activity
20062024
most citedHow To Break Anonymity of the Netflix Prize Dataset

270 citations · 310 across the 6 of their papers we have counts for

collaborators

18 papers

cs.CR2024

Differential Degradation Vulnerabilities in Censorship Circumvention Systems

Zhen Sun, Vitaly Shmatikov

Several recently proposed censorship circumvention systems use encrypted network channels of popular applications to hide their communications. For example, a Tor pluggable transpo…

cs.CL20234 cited

Language Model Inversion

John X. Morris, Wenting Zhao, Justin T. Chiu +2

Language models produce a distribution over the next token; can we use this information to recover the prompt tokens? We consider the problem of language model inversion and show t…

cs.CL20201 cited

Adversarial Semantic Collisions

Congzheng Song, Alexander M. Rush, Vitaly Shmatikov

We study semantic collisions: texts that are semantically unrelated but judged as similar by NLP models. We develop gradient-based approaches for generating semantic collisions and…

cs.CR2020

You Autocomplete Me: Poisoning Vulnerabilities in Neural Code Completion

Roei Schuster, Congzheng Song, Eran Tromer +1

Code autocompletion is an integral feature of modern code editors and IDEs. The latest generation of autocompleters uses neural language models, trained on public open-source code…

cs.CR2020

De-Anonymizing Text by Fingerprinting Language Generation

Zhen Sun, Roei Schuster, Vitaly Shmatikov

Components of machine learning systems are not (yet) perceived as security hotspots. Secure coding practices, such as ensuring that no execution paths depend on confidential inputs…

cs.CR2020

Blind Backdoors in Deep Learning Models

Eugene Bagdasaryan, Vitaly Shmatikov

We investigate a new method for injecting backdoors into machine learning models, based on compromising the loss-value computation in the model-training code. We use it to demonstr…