Agility maneuvers to mitigate inference attacks on sensed location data

Giuseppe Petracca, Lisa M. Marvel, Ananthram Swami, Trent Ray Jaeger

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Sensed location data is subject to inference attacks by cybercriminals that aim to obtain the exact position of sensitive locations, such as the victim's home and work locations, to launch a variety of different attacks. Various Location-Privacy Preserving Mechanisms (LPPMs) exist to reduce the probability of success of inference attacks on location data. However, such mechanisms have been shown to be less effective when the adversary is informed of the protection mechanism adopted, also known as white-box attacks. We propose a novel approach that makes use of targeted agility maneuvers as a more robust defense against white-box attacks. Agility maneuvers are systematically activated in response to specific system events to rapidly and continuously control the rate of change in system configurations and increase diversity in the space of readings, which would decrease the probability of success of inference attacks by an adversary. Experimental results, performed on a real data set, show that the adoption of agility maneuvers reduces the probability of success of white-box attacks to 2.68% on average, compared to 56.92% when using state-of-the-art LPPMs.

Original languageEnglish (US)
Title of host publicationMILCOM 2016 - 2016 IEEE Military Communications Conference
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages259-264
Number of pages6
ISBN (Electronic)9781509037810
DOIs
StatePublished - Dec 22 2016
Event35th IEEE Military Communications Conference, MILCOM 2016 - Baltimore, United States
Duration: Nov 1 2016Nov 3 2016

Publication series

NameProceedings - IEEE Military Communications Conference MILCOM

Other

Other35th IEEE Military Communications Conference, MILCOM 2016
CountryUnited States
CityBaltimore
Period11/1/1611/3/16

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

Cite this

Petracca, G., Marvel, L. M., Swami, A., & Jaeger, T. R. (2016). Agility maneuvers to mitigate inference attacks on sensed location data. In MILCOM 2016 - 2016 IEEE Military Communications Conference (pp. 259-264). [7795336] (Proceedings - IEEE Military Communications Conference MILCOM). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/MILCOM.2016.7795336
Petracca, Giuseppe ; Marvel, Lisa M. ; Swami, Ananthram ; Jaeger, Trent Ray. / Agility maneuvers to mitigate inference attacks on sensed location data. MILCOM 2016 - 2016 IEEE Military Communications Conference. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 259-264 (Proceedings - IEEE Military Communications Conference MILCOM).
@inproceedings{3d7339e60b61426ab204d291c69d51d5,
title = "Agility maneuvers to mitigate inference attacks on sensed location data",
abstract = "Sensed location data is subject to inference attacks by cybercriminals that aim to obtain the exact position of sensitive locations, such as the victim's home and work locations, to launch a variety of different attacks. Various Location-Privacy Preserving Mechanisms (LPPMs) exist to reduce the probability of success of inference attacks on location data. However, such mechanisms have been shown to be less effective when the adversary is informed of the protection mechanism adopted, also known as white-box attacks. We propose a novel approach that makes use of targeted agility maneuvers as a more robust defense against white-box attacks. Agility maneuvers are systematically activated in response to specific system events to rapidly and continuously control the rate of change in system configurations and increase diversity in the space of readings, which would decrease the probability of success of inference attacks by an adversary. Experimental results, performed on a real data set, show that the adoption of agility maneuvers reduces the probability of success of white-box attacks to 2.68{\%} on average, compared to 56.92{\%} when using state-of-the-art LPPMs.",
author = "Giuseppe Petracca and Marvel, {Lisa M.} and Ananthram Swami and Jaeger, {Trent Ray}",
year = "2016",
month = "12",
day = "22",
doi = "10.1109/MILCOM.2016.7795336",
language = "English (US)",
series = "Proceedings - IEEE Military Communications Conference MILCOM",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "259--264",
booktitle = "MILCOM 2016 - 2016 IEEE Military Communications Conference",
address = "United States",

}

Petracca, G, Marvel, LM, Swami, A & Jaeger, TR 2016, Agility maneuvers to mitigate inference attacks on sensed location data. in MILCOM 2016 - 2016 IEEE Military Communications Conference., 7795336, Proceedings - IEEE Military Communications Conference MILCOM, Institute of Electrical and Electronics Engineers Inc., pp. 259-264, 35th IEEE Military Communications Conference, MILCOM 2016, Baltimore, United States, 11/1/16. https://doi.org/10.1109/MILCOM.2016.7795336

Agility maneuvers to mitigate inference attacks on sensed location data. / Petracca, Giuseppe; Marvel, Lisa M.; Swami, Ananthram; Jaeger, Trent Ray.

MILCOM 2016 - 2016 IEEE Military Communications Conference. Institute of Electrical and Electronics Engineers Inc., 2016. p. 259-264 7795336 (Proceedings - IEEE Military Communications Conference MILCOM).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

TY - GEN

T1 - Agility maneuvers to mitigate inference attacks on sensed location data

AU - Petracca, Giuseppe

AU - Marvel, Lisa M.

AU - Swami, Ananthram

AU - Jaeger, Trent Ray

PY - 2016/12/22

Y1 - 2016/12/22

N2 - Sensed location data is subject to inference attacks by cybercriminals that aim to obtain the exact position of sensitive locations, such as the victim's home and work locations, to launch a variety of different attacks. Various Location-Privacy Preserving Mechanisms (LPPMs) exist to reduce the probability of success of inference attacks on location data. However, such mechanisms have been shown to be less effective when the adversary is informed of the protection mechanism adopted, also known as white-box attacks. We propose a novel approach that makes use of targeted agility maneuvers as a more robust defense against white-box attacks. Agility maneuvers are systematically activated in response to specific system events to rapidly and continuously control the rate of change in system configurations and increase diversity in the space of readings, which would decrease the probability of success of inference attacks by an adversary. Experimental results, performed on a real data set, show that the adoption of agility maneuvers reduces the probability of success of white-box attacks to 2.68% on average, compared to 56.92% when using state-of-the-art LPPMs.

AB - Sensed location data is subject to inference attacks by cybercriminals that aim to obtain the exact position of sensitive locations, such as the victim's home and work locations, to launch a variety of different attacks. Various Location-Privacy Preserving Mechanisms (LPPMs) exist to reduce the probability of success of inference attacks on location data. However, such mechanisms have been shown to be less effective when the adversary is informed of the protection mechanism adopted, also known as white-box attacks. We propose a novel approach that makes use of targeted agility maneuvers as a more robust defense against white-box attacks. Agility maneuvers are systematically activated in response to specific system events to rapidly and continuously control the rate of change in system configurations and increase diversity in the space of readings, which would decrease the probability of success of inference attacks by an adversary. Experimental results, performed on a real data set, show that the adoption of agility maneuvers reduces the probability of success of white-box attacks to 2.68% on average, compared to 56.92% when using state-of-the-art LPPMs.

UR - http://www.scopus.com/inward/record.url?scp=85011829427&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85011829427&partnerID=8YFLogxK

U2 - 10.1109/MILCOM.2016.7795336

DO - 10.1109/MILCOM.2016.7795336

M3 - Conference contribution

T3 - Proceedings - IEEE Military Communications Conference MILCOM

SP - 259

EP - 264

BT - MILCOM 2016 - 2016 IEEE Military Communications Conference

PB - Institute of Electrical and Electronics Engineers Inc.

ER -

Petracca G, Marvel LM, Swami A, Jaeger TR. Agility maneuvers to mitigate inference attacks on sensed location data. In MILCOM 2016 - 2016 IEEE Military Communications Conference. Institute of Electrical and Electronics Engineers Inc. 2016. p. 259-264. 7795336. (Proceedings - IEEE Military Communications Conference MILCOM). https://doi.org/10.1109/MILCOM.2016.7795336