Hexuan Yu (Virginia Polytechnic Institute and State University), Changlai Du (Virginia Polytechnic Institute and State University), Yang Xiao (University of Kentucky), Angelos Keromytis (Georgia Institute of Technology), Chonggang Wang (InterDigital), Robert Gazda (InterDigital), Y. Thomas Hou (Virginia Polytechnic Institute and State University), Wenjing Lou (Virginia Polytechnic Institute and State University)

Mobile tracking has long been a privacy problem, where the geographic data and timestamps gathered by mobile network operators (MNOs) are used to track the locations and movements of mobile subscribers. Additionally, selling the geolocation information of subscribers has become a lucrative business. Many mobile carriers have violated user privacy agreements by selling users' location history to third parties without user consent, exacerbating privacy issues related to mobile tracking and profiling. This paper presents AAKA, an anonymous authentication and key agreement scheme designed to protect against mobile tracking by honest-but-curious MNOs. AAKA leverages anonymous credentials and introduces a novel mobile authentication protocol that allows legitimate subscribers to access the network anonymously, without revealing their unique (real) IDs. It ensures the integrity of user credentials, preventing forgery, and ensures that connections made by the same user at different times cannot be linked. While the MNO alone cannot identify or profile a user, AAKA enables identification of a user under legal intervention, such as when the MNOs collaborate with an authorized law enforcement agency. Our design is compatible with the latest cellular architecture and SIM standardized by 3GPP, meeting 3GPP's fundamental security requirements for User Equipment (UE) authentication and key agreement processes. A comprehensive security analysis demonstrates the scheme's effectiveness. The evaluation shows that the scheme is practical, with a credential presentation generation taking ~52 ms on a constrained host device equipped with a standard cellular SIM.

View More Papers

Exploring the Influence of Prompts in LLMs for Security-Related...

Weiheng Bai (University of Minnesota), Qiushi Wu (IBM Research), Kefu Wu, Kangjie Lu (University of Minnesota)

Read More

ShapFuzz: Efficient Fuzzing via Shapley-Guided Byte Selection

Kunpeng Zhang (Shenzhen International Graduate School, Tsinghua University), Xiaogang Zhu (Swinburne University of Technology), Xi Xiao (Shenzhen International Graduate School, Tsinghua University), Minhui Xue (CSIRO's Data61), Chao Zhang (Tsinghua University), Sheng Wen (Swinburne University of Technology)

Read More

GhostType: The Limits of Using Contactless Electromagnetic Interference to...

Qinhong Jiang (Zhejiang University), Yanze Ren (Zhejiang University), Yan Long (University of Michigan), Chen Yan (Zhejiang University), Yumai Sun (University of Michigan), Xiaoyu Ji (Zhejiang University), Kevin Fu (Northeastern University), Wenyuan Xu (Zhejiang University)

Read More

The Impact of Workload on Phishing Susceptibility: An Experiment

Sijie Zhuo (University of Auckland), Robert Biddle (University of Auckland and Carleton University, Ottawa), Lucas Betts, Nalin Asanka Gamagedara Arachchilage, Yun Sing Koh, Danielle Lottridge, Giovanni Russello (University of Auckland)

Read More