ReFuzz: Reusing Tests for Processor Fuzzing with Contextual Bandits

Paper

First seen 7/4/2026

Last seen 9/10/2026

Evidence 5 chunks

NEIGHBORHOOD

No graph connections found for this entity yet. It may appear in future ingestion runs.

15 connections

ReFuzz introduces → 100% 3e

The paper introduces ReFuzz as its core contribution, a novel adaptive fuzzing framework.

Chen Chen authored by → 100% 2e

Chen Chen is listed as an author of the ReFuzz paper.

Zaiyan Xu authored by → 100% 2e

Zaiyan Xu is listed as an author of the ReFuzz paper.

Mohamadreza Rostami authored by → 100% 2e

Mohamadreza Rostami is listed as an author of the ReFuzz paper.

David Liu authored by → 100% 2e

David Liu is listed as an author of the ReFuzz paper.

Dileep Kalathil authored by → 100% 2e

Dileep Kalathil is listed as an author of the ReFuzz paper.

Ahmad-Reza Sadeghi authored by → 100% 2e

Ahmad-Reza Sadeghi is listed as an author of the ReFuzz paper.

Jeyavijayan Rajendran authored by → 100% 2e

Jeyavijayan Rajendran is listed as an author of the ReFuzz paper.

Technische Universitat Darmstadt is listed as an institutional affiliation of the paper.

Texas A&M University published by → 100% 1e

Texas A&M University is listed as the primary institutional affiliation of the paper.

Processor Fuzzing uses → 98% 1e

The ReFuzz paper presents research on processor fuzzing.

The ReFuzz paper uses contextual bandits as the core technique.

ReFuzz paper targets improving vulnerability detection on new processors.

hardware security mentions → 90% 1e

The ReFuzz paper is presented in the context of hardware security research.

NDSS 2026 published by → 97% 1e

The ReFuzz paper is published at NDSS 2026.