, Doron Jonathan Ben Chayim, Eyal Lenga +3
AI agents increasingly act autonomously in the world, yet harmful behavior cannot be reliably traced to the account that deployed the agent. This creates an accountability gap acro…
Love, Lies, and Language Models: Investigating AI's Role in Romance-Baiting Scams
Gilad Gressel, Rahul Pankajakshan, Shir Rozenfeld +4
Romance-baiting scams have become a major source of financial and emotional harm worldwide. These operations are run by organized crime syndicates that traffic thousands of people…
ProxyPrints: From Database Breach to Spoof, A Plug-and-Play Defense for Biometric Systems
Yaniv Hacmon, Keren Gorelik, Gilad Gressel +1
Fingerprint recognition systems are widely deployed for authentication and forensic applications, but the security of stored fingerprint data remains a critical vulnerability. Whil…
Memory Backdoor Attacks on Neural Networks
Eden Luzon, Guy Amit, Roy Weiss +3
Neural networks are often trained on proprietary datasets, making them attractive attack targets. We present a novel dataset extraction method leveraging an innovative training tim…
Efficient Model Extraction via Boundary Sampling
Maor Biton Dor, Yisroel Mirsky
This paper introduces a novel data-free model extraction attack that significantly advances the current state-of-the-art in terms of efficiency, accuracy, and effectiveness. Tradit…
The Best Defense is a Good Offense: Countering LLM-Powered Cyberattacks
Daniel Ayzenshteyn, Roy Weiss, Yisroel Mirsky
As large language models (LLMs) continue to evolve, their potential use in automating cyberattacks becomes increasingly likely. With capabilities such as reconnaissance, exploitati…
Counter-Samples: A Stateless Strategy to Neutralize Black Box Adversarial Attacks
Roey Bokobza, Yisroel Mirsky
Our paper presents a novel defence against black box attacks, where attackers use the victim model as an oracle to craft their adversarial examples. Unlike traditional preprocessin…
What Was Your Prompt? A Remote Keylogging Attack on AI Assistants
Roy Weiss, Daniel Ayzenshteyn, Guy Amit +1
AI assistants are becoming an integral part of society, used for asking advice or help in personal and confidential issues. In this paper, we unveil a novel side-channel that can b…
Deepfake CAPTCHA: A Method for Preventing Fake Calls
Lior Yasur, Guy Frankovits, Fred M. Grabovski +1
Deep learning technology has made it possible to generate realistic content of specific individuals. These `deepfakes' can now be generated in real-time which enables attackers to…
DF-Captcha: A Deepfake Captcha for Preventing Fake Calls
Yisroel Mirsky
Social engineering (SE) is a form of deception that aims to trick people into giving access to data, information, networks and even money. For decades SE has been a key method for…
The Security of Deep Learning Defences for Medical Imaging
Moshe Levy, Guy Amit, Yuval Elovici +1
Deep learning has shown great promise in the domain of medical image analysis. Medical professionals and healthcare providers have been adopting the technology to speed up and enha…
Lightweight Collaborative Anomaly Detection for the IoT using Blockchain
Yisroel Mirsky, Tomer Golomb, Yuval Elovici
Due to their rapid growth and deployment, the Internet of things (IoT) have become a central aspect of our daily lives. Unfortunately, IoT devices tend to have many vulnerabilities…
DANTE: A framework for mining and monitoring darknet traffic
Dvir Cohen, Yisroel Mirsky, Yuval Elovici +4
Trillions of network packets are sent over the Internet to destinations which do not exist. This 'darknet' traffic captures the activity of botnets and other malicious campaigns ai…
The Security of IP-based Video Surveillance Systems
Naor Kalbo, Yisroel Mirsky, Asaf Shabtai +1
IP-based Surveillance systems protect industrial facilities, railways, gas stations, and even one's own home. Therefore, unauthorized access to these systems has serious security i…
Physical Layer Encryption using a Vernam Cipher
Yisroel Mirsky, Benjamin Fedidat, Yoram Haddad
Secure communication is a necessity. However, encryption is commonly only applied to the upper layers of the protocol stack. This exposes network information to eavesdroppers, incl…
CT-GAN: Malicious Tampering of 3D Medical Imagery using Deep Learning
Yisroel Mirsky, Tom Mahler, Ilan Shelef +1
In 2018, clinics and hospitals were hit with numerous attacks leading to significant data breaches and interruptions in medical services. An attacker with access to medical records…
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…
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…
HVACKer: Bridging the Air-Gap by Attacking the Air Conditioning System
Yisroel Mirsky, Mordechai Guri, Yuval Elovici
Modern corporations physically separate their sensitive computational infrastructure from public or other accessible networks in order to prevent cyber-attacks. However, attackers…
9-1-1 DDoS: Threat, Analysis and Mitigation
Mordechai Guri, Yisroel Mirsky, Yuval Elovici
The 911 emergency service belongs to one of the 16 critical infrastructure sectors in the United States. Distributed denial of service (DDoS) attacks launched from a mobile phone b…