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Private Location Sharing for Decentralized Routing services
[article]
2022
arXiv
pre-print
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With this as motivation, we study the problem of using location data for routing services in a privacy-preserving way. ...
Data-driven methodologies offer many exciting upsides, but they also introduce new challenges, particularly in the realm of user privacy. ...
Users traveling in the transportation network share their location data in a privacy-preserving way to estimate the traffic counts in a decentralized manner (upper left). ...
arXiv:2202.13305v2
fatcat:opiegpkqzncgdadbihomnuv5uy
Quantifying the Tradeoff Between Cybersecurity and Location Privacy
[article]
2021
arXiv
pre-print
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When it comes to location-based services (LBS), user privacy protection can be in conflict with security of both users and trips. ...
While LBS providers could adopt privacy preservation mechanisms to obfuscate customer data, the accuracy of vehicle location data and trajectories is crucial for detecting anomalies, especially when machine ...
Location perturbation for differential privacy
inject new (malicious) trips into the Porto dataset considering For perturbing vehicle location data to achieve differential
simplified assumptions ...
arXiv:2105.01262v2
fatcat:yick5s644vfo5pq4rr7svrxcdi
Privacy of Autonomous Vehicles: Risks, Protection Methods, and Future Directions
[article]
2022
arXiv
pre-print
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Such collected large data, treated as the new oil for ML in the data-centric AI era, usually contains a large amount of privacy-sensitive information which is hard to remove or even audit. ...
Although existing privacy protection approaches have achieved certain theoretical and empirical success, there is still a gap when applying them to real-world applications such as autonomous vehicles. ...
Some apps in AVs or connected vehicle networks may easily assess this information, causing privacy concerns for some big companies. ...
arXiv:2209.04022v1
fatcat:b5yvdq5yijf35bqp4qanpwy23y
Guest Editorial Special Issue on Intent-Based Networking for 5G-Envisioned Internet of Connected Vehicles
2021
IEEE transactions on intelligent transportation systems (Print)
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Therefore, to promote productivity, improve efficiency, and ensure the efficient handling of continuous growing data, it requires the support of high computing paradigm that can process the data with minimum ...
Moreover, with the development of massive multiple-input-multiple-output (MIMO), non-orthogonal multiple access (NOMA), terahertz (THz) frequencies, millimeterwave (mmWave), and heterogeneous networks ...
The vehicle's sensory data contain sensitive information, such as location and speed, which could violate the users' privacy if they are leaked with no perturbation. ...
doi:10.1109/tits.2021.3101259
fatcat:gwasd62i7jdkfn4vjkvtenqejm
Privacy Challenges with Protecting Live Vehicular Location Context
2020
IEEE Access
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For example, techniques such as [96] which provides location privacy in cellular networks using pseudonyms would need to collaborate with a vehicle to schedule pseudonym changes. ...
Therefore, transportation networks will deploy Intelligent Transportation Systems (ITSs) to manage these vehicles. ...
doi:10.1109/access.2020.3038533
fatcat:6uqpvvehonbwzfh5ybt6ezsvdu
Privacy in the Smart City—Applications, Technologies, Challenges, and Solutions
2018
IEEE Communications Surveys and Tutorials
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We therefore systematize the application areas, enabling technologies, privacy types, attackers and data sources for the attacks, giving structure to the fuzzy term "smart city". ...
This overwhelming complexity is one reason why holistic privacy protection only rarely enters the picture. ...
[210] to prevent location semantics attacks against k-anonymity Internet of Things Cluster IoT data streams and only release clusters with at least k members [211] Differential Privacy Open Data Release ...
doi:10.1109/comst.2017.2748998
fatcat:q2iwcfkjevgrpe7vjxt5ugvrjy
Trust but Verify: Cryptographic Data Privacy for Mobility Management
[article]
2021
arXiv
pre-print
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2021 pre-print arXiv:2104.07768v3 fatcat:ymwpmk4ee5dpjg3wgof2avm2saOther Versions
In the context of transportation research, mobility data can provide Municipal Authorities (MA) with insights on how to operate, regulate, or improve the transportation network. ...
The era of Big Data has brought with it a richer understanding of user behavior through massive data sets, which can help organizations optimize the quality of their services. ...
Such disputes highlight the need for privacy-preserving data analysis tools in transportation. ...
arXiv:2104.07768v4
fatcat:eyzfgip5ufgepd3gqhthfttyam
Blockchain for the Internet of Vehicles towards Intelligent Transportation Systems: A Survey
[article]
2020
arXiv
pre-print
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Internet of Vehicles (IoV) is an emerging concept that is believed to help realise the vision of intelligent transportation systems (ITS). ...
IoV enables the integration of smart vehicles with the Internet and system components attributing to their environment such as public infrastructures, sensors, computing nodes, pedestrians and other vehicles ...
Furthermore, differential privacy also offers location privacy in real-time within the IoV scenarios. ...
arXiv:2007.06022v1
fatcat:j7zjypmq3jhzjeqejeedjgdepa
Differential Privacy in Cognitive Radio Networks: A Comprehensive Survey
[article]
2021
arXiv
pre-print
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In order to preserve this privacy leakage, various privacy preserving strategies have been developed by researchers, and according to us differential privacy is the most significant among them. ...
Various capabilities of CR nodes depend upon efficient and continuous reporting of data with each other and centralized base stations, which in turn can cause leakage in privacy. ...
117] Preserving Geo-location for CRN participants in collaborative network. ...
arXiv:2111.02011v2
fatcat:a5hique4fvfxrclslvpgda5jyy
Cyber Security of Connected Autonomous Vehicles
2022
European Journal of Science and Technology
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Autonomous systems use lots of IoT sensors data. Connected vehicles have a data-sharing network and they are vulnerable to security attacks. ...
Importance of communication security in vehicular network systems is a soaring issue with the evolving automotive industry day by day. ...
Material and Method
Attacks On Data-Driven Vehicular Network A general summary of the attacks on connected vehicle network presented under this heading. ...
doi:10.31590/ejosat.1039449
fatcat:2mxrsrxmujdnfb3ccstrdobl7i
A Survey of Location Privacy Preservation in Social Internet of Vehicles
2020
IEEE Access
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LOCATION PRIVACY PROTECTION BASED ON USER ATTRIBUTE INFORMATION Every vehicle driven by user has his/her own identity, which can to some extent directly reflect the identity of the user. ...
location privacy preservation algorithms are analyzed in detail, after which their privacy preservation performance is compared and analyzed. (5) Location privacy preservation remains an active research ...
His research interests include delay/disrupted tolerant networks, opportunistic networks, and video delivery. ...
doi:10.1109/access.2020.3036044
fatcat:ygebciupkfgk7j3p2uehlvfzse
Federated Learning for 6G: Paradigms, Taxonomy, Recent Advances and Insights
[article]
2023
arXiv
pre-print
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By allowing mobile handsets and devices to collaboratively learn a global model without explicit sharing of training data, FL exhibits high privacy and efficient spectrum utilization. ...
Artificial Intelligence (AI) is expected to play an instrumental role in the next generation of wireless systems, such as sixth-generation (6G) mobile network. ...
This approach properly resolves the question of privacy in target localization and location data processing in collaboration with many mobile users. ...
arXiv:2312.04688v1
fatcat:uwut2mfcrzdbdh5z5emhjg2iqa
Towards Mobility Data Science (Vision Paper)
[article]
2024
arXiv
pre-print
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With the availability of GPS-equipped mobile devices and other inexpensive location-tracking technologies, mobility data is collected ubiquitously. ...
Mobility data captures the locations of moving objects such as humans, animals, and cars. ...
In recent years, local differential privacy (LDP), the local variant of differential privacy, [63, 95] has become the de facto standard for preserving privacy at data collection stage. ...
arXiv:2307.05717v4
fatcat:vpoeynpefzbj7nyl6xzveuzn6u
Federated Learning for Internet of Things: A Comprehensive Survey
[article]
2021
arXiv
pre-print
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data privacy concerns. ...
We then provide an extensive survey of the use of FL in various key IoT applications such as smart healthcare, smart transportation, Unmanned Aerial Vehicles (UAVs), smart cities, and smart industry. ...
[102]
IoT privacy
preservation
HFL
DNN
Vehicles
Cloud
server
An FL-differential privacy-based
scheme for privacy enhancement
in vehicular IoT. ...
arXiv:2104.07914v1
fatcat:b5wsrfcbynel7jqdxpfw4ftwh4
DIFFERENTIAL PRIVACY FOR IOT-ENABLED CRITICAL INFRASTRUCTURE: A COMPREHENSIVE SURVEY
2021
IEEE Access
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Therefore, Dwork's differential privacy has emerged as the most viable privacy preservation strategy for IoT-enabled critical infrastructure. ...
Adversaries carry out privacy-oriented attacks to gain access to the sensitive and confidential data of critical infrastructure for various self-centered, political and commercial gains. ...
[216] proposed a differentially private strategy to preserve the location information along with the charging times of electric vehicles by leveraging Laplace noise addition mechanism. ...
doi:10.1109/access.2021.3124309
fatcat:vejtyjyrwffeffi7ob2o2svyja
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