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Recessive Social Networking: Preventing Privacy Leakage against Reverse Image Search

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paper

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Recessive Social Networking : Preventing Privacy Leakage against Reverse Image Search. / Zhang, Jiajie; Zhang, Bingsheng; Lin, Jiancheng.

2019 IEEE European Symposium on Security and Privacy Workshops (EuroS&PW). IEEE, 2019. p. 211-219.

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paper

Harvard

Zhang, J, Zhang, B & Lin, J 2019, Recessive Social Networking: Preventing Privacy Leakage against Reverse Image Search. in 2019 IEEE European Symposium on Security and Privacy Workshops (EuroS&PW). IEEE, pp. 211-219. https://doi.org/10.1109/EuroSPW.2019.00030

APA

Zhang, J., Zhang, B., & Lin, J. (2019). Recessive Social Networking: Preventing Privacy Leakage against Reverse Image Search. In 2019 IEEE European Symposium on Security and Privacy Workshops (EuroS&PW) (pp. 211-219). IEEE. https://doi.org/10.1109/EuroSPW.2019.00030

Vancouver

Zhang J, Zhang B, Lin J. Recessive Social Networking: Preventing Privacy Leakage against Reverse Image Search. In 2019 IEEE European Symposium on Security and Privacy Workshops (EuroS&PW). IEEE. 2019. p. 211-219 https://doi.org/10.1109/EuroSPW.2019.00030

Author

Zhang, Jiajie ; Zhang, Bingsheng ; Lin, Jiancheng. / Recessive Social Networking : Preventing Privacy Leakage against Reverse Image Search. 2019 IEEE European Symposium on Security and Privacy Workshops (EuroS&PW). IEEE, 2019. pp. 211-219

Bibtex

@inproceedings{6500d0d964ee409186905611482fd3b9,
title = "Recessive Social Networking: Preventing Privacy Leakage against Reverse Image Search",
abstract = "This work investigates the image privacy problem in the context of social networking under the threat of reverse image search. We introduce a new concept called recessive social networking. Unlike conventional privacy-preserving social networking, in our setting, the aim is to deceive machine learning algorithms that used in reverse image search, while still enabling unaffected ubiquitous social networking among humans. We, for the first time, ultilize adversarial example technique as a defensive mechanism to protect image privacy against content-based image search algorithms in the context of social networking. Finally, rigorous evaluations are conducted to demonstrate the effectiveness, transferability, and robustness of the proposed countermeasure.",
author = "Jiajie Zhang and Bingsheng Zhang and Jiancheng Lin",
note = "{\textcopyright}2019 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. ",
year = "2019",
month = aug,
day = "19",
doi = "10.1109/EuroSPW.2019.00030",
language = "English",
isbn = "9781728130279",
pages = "211--219",
booktitle = "2019 IEEE European Symposium on Security and Privacy Workshops (EuroS&PW)",
publisher = "IEEE",

}

RIS

TY - GEN

T1 - Recessive Social Networking

T2 - Preventing Privacy Leakage against Reverse Image Search

AU - Zhang, Jiajie

AU - Zhang, Bingsheng

AU - Lin, Jiancheng

N1 - ©2019 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.

PY - 2019/8/19

Y1 - 2019/8/19

N2 - This work investigates the image privacy problem in the context of social networking under the threat of reverse image search. We introduce a new concept called recessive social networking. Unlike conventional privacy-preserving social networking, in our setting, the aim is to deceive machine learning algorithms that used in reverse image search, while still enabling unaffected ubiquitous social networking among humans. We, for the first time, ultilize adversarial example technique as a defensive mechanism to protect image privacy against content-based image search algorithms in the context of social networking. Finally, rigorous evaluations are conducted to demonstrate the effectiveness, transferability, and robustness of the proposed countermeasure.

AB - This work investigates the image privacy problem in the context of social networking under the threat of reverse image search. We introduce a new concept called recessive social networking. Unlike conventional privacy-preserving social networking, in our setting, the aim is to deceive machine learning algorithms that used in reverse image search, while still enabling unaffected ubiquitous social networking among humans. We, for the first time, ultilize adversarial example technique as a defensive mechanism to protect image privacy against content-based image search algorithms in the context of social networking. Finally, rigorous evaluations are conducted to demonstrate the effectiveness, transferability, and robustness of the proposed countermeasure.

U2 - 10.1109/EuroSPW.2019.00030

DO - 10.1109/EuroSPW.2019.00030

M3 - Conference contribution/Paper

SN - 9781728130279

SP - 211

EP - 219

BT - 2019 IEEE European Symposium on Security and Privacy Workshops (EuroS&PW)

PB - IEEE

ER -