| Title | Differential privacy protection method for trip-oriented shared data |
| Creator | |
| Date Issued | 2023-08-30 |
| Source Publication | Concurrency and Computation: Practice and Experience
 |
| ISSN | 1532-0626 |
| Volume | 35 |
| Issue | 19 |
| Abstract | While location information sharing technology provides convenience for unmanned driving and journey navigation, user journey information sharing has also become a disaster for privacy information leakage. The traditional differential privacy method can only perturb the data entirely and cannot consider the design of data availability. In this paper, the difference privacy algorithm is improved by combining it with the Apriori algorithm, and the relevant perturbation is carried out after mining the associated data of the user's trip. In the face of possible data attacks, the privacy protection of the sensitive information of the user's actual data is ensured while the availability of the data is ensured. By testing 3000 trip data generated by experimental simulation, the results show that the correlation information between the original datasets is destroyed. However good availability is maintained after the Laplace data perturbation of the proposed algorithm for both simultaneous and multi-person trips. |
| Keyword | association rule differential privacy machine learning noise privacy protection |
| DOI | 10.1002/cpe.7414 |
| URL | View source |
| Language | 英语English |
| Scopus ID | 2-s2.0-85141772190 |
| Citation statistics | |
| Document Type | Conference paper |
| Identifier | http://repository.uic.edu.cn/handle/39GCC9TT/11552 |
| Collection | Beijing Normal-Hong Kong Baptist University |
| Corresponding Author | Luo，Entao |
| Affiliation | 1.School of Information Engineering,Hunan University of Science and Engineering,YongZhou,China 2.Guangxi Key Laboratory of Cryptography and Information Security,Guilin University of Electronic Technology,Guilin,China 3.Department of Computer Science,Northeastern Illinois University,Chicago,United States 4.School of Computer Science and Engineering,Guangzhou University,Guangzhou,China 5.School of Computer Science and Engineering,Hunan University of Science and Technology,Xiangtan,China 6.School of Computer Science and Engineering,Nanjing University of Science and Technology,NanJing,China 7.Institute of Artificial Intelligence and Future Networks,Beijing Normal University (BNU Zhuhai),Zhuhai,China 8.Guangdong Key Lab of AI and Multi-Modal Data Processing,BNU-HKBU United International College (UIC),Zhuhai,China |
| Recommended Citation GB/T 7714 | Du，Danlei,Luo，Entao,Yi，Yanget al. Differential privacy protection method for trip-oriented shared data[C], 2023. |
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