activity
20162026
most citedA Simple Explanation for the Existence of Adversarial Examples with Small Hamming Distance

70 citations · 79 across the 7 of their papers we have counts for

collaborators

9 papers

cs.CR2026

CryptanalysisBench: Can LLMs do Cryptanalysis?

Lukas Fluri, Avital Shafran, Nicholas Carlini +5

Cryptanalysis - the task of finding attacks against cryptographic schemes - sits at the intersection of mathematical reasoning and cybersecurity, two areas where LLMs have advanced…

cs.CR2026★ 1 cited

Reconstructing Protected Biometric Templates from Binary Authentication Results

Eliron Rahimi, Margarita Osadchy, Orr Dunkelman

Biometric data is considered to be very private and highly sensitive. As such, many methods for biometric template protection were considered over the years -- from biohashing and…

cs.CY2021

COVID-19 Datathon Based on Deidentified Governmental Data as an Approach for Solving Policy Challenges, Increasing Trust, and Building a Community: Case Study

Mor Peleg, Amnon Reichman, Sivan Shachar +9

Triggered by the COVID-19 crisis, Israel's Ministry of Health (MoH) held a virtual Datathon based on deidentified governmental data. Organized by a multidisciplinary committee, Isr…

cs.CR2020★ 4 cited

Fuzzy Commitments Offer Insufficient Protection to Biometric Templates Produced by Deep Learning

Danny Keller, Margarita Osadchy, Orr Dunkelman

In this work, we study the protection that fuzzy commitments offer when they are applied to facial images, processed by the state of the art deep learning facial recognition system…

cs.CG2020

Error Resilient Space Partitioning

Orr Dunkelman, Zeev Geyzel, Chaya Keller +4

A major research area in discrete geometry is to consider the best way to partition the -dimensional Euclidean space under various quality criteria. In this paper…

cs.LG2019★ 70 cited

A Simple Explanation for the Existence of Adversarial Examples with Small Hamming Distance

Adi Shamir, Itay Safran, Eyal Ronen +1

The existence of adversarial examples in which an imperceptible change in the input can fool well trained neural networks was experimentally discovered by Szegedy et al in 2013, wh…

cs.CR2017

Tight Bounds on Online Checkpointing Algorithms

Achiya Bar-On, Itai Dinur, Orr Dunkelman +4

The problem of online checkpointing is a classical problem with numerous applications which had been studied in various forms for almost 50 years. In the simplest version of this p…

cs.CR2016★ 4 cited

HoneyFaces: Increasing the Security and Privacy of Authentication Using Synthetic Facial Images

Mor Ohana, Orr Dunkelman, Stuart Gibson +1

One of the main challenges faced by Biometric-based authentication systems is the need to offer secure authentication while maintaining the privacy of the biometric data. Previous…

cs.CR2016

Breaching the Privacy of Israel's Paper Ballot Voting System

Tomer Ashur, Orr Dunkelman, Nimrod Talmon

An election is a process through which citizens in liberal democracies select their governing bodies, usually through voting. For elections to be truly honest, people must be able…