Energy-Aware RFID Authentication in Edge Computing

Internet of Things (IoT) devices are basic units in edge computing. Denial of service (DoS) attack is a great threat to low-cost IoT devices, even worse in privacy-preserving authentication protocols for radio frequency identification (RFID) tags. During DoS attacks, the attacker consumes the legal states in a target tag by continuous scanning and further observes its behavior in authentication to break privacy. Due to lack of adequate energy and computing power, it is hard for passive backscattering RFID tags to defend against DoS attacks. In this work, we cast a new insight on the DoS attacks to RFID tags and leverage the malicious scanning behavior as a new energy source. In this way, a passive tag gains more and more energy and can afford more and more complex cryptography computation under a DoS attack. Finally, the victim tag with adequate energy achieves to complete the complicated public key cryptographic computations and defend against the DoS attack. We further propose a protocol, namely the RUND protocol. We define the tracking privacy model and introduce in the notion of tracking interval to define the tracking privacy other than indistinguishable privacy. To guarantee the security and tracking privacy properties of our protocol, we propose 3 rules as designing guidelines. The analysis shows that our approach can achieve $O$ (1) efficiency while providing DoS-defending privacy-preserving authentication. Furthermore, with proper parameters our approach can save about 40% boosting time at least, compared to the directly charging for public key cryptographic computation method.

[1]  Deepak Hanamant Mane Energy-Harvested Lightweight Cryptosystems , 2014 .

[2]  Joarder Kamruzzaman,et al.  Security and Privacy in RFID Systems , 2013 .

[3]  Kevin Fu,et al.  On the limits of effective hybrid micro-energy harvesting on mobile CRFID sensors , 2010, MobiSys '10.

[4]  Sozo Inoue,et al.  A Secure High-Speed Identification Scheme for RFID Using Bloom Filters , 2008, 2008 Third International Conference on Availability, Reliability and Security.

[5]  Lei Yang,et al.  Tagoram: real-time tracking of mobile RFID tags to high precision using COTS devices , 2014, MobiCom.

[6]  Yuyu Yin,et al.  QoS Prediction for Web Service Recommendation with Network Location-Aware Neighbor Selection , 2016, Int. J. Softw. Eng. Knowl. Eng..

[7]  Jian Wan,et al.  Location-Aware Service Recommendation With Enhanced Probabilistic Matrix Factorization , 2018, IEEE Access.

[8]  Jianfeng Ma,et al.  Attack gives me power: DoS-defending constant-time privacy-preserving authentication of low-cost devices such as backscattering RFID tags , 2016, MSCC '16.

[9]  Roc Berenguer,et al.  Battery-less Wireless Sensors Based on Low Power UHF RFID Tags , 2013 .

[10]  Jian Su,et al.  SLAP: Succinct and Lightweight Authentication Protocol for low-cost RFID system , 2018, Wirel. Networks.

[11]  Alex S. Taylor,et al.  Rethinking RFID: awareness and control for interaction with RFID systems , 2010, CHI.

[12]  Xiaowen Zhang,et al.  Implementation and performance testing of the SQUASH RFID authentication protocol , 2010, 2010 IEEE Long Island Systems, Applications and Technology Conference.

[13]  Gildas Avoine,et al.  Privacy-Friendly Authentication in RFID Systems: On Sublinear Protocols Based on Symmetric-Key Cryptography , 2013, IEEE Transactions on Mobile Computing.

[14]  Lei Yang,et al.  Proactive Batch Authentication: Fishing Counterfeit RFID Tags in Muddy Waters , 2019, IEEE Internet of Things Journal.

[15]  Yueshen Xu,et al.  QoS Prediction for Service Recommendation with Deep Feature Learning in Edge Computing Environment , 2019, Mob. Networks Appl..

[16]  Yuanqing Zheng,et al.  PLACE: Physical Layer Cardinality Estimation for Large-Scale RFID Systems , 2015, IEEE/ACM Transactions on Networking.

[17]  Yueshen Xu,et al.  Network Location-Aware Service Recommendation with Random Walk in Cyber-Physical Systems , 2017, Sensors.

[18]  Joshua R. Smith,et al.  Design of a Passively-Powered, Programmable Sensing Platform for UHF RFID Systems , 2007, 2007 IEEE International Conference on RFID.

[19]  Bart Preneel,et al.  Proper RFID Privacy: Model and Protocols , 2014, IEEE Transactions on Mobile Computing.

[20]  Yunhao Liu,et al.  OTrack: Order tracking for luggage in mobile RFID systems , 2013, 2013 Proceedings IEEE INFOCOM.

[21]  Serge Vaudenay,et al.  On Privacy Models for RFID , 2007, ASIACRYPT.

[22]  Yucong Duan,et al.  Probabilistic Model Checking-Based Service Selection Method for Business Process Modeling , 2017, Int. J. Softw. Eng. Knowl. Eng..

[23]  Lei Yang,et al.  Analog On-Tag Hashing: Towards Selective Reading as Hash Primitives in Gen2 RFID Systems , 2017, MobiCom.

[24]  Yucong Duan,et al.  Toward service selection for workflow reconfiguration: An interface-based computing solution , 2018, Future Gener. Comput. Syst..

[25]  Bruno Blanchet,et al.  Automatic verification of correspondences for security protocols , 2008, J. Comput. Secur..

[26]  Srdjan Capkun,et al.  Physical-layer identification of UHF RFID tags , 2010, MobiCom.

[27]  Jianfeng Ma,et al.  MAP: Towards Authentication for Multiple Tags , 2013, Int. J. Distributed Sens. Networks.

[28]  Kevin Fu,et al.  Maximalist Cryptography and Computation on the WISP UHF RFID Tag , 2013 .

[29]  David Wetherall,et al.  Ambient backscatter: wireless communication out of thin air , 2013, SIGCOMM.

[30]  Jung Hee Cheon,et al.  Reducing RFID reader load with the meet-in-the-middle strategy , 2012, Journal of Communications and Networks.

[31]  David Wetherall,et al.  Dewdrop: An Energy-Aware Runtime for Computational RFID , 2011, NSDI.

[32]  Yueshen Xu,et al.  Collaborative QoS Prediction for Mobile Service with Data Filtering and SlopeOne Model , 2017, Mob. Inf. Syst..

[33]  Wei Xi,et al.  CBID: A Customer Behavior Identification System Using Passive Tags , 2014, 2014 IEEE 22nd International Conference on Network Protocols.

[34]  Jacob Sorber,et al.  Timely Execution on Intermittently Powered Batteryless Sensors , 2017, SenSys.

[35]  Lei Yang,et al.  Identification-free batch authentication for RFID tags , 2010, The 18th IEEE International Conference on Network Protocols.

[36]  Tony Q. S. Quek,et al.  Lightweight and Practical Anonymous Authentication Protocol for RFID Systems Using Physically Unclonable Functions , 2018, IEEE Transactions on Information Forensics and Security.

[37]  Gildas Avoine,et al.  Time Measurement Threatens Privacy-Friendly RFID Authentication Protocols , 2010, RFIDSec.

[38]  Koutarou Suzuki,et al.  Cryptographic Approach to “Privacy-Friendly” Tags , 2003 .

[39]  Matthew Hicks,et al.  Clank: Architectural support for intermittent computation , 2017, 2017 ACM/IEEE 44th Annual International Symposium on Computer Architecture (ISCA).

[40]  Levente Buttyán,et al.  Optimal Key-Trees for Tree-Based Private Authentication , 2006, Privacy Enhancing Technologies.

[41]  Lei Yang,et al.  Perceiving the Slightest Tag Motion beyond Localization , 2015, IEEE Transactions on Mobile Computing.

[42]  Andrey Bogdanov,et al.  Hash Functions and RFID Tags: Mind the Gap , 2008, CHES.

[43]  Basel Alomair,et al.  Scalable RFID Systems: A Privacy-Preserving Protocol with Constant-Time Identification , 2012, IEEE Trans. Parallel Distributed Syst..

[44]  Brandon Lucia,et al.  Chain: tasks and channels for reliable intermittent programs , 2016, OOPSLA.

[45]  Philippe Oechslin,et al.  Reducing Time Complexity in RFID Systems , 2005, Selected Areas in Cryptography.

[46]  Norbert Felber,et al.  ECC Is Ready for RFID - A Proof in Silicon , 2008, Selected Areas in Cryptography.

[47]  Farinaz Koushanfar,et al.  Idetic: A high-level synthesis approach for enabling long computations on transiently-powered ASICs , 2013, 2013 IEEE International Conference on Pervasive Computing and Communications (PerCom).

[48]  Kevin Fu,et al.  Mementos: system support for long-running computation on RFID-scale devices , 2011, ASPLOS XVI.