Receivers location privacy in avionic crowdsourced networks: Issues and countermeasures

Abstract The lack of message encryption characterizing wireless avionic protocols, including Automatic Dependent Surveillance - Broadcast (ADS-B), recently favored the rise of a few communities that, gathering data collected by receivers at the ground or in space, offer advanced services, while at the same time releasing the cited data to the public. In this context, hiding the location of an ADS-B receiver could be useful for several reasons, including military and privacy aspects. Therefore, taking into account these considerations, the data provided by a few antennas in one of the most popular crowdsourcing platforms, Opensky Network, are released removing any information that could lead to their direct location identification. In this manuscript, we investigate the effectiveness of protecting location privacy in avionic crowdsourced networks. As a worst-case scenario, we demonstrate that, when a feasible number of receivers are deployed in the same area of a protected one, due to the nature of involved ADS-B data, standard time-based localization schemes can identify the location of any protected receiver. Our model, applied to real data, can identify the location of a protected receiver with an error ranging from 0.9 km to 2.6 km, depending on the target sensor—while the location uncertainty induced by the anonymization technique was expected to be of approximately 450 km. Our findings, supported by an extensive experimental campaign run over real data, apply to a variety of potentially protected receivers. Moreover, we also provide effective countermeasures to increase receivers’ location privacy. Finally, we discuss the trade-offs implied by the cited countermeasures, showing that it is possible to increase location privacy while not decreasing data utility.

[1]  Roberto Di Pietro,et al.  GNSS spoofing detection via opportunistic IRIDIUM signals , 2020, WISEC.

[2]  Roger Wattenhofer,et al.  Indoor Localization with Aircraft Signals , 2017, SenSys.

[3]  Ivan Martinovic,et al.  Bringing up OpenSky: A large-scale ADS-B sensor network for research , 2014, IPSN-14 Proceedings of the 13th International Symposium on Information Processing in Sensor Networks.

[4]  Roberto Di Pietro,et al.  SOS: Standard-Compliant and Packet Loss Tolerant Security Framework for ADS-B Communications , 2021, IEEE Transactions on Dependable and Secure Computing.

[5]  Gennaro Boggia,et al.  Tracing a Linearly Moving Node From Asynchronous Time-of-Arrival Measurements , 2016, IEEE Communications Letters.

[6]  Ivan Martinovic,et al.  On the Security of the Automatic Dependent Surveillance-Broadcast Protocol , 2013, IEEE Communications Surveys & Tutorials.

[7]  Ivan Martinovic,et al.  A k-NN-Based Localization Approach for Crowdsourced Air Traffic Communication Networks , 2018, IEEE Transactions on Aerospace and Electronic Systems.

[8]  Arani Bhattacharya,et al.  Short: LSTM-based GNSS Spoofing Detection Using Low-cost Spectrum Sensors , 2020, 2020 IEEE 21st International Symposium on "A World of Wireless, Mobile and Multimedia Networks" (WoWMoM).

[9]  Ling Liu,et al.  Synchronization-Free GPS Spoofing Detection with Crowdsourced Air Traffic Control Data , 2019, 2019 20th IEEE International Conference on Mobile Data Management (MDM).

[10]  Kim-Kwang Raymond Choo,et al.  A Forensically Sound Adversary Model for Mobile Devices , 2015, PloS one.

[11]  Muthu Ramachandran,et al.  Efficient location privacy algorithm for Internet of Things (IoT) services and applications , 2017, J. Netw. Comput. Appl..

[12]  Rui Pinheiro,et al.  Monitoring Meteorological Parameters with Crowdsourced Air Traffic Control Data , 2018, 2018 17th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN).

[13]  Ivan Martinovic,et al.  Lightweight Location Verification in Air Traffic Surveillance Networks , 2015, CPSS@ASIACSS.

[14]  Ivan Martinovic,et al.  The Real First Class? Inferring Confidential Corporate Mergers and Government Relations from Air Traffic Communication , 2018, 2018 IEEE European Symposium on Security and Privacy (EuroS&P).

[15]  Srdjan Capkun,et al.  Investigation of multi-device location spoofing attacks on air traffic control and possible countermeasures , 2016, MobiCom.

[16]  Roberto Di Pietro,et al.  Drive me not: GPS spoofing detection via cellular network: (architectures, models, and experiments) , 2019, WiSec.

[17]  Kim-Kwang Raymond Choo,et al.  The Role of the Adversary Model in Applied Security Research , 2019, IACR Cryptol. ePrint Arch..

[18]  Ivan Martinovic,et al.  Undermining Privacy in the Aircraft Communications Addressing and Reporting System (ACARS) , 2018, Proceedings on Privacy Enhancing Technologies.

[19]  Yuxing Han,et al.  Weighted Centroid Localization Algorithm: Theoretical Analysis and Distributed Implementation , 2011, IEEE Transactions on Wireless Communications.

[20]  Guevara Noubir,et al.  Wireless attacks on aircraft landing systems: demo , 2019, WiSec.

[21]  Jens B. Schmitt,et al.  Secure Motion Verification using the Doppler Effect , 2016, WISEC.

[22]  Gennaro Boggia,et al.  Position and Velocity Estimation of a Non-Cooperative Source From Asynchronous Packet Arrival Time Measurements , 2018, IEEE Transactions on Mobile Computing.

[23]  Andrew Weinert,et al.  Developing a Low Altitude Manned Encounter Model Using ADS-B Observations , 2019, 2019 IEEE Aerospace Conference.

[24]  Stefan Katzenbeisser,et al.  On (The Lack Of) Location Privacy in Crowdsourcing Applications , 2019, USENIX Security Symposium.

[25]  Ivan Martinovic,et al.  OpenSky Report 2018: Assessing the Integrity of Crowdsourced Mode S and ADS-B Data , 2018, 2018 IEEE/AIAA 37th Digital Avionics Systems Conference (DASC).

[26]  Ivan Martinovic,et al.  On the Applicability of Satellite-Based Air Traffic Control Communication for Security , 2019, IEEE Communications Magazine.

[27]  Roberto Di Pietro,et al.  Reliability of ADS-B communications: novel insights based on an experimental assessment , 2019, SAC.

[28]  Rui Pinheiro,et al.  On Perception and Reality in Wireless Air Traffic Communication Security , 2016, IEEE Transactions on Intelligent Transportation Systems.

[29]  Jean-Yves Le Boudec,et al.  Quantifying Location Privacy , 2011, 2011 IEEE Symposium on Security and Privacy.

[30]  Guevara Noubir,et al.  Wireless Attacks on Aircraft Instrument Landing Systems , 2019, USENIX Security Symposium.

[31]  Ivan Martinovic,et al.  OpenSky Report 2019: Analysing TCAS in the Real World using Big Data , 2019, 2019 IEEE/AIAA 38th Digital Avionics Systems Conference (DASC).

[32]  Ivan Martinovic,et al.  Secure Location Verification with a Mobile Receiver , 2016, CPS-SPC '16.

[33]  Mohammed Atiquzzaman,et al.  UAV assistance paradigm: State-of-the-art in applications and challenges , 2020, J. Netw. Comput. Appl..

[34]  Ahmed Abdel Wahab El Marady Enhancing accuracy and security of ADS-B via MLAT assisted-flight information system , 2017, 2017 12th International Conference on Computer Engineering and Systems (ICCES).

[35]  Anomaly Detection using GANs in OpenSky Network , 2018 .

[36]  Hans-Peter Kriegel,et al.  LOF: identifying density-based local outliers , 2000, SIGMOD '00.

[37]  Jens B. Schmitt,et al.  Crowd-GPS-Sec: Leveraging Crowdsourcing to Detect and Localize GPS Spoofing Attacks , 2018, 2018 IEEE Symposium on Security and Privacy (SP).

[38]  Miguel A. Martínez-Prieto,et al.  Integrating flight-related information into a (Big) data lake , 2017, 2017 IEEE/AIAA 36th Digital Avionics Systems Conference (DASC).

[39]  Ivan Martinovic,et al.  OpenSky: A swiss army knife for air traffic security research , 2015, 2015 IEEE/AIAA 34th Digital Avionics Systems Conference (DASC).

[40]  Trevor Hastie,et al.  An Introduction to Statistical Learning , 2013, Springer Texts in Statistics.

[41]  Chen Wang,et al.  GPS spoofed or not? Exploiting RSSI and TSS in crowdsourced air traffic control data , 2020, Distributed and Parallel Databases.

[42]  Daniel Delahaye,et al.  Aircraft trajectory recognition via statistical analysis clustering for Suvarnabhumi International Airport , 2020, 2020 22nd International Conference on Advanced Communication Technology (ICACT).

[43]  Christophe Hurter,et al.  FiberClay: Sculpting Three Dimensional Trajectories to Reveal Structural Insights , 2019, IEEE Transactions on Visualization and Computer Graphics.

[44]  Duminda Wijesekera,et al.  ADS-Bsec: A Holistic Framework to Secure ADS-B , 2018, IEEE Transactions on Intelligent Vehicles.

[45]  Fabio Ricciato,et al.  Nanosecond-Precision Time-of-Arrival Estimation for Aircraft Signals with Low-Cost SDR Receivers , 2018, 2018 17th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN).

[46]  Abderrahim Benslimane,et al.  On location-privacy in opportunistic mobile networks, a survey , 2018, J. Netw. Comput. Appl..

[47]  Goo-Rak Kwon,et al.  Beacon based indoor positioning system using weighted centroid localization approach , 2016, 2016 Eighth International Conference on Ubiquitous and Future Networks (ICUFN).

[48]  Ivan Martinovic,et al.  Realities and challenges of nextgen air traffic management: the case of ADS-B , 2014, IEEE Communications Magazine.

[49]  Christina Pöpper,et al.  MAVPro: ADS-B message verification for aviation security with minimal numbers of on-ground sensors , 2020, WISEC.

[50]  Victor I. Chang,et al.  User-defined privacy location-sharing system in mobile online social networks , 2017, J. Netw. Comput. Appl..