A Road Truncation-Based Location Privacy-Preserving Method against Side-Weight Inference Attack
Taking advantage of precise positioning technology, location-based service (LBS) has brought a lot of convenience to people’s daily life and made the city smarter. However, the LBS applications also bring some challenges to personal location privacy protection. In order to obtain services from LBS p...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-01-01
|
| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/12/3/1107 |
| _version_ | 1797489364589084672 |
|---|---|
| author | Qingyuan Li Hao Wu Xiang Wu Ning Zhao Lan Dong |
| author_facet | Qingyuan Li Hao Wu Xiang Wu Ning Zhao Lan Dong |
| author_sort | Qingyuan Li |
| collection | DOAJ |
| description | Taking advantage of precise positioning technology, location-based service (LBS) has brought a lot of convenience to people’s daily life and made the city smarter. However, the LBS applications also bring some challenges to personal location privacy protection. In order to obtain services from LBS providers, users have to upload their queries including sensitive information, such as identities and locations. This information may be leaked out by the LBS providers or even eavesdropped on by malicious adversaries, which may cause privacy leakage. To tackle this problem, many solutions have been investigated under the assumption that users are uniformly distributed. However, the users are not always uniformly distributed in real-world situations. For a side-weight inference attack, the adversary would infer that the target user is more likely to belong to the road section with more users, resulting in performance deterioration. In this paper, we investigate the issue of location privacy preservation against side-weight inference attack for non-uniform distributed road network. Meanwhile, we consider the cost function of LBS and formulate the object as a mixed integer programming problem. Then, we propose a road truncation-based scheme to protect location privacy. The road section with high user density is designed to be truncated. Finally, simulation results show that our scheme meets the demand for privacy protection at a low cost. As a result, our scheme is proven to protect users’ location privacy effectively and efficiently. |
| first_indexed | 2024-03-10T00:16:28Z |
| format | Article |
| id | doaj.art-ee1237e56b5d4c4f8c8344994e4e5016 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T00:16:28Z |
| publishDate | 2022-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-ee1237e56b5d4c4f8c8344994e4e50162023-11-23T15:51:58ZengMDPI AGApplied Sciences2076-34172022-01-01123110710.3390/app12031107A Road Truncation-Based Location Privacy-Preserving Method against Side-Weight Inference AttackQingyuan Li0Hao Wu1Xiang Wu2Ning Zhao3Lan Dong4State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing 100044, ChinaState Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing 100044, ChinaState Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing 100044, ChinaNational Computer Network Emergency Response Technical Team, Coordination Center of China, Beijing 100029, ChinaSchool of Computer and Information Technology, Beijing Jiaotong University, Beijing 100044, ChinaTaking advantage of precise positioning technology, location-based service (LBS) has brought a lot of convenience to people’s daily life and made the city smarter. However, the LBS applications also bring some challenges to personal location privacy protection. In order to obtain services from LBS providers, users have to upload their queries including sensitive information, such as identities and locations. This information may be leaked out by the LBS providers or even eavesdropped on by malicious adversaries, which may cause privacy leakage. To tackle this problem, many solutions have been investigated under the assumption that users are uniformly distributed. However, the users are not always uniformly distributed in real-world situations. For a side-weight inference attack, the adversary would infer that the target user is more likely to belong to the road section with more users, resulting in performance deterioration. In this paper, we investigate the issue of location privacy preservation against side-weight inference attack for non-uniform distributed road network. Meanwhile, we consider the cost function of LBS and formulate the object as a mixed integer programming problem. Then, we propose a road truncation-based scheme to protect location privacy. The road section with high user density is designed to be truncated. Finally, simulation results show that our scheme meets the demand for privacy protection at a low cost. As a result, our scheme is proven to protect users’ location privacy effectively and efficiently.https://www.mdpi.com/2076-3417/12/3/1107location privacyl-diversityroad truncationside-weight inference attack |
| spellingShingle | Qingyuan Li Hao Wu Xiang Wu Ning Zhao Lan Dong A Road Truncation-Based Location Privacy-Preserving Method against Side-Weight Inference Attack Applied Sciences location privacy l-diversity road truncation side-weight inference attack |
| title | A Road Truncation-Based Location Privacy-Preserving Method against Side-Weight Inference Attack |
| title_full | A Road Truncation-Based Location Privacy-Preserving Method against Side-Weight Inference Attack |
| title_fullStr | A Road Truncation-Based Location Privacy-Preserving Method against Side-Weight Inference Attack |
| title_full_unstemmed | A Road Truncation-Based Location Privacy-Preserving Method against Side-Weight Inference Attack |
| title_short | A Road Truncation-Based Location Privacy-Preserving Method against Side-Weight Inference Attack |
| title_sort | road truncation based location privacy preserving method against side weight inference attack |
| topic | location privacy l-diversity road truncation side-weight inference attack |
| url | https://www.mdpi.com/2076-3417/12/3/1107 |
| work_keys_str_mv | AT qingyuanli aroadtruncationbasedlocationprivacypreservingmethodagainstsideweightinferenceattack AT haowu aroadtruncationbasedlocationprivacypreservingmethodagainstsideweightinferenceattack AT xiangwu aroadtruncationbasedlocationprivacypreservingmethodagainstsideweightinferenceattack AT ningzhao aroadtruncationbasedlocationprivacypreservingmethodagainstsideweightinferenceattack AT landong aroadtruncationbasedlocationprivacypreservingmethodagainstsideweightinferenceattack AT qingyuanli roadtruncationbasedlocationprivacypreservingmethodagainstsideweightinferenceattack AT haowu roadtruncationbasedlocationprivacypreservingmethodagainstsideweightinferenceattack AT xiangwu roadtruncationbasedlocationprivacypreservingmethodagainstsideweightinferenceattack AT ningzhao roadtruncationbasedlocationprivacypreservingmethodagainstsideweightinferenceattack AT landong roadtruncationbasedlocationprivacypreservingmethodagainstsideweightinferenceattack |