Trajectory Privacy Preservation and Lightweight Blockchain Techniques for Mobility-Centric IoT

Authors

Abdur Bin Shahid, School of Computing annd Information Sciences, Florida International UniversityFollow

Document Type

Dissertation

Degree

Doctor of Philosophy (PhD)

Major/Program

Computer Science

First Advisor's Name

Niki Pissinou

First Advisor's Committee Title

Committee chair

Second Advisor's Name

Sundaraja Sitharama Iyengar

Second Advisor's Committee Title

Committee member

Third Advisor's Name

Deng Pan

Third Advisor's Committee Title

Committee member

Fourth Advisor's Name

Kang K. Yen

Fourth Advisor's Committee Title

Committee member

Fifth Advisor's Name

Leonardo Bobadilla

Fifth Advisor's Committee Title

Committee member

Sixth Advisor's Name

Laurent Njilla

Sixth Advisor's Committee Title

Committee member

Keywords

Internet of Things, Mobile Computing, Location-Based Social Network, Location Privacy, Blockchain, Lightweight, Mobile Sensor, Spatial, Temporal, Storage

Date of Defense

11-15-2019

Abstract

Various research efforts have been undertaken to solve the problem of trajectory privacy preservation in the Internet of Things (IoT) of resource-constrained mobile devices. Most attempts at resolving the problem have focused on the centralized model of IoT, which either impose high delay or fail against a privacy-invading attack with long-term trajectory observation. These proposed solutions also fail to guarantee location privacy for trajectories with both geo-tagged and non-geo-tagged data, since they are designed for geo-tagged trajectories only. While a few blockchain-based techniques have been suggested for preserving trajectory privacy in decentralized model of IoT, they require large storage capacity on resource-constrained devices and can only provide conditional privacy when a set of authorities governs the blockchain. This dissertation addresses these challenges to develop efficient trajectory privacy-preservation and lightweight blockchain techniques for mobility-centric IoT.

We develop a pruning-based technique by quantifying the relationship between trajectory privacy and delay for real-time geo-tagged queries. This technique yields higher trajectory privacy with a reduced delay than contemporary techniques while preventing a long-term observation attack. We extend our study with the consideration of the presence of non-geo-tagged data in a trajectory. We design an attack model to show the spatiotemporal correlation between the geo-tagged and non-geo-tagged data which undermines the privacy guarantee of existing techniques. In response, we propose a methodology that considers the spatial distribution of the data in trajectory privacy-preservation and improves existing solutions, in privacy and usability.

With respect to blockchain, we design and implement one of the first blockchain storage management techniques utilizing the mobility of the devices. This technique reduces the required storage space of a blockchain and makes it lightweight for resource-constrained mobile devices. To address the trajectory privacy challenges in an authority-based blockchain under the short-range communication constraints of the devices, we introduce a silence-based one of the first technique to establish a balance between trajectory privacy and blockchain utility.

The designed trajectory privacy- preservation techniques we established are light- weight and do not require an intermediary to guarantee trajectory privacy, thereby providing practical and efficient solution for different mobility-centric IoT, such as mobile crowdsensing and Internet of Vehicles.

Identifier

FIDC008855

Previously Published In

1. A. R. Shahid, N. Pissinou, S. S. Iyengar, J. Miller, Z. Ding, and T. Lemus. Klap for real-world protection of location privacy. In 2018 IEEE World Congress on Services (SERVICES), pages 17-18, July 2018.
2. A. R. Shahid, N. Pissinou, S. S. Iyengar, and K. Makki. Checkins and photos: Spatiotemporal correlation-based location inference attack and defense in location-based social networks. In 2018 17^th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/ 12th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE), pages 1852-1857, Aug 2018.
3. A. R. Shahid, Niki Pissinou, Laurent Njilla, Edwin Aguilar, and Eric Perez. Demo:towards the development of a di_erentially private lightweight and scalable blockchain for iot. In 2019 16th IEEE International Conference on Mobile Ad-Hoc and Smart Systems (MASS-2019), Monterey, CA, USA, November 2019.
4. A. R. Shahid, Niki Pissinou, Laurent Njilla, Sheila Alemany, Ahmed Imteaj, and Kia Makki. Quantifying location privacy in permissioned blockchain-based internet of things (iot). In The 16th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services (MobiQuitous 2019), Houston, USA, November 2019.
5. A. R. Shahid, Niki Pissinou, Corey Staier, and Rain Kwan. Sensor-Chain: a lightweight scalable blockchain framework for internet of things. In The 2019 IEEE International Conference on Internet of Things (iThings-2019), Atlanta, USA, July 2019.

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 License.

Recommended Citation

Shahid, Abdur Bin, "Trajectory Privacy Preservation and Lightweight Blockchain Techniques for Mobility-Centric IoT" (2019). FIU Electronic Theses and Dissertations. 4308.
https://digitalcommons.fiu.edu/etd/4308