Towards robust and low-complexity radiometric fingerprint: PhD forum abstract

ABSTRACT

Authentication is challenging in the IoT because most advanced cryptographic algorithms are difficult to afford by constrained devices expected to run many months or years. Radiometric signatures have been used effectively to identify wireless devices based on imperfections in electronic circuits. This technique is also known as Radio frequency (RF) fingerprinting. Previous work proves the feasibility of this technique but mainly considered static channel conditions. In our current work, we systematically and experimentally study the impact of dynamic and complex channel conditions on the radiometric signatures. The results show a threat to identification accuracy for modulation error-based fingerprinting that was considered channel-resilient. Next step, my research aims at improving the robustness of RF fingerprint systems and make this authentication solution ready for widespread implementation.

References

1. Al-Shawabka and et al. 2020. Exposing the Fingerprint: Dissecting the Impact of the Wireless Channel on Radio Fingerprinting. In INFOCOM IEEE Conference on Computer Communications.
2. Vladimir Brik and et al. 2008. Wireless device identification with radiometric signatures. In Proceedings of the 14th ACM international conference on Mobile computing and networking. 116--127.
3. Pengfei Liu and et al. 2019. Real-time identification of rogue WiFi connections using environment-independent physical features. In INFOCOM IEEE Conference on Computer Communications.
4. Tianhang Zheng and et al. 2019. FID: Function modeling-based data-independent and channel-robust physical-layer identification. In INFOCOM IEEE Conference on Computer Communications.

Index Terms

• Networks

  • Network types

    • Wireless access networks

• Security and privacy

  • Security services