Collaborative Research: SaTC: CORE: Medium: An Anti-tracking and Robocall-free Architecture for Next-G Mobile Networks
- Institution
- Georgia Tech Research Corporation, GA
- Principal investigator
- Angelos D Keromytis
- Funding
- $300K
- Duration
- 2023–2027
Moonbase score
Still being scored
Abstract
Mobile networks have become integral to modern life, providing their users ubiquitous access to voice, text, and data services. However, this reliance on mobile phones has raised serious privacy concerns, as mobile network operators (MNOs) have the ability to track and profile users. While the 5G system offers some privacy protection through the use of concealed and temporary subscriber identifiers, those with access to MNO databases can still track and profile users. This project addresses this problem by developing a fully functional anonymous mobile access architecture that allows legitimate mobile subscribers to access the network without revealing their real identity. The architecture is designed to disable mobile tracking and profiling using anonymous identifiers ensuring that connections made by the same user at different times cannot be linked. The design also supports critical incumbent mobile network functions, including the identification of a user equipment (UE) and recovery of its mobility history under legal intervention, while giving users control over the level of privacy they risk under their own mobile phone use contexts. The research team aims to achieve the above goal by integrating decentralized identifiers (DID) and anonymous verifiable credential (VC) schemes into the 5G authentication and key agreement (5G-AKA) protocol. Key research tasks to realize this anonymous mobile access architecture include developing a novel secure callee discovery mechanism leveraging DID to handle the voice call function, supporting user accountability and ensuring compatibility with existing lawful interception requirements, enabling flexible billing and rate control by service network, disabling robocall scams, quantifying privacy risks and developing identifier refreshing strategies, and conducting experiments and validation. Successful results for this research will enable anti-tracking capabilities while using mobile networks and offer a new way of thinking about privacy enhancement technologies in the digital world. The outcomes of this research will be made publicly available online, including tutorials, talks, publications, and open-source software. The research team is committed to actively expanding the involvement of underrepresented groups. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
LOADING MOONBASE SCORE
Questions for Georgia Tech Research Corporation
Answered by the team behind this research.
No questions yet. Sign in to ask the first one
Related grants
Same institution, same topic, scored first.
- NSF · Georgia Tech Research Corporation64
Collaborative Research: High-Throughput Exploration of Microstructure-Sensitive Design for Steel Microstructure Optimization to Enhance its Corrosion Resistance in Concrete
Surya R Kalidindi · $245K · 2023–2027
- NSF · Georgia Tech Research Corporation63
Collaborative Research: ATD: a-DMIT: a novel Distributed, MultI-channel, Topology-aware online monitoring framework of massive spatiotemporal data
Yao Xie · $100K · 2023–2026
- NSF · Georgia Tech Research Corporation62
Fourier Light-Field Interrogation of Congenital Heart Disease in vivo
Shu Jia · $600K · 2022–2026