3 citations · 7 across the 6 of their papers we have counts for
7 papers
zkFuzz: Foundation and Framework for Effective Fuzzing of Zero-Knowledge Circuits
Hideaki Takahashi, Jihwan Kim, Suman Jana +1
Zero-knowledge (ZK) circuits enable privacy-preserving computations and are central to many cryptographic protocols. Systems like Circom simplify ZK development by combining witnes…
Detecting Buggy Contracts via Smart Testing
Sally Junsong Wang, Jianan Yao, Kexin Pei +2
Smart contracts are susceptible to critical vulnerabilities. Hybrid dynamic analyses, such as concolic execution assisted fuzzing and foundation model assisted fuzzing, have emerge…
On the Transit Obfuscation Problem
Hideaki Takahashi, Alex Fukunaga
Concealing an intermediate point on a route or visible from a route is an important goal in some transportation and surveillance scenarios. This paper studies the Transit Obfuscati…
AIJack: Let's Hijack AI! Security and Privacy Risk Simulator for Machine Learning
Hideaki Takahashi
This paper introduces AIJack, an open-source library designed to assess security and privacy risks associated with the training and deployment of machine learning models. Amid the…
VFLAIR: A Research Library and Benchmark for Vertical Federated Learning
Tianyuan Zou, Zixuan Gu, Yu He +3
Vertical Federated Learning (VFL) has emerged as a collaborative training paradigm that allows participants with different features of the same group of users to accomplish coopera…
Eliminating Label Leakage in Tree-Based Vertical Federated Learning
Hideaki Takahashi, Jingjing Liu, Yang Liu
Vertical federated learning (VFL) enables multiple parties with disjoint features of a common user set to train a machine learning model without sharing their private data. Tree-ba…
Breaching FedMD: Image Recovery via Paired-Logits Inversion Attack
Hideaki Takahashi, Jingjing Liu, Yang Liu
Federated Learning with Model Distillation (FedMD) is a nascent collaborative learning paradigm, where only output logits of public datasets are transmitted as distilled knowledge,…