Brendan Dolan-Gavitt

Orcid: 0000-0002-8867-4282

Affiliations:
  • New York University, Brooklyn, NY, USA


According to our database1, Brendan Dolan-Gavitt authored at least 48 papers between 2007 and 2024.

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Bibliography

2024
An Empirical Evaluation of LLMs for Solving Offensive Security Challenges.
CoRR, 2024

2023
Lost at C: Data from the Security-focused User Study.
Dataset, March, 2023

VeriGen: A Large Language Model for Verilog Code Generation.
CoRR, 2023

LLM-assisted Generation of Hardware Assertions.
CoRR, 2023

StarCoder: may the source be with you!
CoRR, 2023

Can deepfakes be created by novice users?
CoRR, 2023

Can Deepfakes be created on a whim?
Proceedings of the Companion Proceedings of the ACM Web Conference 2023, 2023

Lost at C: A User Study on the Security Implications of Large Language Model Code Assistants.
Proceedings of the 32nd USENIX Security Symposium, 2023

Examining Zero-Shot Vulnerability Repair with Large Language Models.
Proceedings of the 44th IEEE Symposium on Security and Privacy, 2023

Homo in Machina: Improving Fuzz Testing Coverage via Compartment Analysis.
Proceedings of the IEEE Conference on Software Testing, Verification and Validation, 2023

Benchmarking Large Language Models for Automated Verilog RTL Code Generation.
Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, 2023

2022
Lost at C: Data from the Security-focused User Study.
Dataset, October, 2022

Code and Dataset for "Examining Zero-Shot Vulnerability Repair with Large Language Models".
Dataset, March, 2022

Beyond the C: Retargetable Decompilation using Neural Machine Translation.
CoRR, 2022

Security Implications of Large Language Model Code Assistants: A User Study.
CoRR, 2022

Pop Quiz! Can a Large Language Model Help With Reverse Engineering?
CoRR, 2022

Characterizing and Improving Bug-Finders with Synthetic Bugs.
Proceedings of the IEEE International Conference on Software Analysis, 2022

Drifuzz: Harvesting Bugs in Device Drivers from Golden Seeds.
Proceedings of the 31st USENIX Security Symposium, 2022

Asleep at the Keyboard? Assessing the Security of GitHub Copilot's Code Contributions.
Proceedings of the 43rd IEEE Symposium on Security and Privacy, 2022

IRQDebloat: Reducing Driver Attack Surface in Embedded Devices.
Proceedings of the 43rd IEEE Symposium on Security and Privacy, 2022

Towards Deceptive Defense in Software Security with Chaff Bugs.
Proceedings of the 25th International Symposium on Research in Attacks, 2022

2021
Copilot CWE Scenarios Dataset.
Dataset, August, 2021

Can OpenAI Codex and Other Large Language Models Help Us Fix Security Bugs?
CoRR, 2021

An Empirical Cybersecurity Evaluation of GitHub Copilot's Code Contributions.
CoRR, 2021

NNoculation: Catching BadNets in the Wild.
Proceedings of the AISec@CCS 2021: Proceedings of the 14th ACM Workshop on Artificial Intelligence and Security, 2021

SoK: Enabling Security Analyses of Embedded Systems via Rehosting.
Proceedings of the ASIA CCS '21: ACM Asia Conference on Computer and Communications Security, 2021

Evaluating Synthetic Bugs.
Proceedings of the ASIA CCS '21: ACM Asia Conference on Computer and Communications Security, 2021

2020
NNoculation: Broad Spectrum and Targeted Treatment of Backdoored DNNs.
CoRR, 2020

Automatic Uncovering of Hidden Behaviors From Input Validation in Mobile Apps.
Proceedings of the 2020 IEEE Symposium on Security and Privacy, 2020

HeapExpo: Pinpointing Promoted Pointers to Prevent Use-After-Free Vulnerabilities.
Proceedings of the ACSAC '20: Annual Computer Security Applications Conference, 2020

2019
The Rode0day to Less-Buggy Programs.
IEEE Secur. Priv., 2019

BadNets: Evaluating Backdooring Attacks on Deep Neural Networks.
IEEE Access, 2019

2018
Chaff Bugs: Deterring Attackers by Making Software Buggier.
CoRR, 2018

Bug synthesis: challenging bug-finding tools with deep faults.
Proceedings of the 2018 ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering, 2018

Fine-Pruning: Defending Against Backdooring Attacks on Deep Neural Networks.
Proceedings of the Research in Attacks, Intrusions, and Defenses, 2018

Malrec: Compact Full-Trace Malware Recording for Retrospective Deep Analysis.
Proceedings of the Detection of Intrusions and Malware, and Vulnerability Assessment, 2018

Peeling the Onion's User Experience Layer: Examining Naturalistic Use of the Tor Browser.
Proceedings of the 2018 ACM SIGSAC Conference on Computer and Communications Security, 2018

2017
BadNets: Identifying Vulnerabilities in the Machine Learning Model Supply Chain.
CoRR, 2017

AutoCTF: Creating Diverse Pwnables via Automated Bug Injection.
Proceedings of the 11th USENIX Workshop on Offensive Technologies, 2017

Lock-in-Pop: Securing Privileged Operating System Kernels by Keeping on the Beaten Path.
Proceedings of the 2017 USENIX Annual Technical Conference, 2017

2016
LAVA: Large-Scale Automated Vulnerability Addition.
Proceedings of the IEEE Symposium on Security and Privacy, 2016

2015
Understanding and protecting closed-source systems through dynamic analysis.
PhD thesis, 2015

Repeatable Reverse Engineering with PANDA.
Proceedings of the 5th Program Protection and Reverse Engineering Workshop, 2015

2013
Tappan Zee (north) bridge: mining memory accesses for introspection.
Proceedings of the 2013 ACM SIGSAC Conference on Computer and Communications Security, 2013

2011
Virtuoso: Narrowing the Semantic Gap in Virtual Machine Introspection.
Proceedings of the 32nd IEEE Symposium on Security and Privacy, 2011

2009
Robust signatures for kernel data structures.
Proceedings of the 2009 ACM Conference on Computer and Communications Security, 2009

2008
Forensic analysis of the Windows registry in memory.
Digit. Investig., 2008

2007
The VAD tree: A process-eye view of physical memory.
Digit. Investig., 2007


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