4 citations · 4 across the 10 of their papers we have counts for
14 papers
SPIDES: Information-Flow Control for Browser Agents
Egor Zverev, Juhee Kim, Leon Trampert +4
Browser agents automate complex workflows by reading and acting on arbitrary page content, but this flexibility exposes them to prompt injection attacks and unintended data exfiltr…
Optimizing Agent Planning for Security and Autonomy
Aashish Kolluri, Rishi Sharma, Manuel Costa +5
Indirect prompt injection attacks threaten AI agents that execute consequential actions, motivating deterministic system-level defenses. Such defenses can provably block unsafe act…
A Practical and Secure Byzantine Robust Aggregator
De Zhang Lee, Aashish Kolluri, Prateek Saxena +1
In machine learning security, one is often faced with the problem of removing outliers from a given set of high-dimensional vectors when computing their average. For example, many…
Securing AI Agents with Information-Flow Control
Manuel Costa, Boris Köpf, Aashish Kolluri +6
As AI agents become increasingly autonomous and capable, ensuring their security against vulnerabilities such as prompt injection becomes critical. This paper explores the use of i…
CLUE-MARK: Watermarking Diffusion Models using CLWE
Kareem Shehata, Aashish Kolluri, Prateek Saxena
As AI-generated images become widespread, reliable watermarking is essential for content verification, copyright enforcement, and combating disinformation. Existing techniques rely…
Attacking Byzantine Robust Aggregation in High Dimensions
Sarthak Choudhary, Aashish Kolluri, Prateek Saxena
Training modern neural networks or models typically requires averaging over a sample of high-dimensional vectors. Poisoning attacks can skew or bias the average vectors used to tra…
Scalable Neural Network Training over Distributed Graphs
Aashish Kolluri, Sarthak Choudhary, Bryan Hooi +1
Graph neural networks (GNNs) fuel diverse machine learning tasks involving graph-structured data, ranging from predicting protein structures to serving personalized recommendations…
User-Customizable Transpilation of Scripting Languages
Bo Wang, Aashish Kolluri, Ivica Nikolić +2
A transpiler converts code from one programming language to another. Many practical uses of transpilers require the user to be able to guide or customize the program produced from…
LPGNet: Link Private Graph Networks for Node Classification
Aashish Kolluri, Teodora Baluta, Bryan Hooi +1
Classification tasks on labeled graph-structured data have many important applications ranging from social recommendation to financial modeling. Deep neural networks are increasing…
SynGuar: Guaranteeing Generalization in Programming by Example
Bo Wang, Teodora Baluta, Aashish Kolluri +1
Programming by Example (PBE) is a program synthesis paradigm in which the synthesizer creates a program that matches a set of given examples. In many applications of such synthesis…
Private Hierarchical Clustering in Federated Networks
Aashish Kolluri, Teodora Baluta, Prateek Saxena
Analyzing structural properties of social networks, such as identifying their clusters or finding their most central nodes, has many applications. However, these applications are n…
Localizing Patch Points From One Exploit
Shiqi Shen, Aashish Kolluri, Zhen Dong +2
Automatic patch generation can significantly reduce the window of exposure after a vulnerability is disclosed. Towards this goal, a long-standing problem has been that of patch loc…
Exploiting The Laws of Order in Smart Contracts
Aashish Kolluri, Ivica Nikolic, Ilya Sergey +2
We investigate a family of bugs in blockchain-based smart contracts, which we call event-ordering (or EO) bugs. These bugs are intimately related to the dynamic ordering of contrac…
Finding The Greedy, Prodigal, and Suicidal Contracts at Scale
Ivica Nikolic, Aashish Kolluri, Ilya Sergey +2
Smart contracts---stateful executable objects hosted on blockchains like Ethereum---carry billions of dollars worth of coins and cannot be updated once deployed. We present a new s…