Demo Data from VLDB 2026 / reviewers in the wild / expert
Ryon Kennedy
dblp:305/4348
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2024
0009-0002-8468-4915ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Security and privacy · 1 · 1 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Network and information security
1 paper |
Systems and software security · 100% | |
| Computer networks
1 paper |
Cellular and mobile networks · 100% |
Topics — the 5 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Cellular and mobile networks
radio access networks |
0.8 | 1 | 2024 | RANsacked: A Domain-Informed Approach for Fuzzing LTE and 5G RAN-Core Interfaces · CCS 2024 |
Systems and software security › vulnerability discovery
fuzzing |
0.8 | 1 | 2024 | RANsacked: A Domain-Informed Approach for Fuzzing LTE and 5G RAN-Core Interfaces · CCS 2024 |
Systems and software security › vulnerability discovery › fuzzing
grammar-based fuzzing |
0.8 | 1 | 2024 | RANsacked: A Domain-Informed Approach for Fuzzing LTE and 5G RAN-Core Interfaces · CCS 2024 |
Systems and software security
vulnerability discovery |
0.8 | 1 | 2024 | RANsacked: A Domain-Informed Approach for Fuzzing LTE and 5G RAN-Core Interfaces · CCS 2024 |
Cellular and mobile networks
5g |
0.2 | 1 | 2024 | RANsacked: A Domain-Informed Approach for Fuzzing LTE and 5G RAN-Core Interfaces · CCS 2024 |
Methods — techniques the papers use, named apart from their topics
coverage-guided fuzzing · 1.5ASN.1 specification compilation · 1.5
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2024 | RANsacked: A Domain-Informed Approach for Fuzzing LTE and 5G RAN-Core InterfacesabstractCellular network infrastructure serves as the backbone of modern mobile wireless communication. As such, cellular cores must be proactively secured against external threats to ensure reliable service. Compromised base station attacks against the core are a rising threat to cellular networks, while user device inputs have long been considered as an attack vector; despite this, few techniques exist to comprehensively test RAN-Core interfaces against malicious input. In this work, we devise a fuzzing framework that performantly fuzzes cellular interfaces accessible from a base station or user device, overcoming several challenges in fuzzing specific to LTE/5G network components. We also introduce ASNFuzzGen, a tool that compiles ASN.1 specifications into structure-aware fuzzing modules, thereby facilitating effective fuzzing exploration of complex cellular protocols. We run fuzzing campaigns against seven open-source and commercial cores and discover 119 vulnerabilities, with 93 CVEs assigned. Our results reveal common implementation mistakes across several cores that lead to vulnerabilities, and the successful coordination of patches for these vulnerabilities across several vendors demonstrates the practical impact ASNFuzzGen has on hardening user-exposed cellular systems. Nathaniel Bennett, Weidong Zhu 0002, Benjamin Simon, Ryon Kennedy, William Enck, Patrick Traynor, Kevin R. B. Butler |
CCS | 4 |