Smart City Gnosys

Smart city article details

Title	Differential Privacy For Distributed Traffic Monitoring In Smart Cities
ID_Doc	19903
Authors	Gelderie M.; Luff M.; Brodschelm L.
Year	2024
Published	International Conference on Information Systems Security and Privacy, 1
DOI	http://dx.doi.org/10.5220/0012372700003648
Abstract	We study differential privacy in the context of gathering real-time congestion of entire routes in smart cities. Gathering this data is a distributed task that poses unique algorithmic and privacy challenges. We introduce a model of distributed traffic monitoring and define a notion of adjacency for this setting that allows us to employ differential privacy under continual observation. We then introduce and analyze three algorithms that ensure ε differential privacy in this context. First we introduce two algorithms that are built on top of existing algorithmic foundations, and show how they are suboptimal in terms of noise or complexity. We focus, in particular, on whether algorithms can be deployed in our distributed setting. Next, we introduce a novel hybrid scheme that aims to bridge between the first two approaches, retaining an improved computational complexity and a decent noise level. We simulate this algorithm and demonstrate its performance in terms of noise. © 2024 by SCITEPRESS – Science and Technology Publications, Lda.
Author Keywords	Differential Privacy; Smart City; Traffic Monitoring

Similar Articles

Id	Similarity	Authors	Title	Published
41881	0.887	Yang W.; Sun Y.-E.; Huang H.; Du Y.; Huang D.; Li F.; Luo Y.	Persistent Transportation Traffic Volume Estimation With Differential Privacy	Proceedings - 2019 IEEE SmartWorld, Ubiquitous Intelligence and Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Internet of People and Smart City Innovation, SmartWorld/UIC/ATC/SCALCOM/IOP/SCI 2019 (2019)
3803	0.881	Peng F.; Zhao B.; Tang S.; Liu Y.	A Privacy-Preserving Data Aggregation Of Mobile Crowdsensing Based On Local Differential Privacy	ACM International Conference Proceeding Series (2019)
7442	0.876	Gheisari M.; Shojaeian E.; Javadpour A.; Jalili A.; Esmaeili-Najafabadi H.; Bigham B.S.; Vorobeva A.A.; Liu Y.; Rezaei M.	An Agile Privacy-Preservation Solution For Iot-Based Smart City Using Different Distributions	IEEE Open Journal of Vehicular Technology, 4 (2023)
43148	0.872	Wang F.; Li G.; Wang Y.; Rafique W.; Khosravi M.R.; Liu G.; Liu Y.; Qi L.	Privacy-Aware Traffic Flow Prediction Based On Multi-Party Sensor Data With Zero Trust In Smart City	ACM Transactions on Internet Technology, 23, 3 (2023)
19904	0.861	Jia J.; Nishi H.	Differential Privacy Framework Using Secure Computing On Untrusted Servers	Proceedings - 2023 IEEE 6th International Conference on Industrial Cyber-Physical Systems, ICPS 2023 (2023)
709	0.859	Zheng, X; Tian, L; Luo, GC; Cai, ZP	A Collaborative Mechanism For Private Data Publication In Smart Cities	IEEE INTERNET OF THINGS JOURNAL, 7, 9 (2020)
19912	0.857	Gupta S.; Torra V.	Differentially Private Traffic Flow Prediction Using Transformers: A Federated Approach	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 14398 LNCS (2024)
16150	0.856	Guastella D.A.; Pournaras E.	Cooperative Multi-Agent Traffic Monitoring Can Reduce Camera Surveillance	IEEE Access, 11 (2023)
29537	0.856	Tiausas F.; Yasumoto K.; Talusan J.P.; Yamana H.; Yamaguchi H.; Bhattacharjee S.; Dubey A.; Das S.K.	Hprop: Hierarchical Privacy-Preserving Route Planning For Smart Cities	ACM Transactions on Cyber-Physical Systems, 7, 4 (2023)
19911	0.855	Hale M.; Parker K.; Barooah P.; Yazdani K.	Differentially Private Smart Metering: Implementation, Analytics, And Billing	UrbSys 2019 - Proceedings of the 1st ACM International Workshop on Urban Building Energy Sensing, Controls, Big Data Analysis, and Visualization, Part of BuildSys 2019 (2019)