Information Security of Location Estimation - Increasing Trustworthiness

Vulnerabilities of GNSS (Global Navigation Satellite Systems) or non-GNSS based localization include (1) unintended disruptions of the position or timing solution, (2) malicious attack on the physical or virtual infrastructure of the localization engine, (3) theft of information from the localization engine or its associated modules, and (4) loopholes in the policy framework supporting the legal creation and exploitation of location-based applications jeopardizing the privacy of the individual. This paper gives a brief overview to the state-of-the-art in vulnerabilities in localization, including in its technology, security, robustness, privacy, and policy aspects. It discusses the requirements for enhancing the trustworthiness of localization as to overcome a majority of the vulnerabilities. The paper addresses in particular the question of what are the constraints of ensuring continuous logistics of a localization solution and potential solutions. Thus, this paper presents firstly a brief state-of-the-art analysis of vulnerabilities in localization and then focuses on the requirements for enhancing the trustworthiness.

[1]  J. A. Volpe Vulnerability Assessment of the Transportation Infrastructure Relying on the Global Positioning Syst , 2001 .

[2]  Oscar Isoz,et al.  Assessment of GPS L1/Galileo E1 interference monitoring system for the airport environment , 2011 .

[3]  Elisa Bertino,et al.  Anonymous Geo-Forwarding in MANETs through Location Cloaking , 2008, IEEE Transactions on Parallel and Distributed Systems.

[4]  Masafumi Okada,et al.  Motion pattern design satisfying dynamical consistency and differential relations between position, velocity and acceleration , 2013, The SICE Annual Conference 2013.

[5]  Audrey Giremus,et al.  Bayesian detection of interference in satellite navigation systems , 2011, 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[6]  Tony J. Dodd,et al.  Active Bayesian perception for angle and position discrimination with a biomimetic fingertip , 2013, 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[7]  Saeed Daneshmand,et al.  GNSS Interference Mitigation Using Antenna Array Processing , 2013 .

[8]  Sadie Creese,et al.  Building Confidence in Information-Trustworthiness Metrics for Decision Support , 2013, 2013 12th IEEE International Conference on Trust, Security and Privacy in Computing and Communications.

[9]  Bart Preneel,et al.  Location verification using secure distance bounding protocols , 2005, IEEE International Conference on Mobile Adhoc and Sensor Systems Conference, 2005..

[10]  Aruna Seneviratne,et al.  SSIDs in the wild: Extracting semantic information from WiFi SSIDs , 2015, 2015 IEEE 40th Conference on Local Computer Networks (LCN).

[11]  Prasant Mohapatra,et al.  STAMP: Enabling Privacy-Preserving Location Proofs for Mobile Users , 2016, IEEE/ACM Transactions on Networking.

[12]  Frank Kargl,et al.  A location privacy metric for V2X communication systems , 2009, 2009 IEEE Sarnoff Symposium.

[13]  René Landry,et al.  Analysis of GNSS Interference Impact on Society and Evaluation of Spectrum Protection Strategies , 2013 .

[14]  Zhu Han,et al.  Interference Improves PHY Security for Cognitive Radio Networks , 2016, IEEE Transactions on Information Forensics and Security.

[15]  Bernd Eissfeller,et al.  ANALYSIS, DETECTION AND MITIGATION OF INCAR GNSS JAMMER INTERFERENCE IN INTELLIGENT TRANSPORT SYSTEMS , 2013 .

[16]  Fabio Dovis,et al.  Impact and Detection of GNSS Jammers on Consumer Grade Satellite Navigation Receivers , 2016, Proceedings of the IEEE.

[17]  Walid Saad,et al.  Device Fingerprinting in Wireless Networks: Challenges and Opportunities , 2015, IEEE Communications Surveys & Tutorials.

[18]  Alfred Menezes,et al.  Handbook of Applied Cryptography , 2018 .

[19]  Laura Ruotsalainen,et al.  Performance of a MEMS IMU deeply coupled with a GNSS receiver under jamming , 2014, 2014 Ubiquitous Positioning Indoor Navigation and Location Based Service (UPINLBS).

[20]  Srdjan Capkun,et al.  Secure positioning in wireless networks , 2006, IEEE Journal on Selected Areas in Communications.

[21]  Jo Ueyama,et al.  Exploiting the use of machine learning in two different sensor network architectures for indoor localization , 2016, 2016 IEEE International Conference on Industrial Technology (ICIT).

[22]  Dennis M. Akos,et al.  Jamming Detection in GNSS Receivers: Performance Evaluation of Field Trials , 2013 .

[23]  F. Dovis GNSS Interference Threats and Countermeasures , 2015 .

[24]  Todd E. Humphreys,et al.  Receiver-Autonomous Spoofing Detection: Experimental Results of a Multi-Antenna Receiver Defense against a Portable Civil GPS Spoofer , 2009 .

[25]  Martti Kirkko-Jaakkola,et al.  Deeply Coupled GNSS, INS and Visual Sensor Integration for Interference Mitigation , 2014 .

[26]  Alexander Rügamer,et al.  Jamming and Spoofing of GNSS Signals - An Underestimated Risk?! , 2015 .

[27]  Dan Boneh,et al.  Location Privacy via Private Proximity Testing , 2011, NDSS.

[28]  Jian Wang,et al.  Integrity monitoring and risk evaluation for BDS-based train positioning using track map database , 2014, 2014 International Conference on Electromagnetics in Advanced Applications (ICEAA).

[29]  Panagiotis Papadimitratos,et al.  GNSS-based Positioning: Attacks and countermeasures , 2008, MILCOM 2008 - 2008 IEEE Military Communications Conference.

[30]  Kpatcha M. Bayarou,et al.  Short paper: Experimental analysis of misbehavior detection and prevention in VANETs , 2013, 2013 IEEE Vehicular Networking Conference.