iTest4ORAN: A Systematic Approach to Diagnostic Testing of Next-Generation Radio Access Networks

Our Mission

Systematically enhance Open Radio Access Network (O-RAN) diagnostic testing with novel instruments on near-complete test coverage, non-intrusive performance/security testing and efficient testing along with the RAN evolution.

Research Focus

	Coverage: We seek to provide comprehensive testing to achieve near-complete test coverage. We focus on uncovering missing test cases in interoperability tests. The key is to address the search space explosion problem by leveraging dependence among multiple procedures and multiple interfaces of RAN software.
	Performance: We propose to enhance performance tests in an non-intrusive manner. We plan to supplement existing performance tests of real applications on commodity 5G devices with full-stack end-to-end performance assessment and scalable stress tests at low overhead.
	Security: We propose to improve security tests to uncover new vulnerabilities rooted in non-atomic executions of security procedures in 3GPP/O-RAN specified RAN. The key is to how to efficiently search for all possible vulnerabilities and attacks, while analyzing their potential damages by assuming realistic threat models.
	Efficiency: We plan to explore a paradigm shift from individual, ad hoc testing to a methodical approach to RAN software testing. We propose to organize test cases in an efficient graph structure, thus avoiding repetitive executions of same steps and enabling parallel execution of independent test branches. In addition, we plan to enable incremental testing for incremental changes with the evolution of specifications.
	Reusability: We will integrate our research outcomes into a toolkit and release it to the community. This toolkit will facilitate conformance/interoperability, end-to-end performance and security tests.

Publication

[MobiCom'25] Sixu Tan, Zeyu Li, Zhutian Liu, Harsh Patel, Zhaowei Tan, Automated Model-Based Fuzzing for 5G O-RAN, Proceedings of the 31st Annual International Conference on Mobile Computing and Networking (MobiCom'25), pp. 201–215, Nov 4 - 8, 2025, Hong Kong, China.


        @inproceedings{tan2025automated,,
        author = {Tan, Sixu and Li, Zeyu and Liu, Zhutian and Patel, Harsh and Tan, Zhaowei},
        title = {Automated Model-Based Fuzzing for 5G O-RAN},
        year = {2025},
        url = {https://doi.org/10.1145/3680207.3723469},
        doi = {10.1145/3680207.3723469},
        booktitle = {Proceedings of the 31st Annual International Conference on Mobile Computing and Networking},
        pages = {201–215},
        numpages = {15},
        location = {Hong Kong, China},
        series = {ACM MOBICOM '25}
        }

People

Chunyi Peng
Faculty
Purdue University

Zhaowei Tan
Faculty
University of California, Riverside

Songwu Lu
Faculty
University of California, Los Angeles

Yanbing Liu Ph.D Candidate Purdue University	Sixu Tan Ph.D Student UC Riverside	Zhutian Liu Ph.D Student UC Riverside	Yifei Xu Ph.D Candidate UCLA
Chenwei Gu Ph.D Student UCLA	Sujala Awasthi MS Student Purdue

Acknowledgement

This project is partially funded by NSF under CNS-2403048, CNS-2403049 and CNS-2403050. NSF