Computer Science ›› 2025, Vol. 52 ›› Issue (5): 307-321.doi: 10.11896/jsjkx.240600067
• Information Security • Previous Articles Next Articles
CAO Tengfei1,2,3, YIN Runtian1,3, ZHU Liang4, XU Changqiao2
CLC Number:
| [1]Pew Research Center.Americans Increasingly Use Smartphones for More than Voice Calls,Texting [EB/OL].www.pewresearch.org/internet/ft_01-27-16_smartphoneactivities/. [2]JIANG H,LI J,ZHAO P,et al.Location privacy-preservingmechanisms in location-based services:A comprehensive survey[J].ACM Computing Surveys(CSUR),2021,54(1):1-36. [3]ENCK W,GILBERT P,HAN S,et al.Taintdroid:an information-flow tracking system for realtime privacy monitoring on smartphones[J].ACM Transactions on Computer Systems,2014,32(2):1-29. [4]ZHAO Y,CHEN J.Vector-indistinguishability:location dependency based privacy protection for successive location data[J].IEEE Transactions on Computers,2024,73(4):970-979. [5]MOHAMED R,FARRUKH H,LU Y,et al.iStelan:Disclosing Sensitive User Information by Mobile Magnetometer from Finger Touches[C]//Proceedings on Privacy Enhancing Technologies.2023:79-96. [6]WU Y,SHI C,ZHANG T,et al.Privacy Leakage via Unre-stricted Motion-Position Sensors in the Age of Virtual Reality:A Study of Snooping Typed Input on Virtual Keyboards[C]//2023 IEEE Symposium on Security and Privacy(SP).IEEE Computer Society,2023:3382-3398. [7]HU G,ZHANG B,XIAO X,et al.SAMLDroid:a static taintanalysis and machine learning combined high-accuracy method for identifying Android apps with location privacy leakage risks[J].Entropy,2021,23(11):1489. [8]ALLEN M.Health Insurers Are Vacuuming Up Details About You - And It Could Raise Your Rates [EB/OL].www.npr.org/sections/healthshots/2018/07/17/629441555/health-insurers-arevacuuming-up-details-about-you-and-it-could-raise-yourrates. [9]LI H,ZHU H,DU S,et al.Privacy leakage of location sharing in mobile social networks:Attacks and defense[J].IEEE Transactions on Dependable and Secure Computing,2016,15(4):646-660. [10]RUSERT J,KHALID O,HONG D,et al.No Place to Hide:Inadvertent Location Privacy Leaks on Twitter[J].Proc.Priv.Enhancing Technol.,2019(4):172-189. [11]FANG D,QIAN Y.5G wireless security and privacy:Architecture and flexible mechanisms[J].IEEEVehicular Technology Magazine,2020,15(2):58-64. [12]WANG J,WANG F Y,CAO Z,et al.Sink location privacy protection under direction attack in wireless sensor networks[J].Wireless Networks,2017,23:579-591. [13]VELAYUDHAN N C,ANITHA A,MADANAN M.Sybil attack with RSU detection and location privacy in urban VANETs:An efficient EPORP technique[J].Wireless Personal Communications,2022,122:3573-3601. [14]BALARAM A,PUSHPA S.Sybil attack resistant location privacy in VANET[J].International Journal of Information and Communication Technology,2018,13(4):389-406. [15]XUE D,WU L F,LI H B,et al.A novel destination prediction attack and corresponding location privacy protection method in geo-social networks[J].International Journal of Distributed Sensor Networks,2017,13(1):1550147716685421. [16]XU Z,ZHANG H,YU X,et al.Privacy-Aware Information Sharing in Location-Based Services:Attacks and Defense[J].IEICE Transactions on Information and Systems,2016,99(8):1991-2001. [17]YAN G H,LIU T,ZHANG X J,et al.Service similarity-based location k-anonymity method for resisting background knowledge inference attacks[J].Journal of Xi'an Jiaotong University,2020,54(1):8-18. [18]LIU S,SINGH L,TIAN K.Information Exposure From Relational Background Knowledge on Social Media[C]//2020 IEEE International Conference on Data Science and Advanced Analy-tics(DSAA).IEEE,2020:282-291. [19]LIN T L,CHANG H Y,LI S L.A location privacy attack based on the location sharing mechanism with erroneous distance in geosocial networks[J].Sensors,2020,20(3):918. [20]JIANG H,ZHAO P,WANG C.RobLoP:Towards robust privacy preserving against location dependent attacks in continuous LBS queries[J].IEEE/ACM Transactions on Networking,2018,26(2):1018-1032. [21]ZHAO P,LI J,ZENG F.ILLIA:Enabling $ k $-anonymity-based privacy preserving against location injection attacks in continuous LBS queries[J].IEEE Internet of Things Journal,2018,5(2):1033-1042. [22]LI H,ZHU H,DU S,et al.Privacy leakage of location sharing in mobile social networks:Attacks and defense[J].IEEE Transactions on Dependable and Secure Computing,2016,15(4):646-660. [23]SUN Y,CHEN M,HU L,et al.ASA:Against statistical attacks for privacy-aware users in Location Based Service[J].Future Generation Computer Systems,2017,70:48-58. [24]MURAKAMI T.Expectation-Maximization Tensor Factoriza-tion for Practical Location Privacy Attacks[C]//Proc.Priv.Enhancing Technol..2017:138-155. [25]MA Q,ZHANG S,ZHU T,et al.PLP:Protecting location privacy against correlation analyze attack in crowdsensing[J].IEEETransactions on Mobile Computing.2016,16(9):2588-2598. [26]DEWRI R.Local differential perturbations:Location privacy un-der approximate knowledge attackers[J].IEEE Transactions on Mobile Computing.2012,12(12):2360-2372. [27]NIU B,SUN J,CHEN Y.Evaluating the Impact of Adversarial Factors on Membership Inference Attacks[C]//2023 IEEE Smart World Congress(SWC).Portsmouth,United Kingdom,2023:1-8. [28]GUNAWAN D,PRIYAWATI D,NUGROHO Y S.Preserving Individual Privacy from Inference Attack in Transaction Data Publishing[C]//2023 Eighth International Conference on Informatics and Computing(ICIC).Manado,Indonesia,2023:1-6. [29]YI J,CAO T F,GAO S,et al.Honeypot defense and transmission strategy based on offensive and defensive games in vehicular networks[J].Chinese Journal of Network and Information Security,2022,8(4):157-167. [30]PAN X,CHEN W Z,WU L,et al.Protecting personalized privacy against sensitivity homogeneity attacks over road networks in mobile services[J].Frontiers of Computer Science,2016,10:370-386. [31]LIU Z P,LIU Q N,MIAO D W.A blockchain anonymity solution to prevent location homogeneity attacks[J].Concurrency and Computation:Practice and Experience,2022,34(27):e7326. [32]LI Y J,ZHU Y F,BAI L F.Enhanced location k-anonymity privacy protection scheme based on Geohash[J].Computer Science,2024,51(9):393-400. [33]SHAHAM S,DING M,LIU B,et al.Privacy preservation in location-based services:A novel metric and attack model[J].IEEE Transactions on Mobile Computing.2020,20(10):3006-3019. [34]NIU B,CHEN Y,WANG Z,et al.Eclipse:Preserving differential location privacy against long-term observation attacks[J].IEEE Transactions on Mobile Computing,2020,21(1):125-138. [35]MA Z,XU S,LIU B.LPP2KL:Online Location Privacy Protection Against Knowing-and-Learning Attacks for LBSs[J].IEEE Transactions on Computational Social Systems,2022,10(1):234-245. [36]WANG J,WANG F,LI H.Differential Privacy Location Protection Scheme Based on Hilbert Curve[J].Security and Communication Networks,2021(1):5574415. [37]ZHANG Q,ZHANG X,WANG M,et al.DPLQ:location－based service privacy protection scheme based on differential privacy[J].IET Information Security,2021,15(6):442-456. [38]LI H,WANG Y,GUO F,et al.Differential privacy location protection method based on the Markov model[J].Wireless Communications and Mobile Computing,2021(1):4696455. [39]SAINI I,SAAD S,JAEKEL A.A comprehensive pseudonymchanging scheme for improving location privacy in vehicular networks[J].Internet of Things,2022,19:100559. [40]ULLAH I,SHAH M A,KHAN A.Adaptive Grouping andPseudonym Changing Policy for Protection of Vehicles Location Information in VANETs[C]//2021 IEEE Symposium Series on Computational Intelligence(SSCI).IEEE,2021:1-7. [41]MEMON I,MEMON H,ARAIN Q A.Pseudonym changingstrategy with mix zones based authentication protocol for location privacy in road networks[J].Wireless Personal Communications,2021,116:3309-3329. [42]WANG J,WANG C R,MA J F,et al.A fake location selection algorithm based on location semantics and query probability[J].Journal of Communication,2020,41(3):53-61. [43]LI L,SHI D,ZHANG X,et al.Privacy preserving participant recruitment for coverage maximization in location aware mobile crowdsensing[J].IEEE Transactions on Mobile Computing,2021,21(9):3250-3262. [44]GAO Z G,HUANG Y,ZHENG L,et al.Protecting location privacy of users based on trajectory obfuscation in mobile crowdsensing[J].IEEE Transactions on Industrial Informatics,2022,18(9):6290-6299. [45]BUCCAFURRI F,DE A V,IDONE M F,et al.A DistributedLocation Trusted Service Achieving k-Anonymity against the Global Adversary[C]//2021 22nd IEEE International Confe-rence on Mobile Data Management(MDM).IEEE,2021:133-138. [46]YANG M,YE B,CHEN Y,et al.A trusted de-swinging k-anonymity scheme for location privacy protection[J].Journal of Cloud Computing,2022,11(1):2. [47]XING L,JIA X,GAO J,et al.A location privacy protection algorithm based on double k-anonymity in the social internet of vehicles[J].IEEE Communications Letters,2021,25(10):3199-3203. [48]ZHENG X,YUAN Q,WANG B,et al.A Homomorphic En-cryption Based Location Privacy Preservation Scheme for Crowdsensing Tasks Allocation[J].Wireless Personal Communications,2022,126(1):719-740. [49]JAIN M,SINGH P,RAMAN B.SHELBRS:Location-BasedRecommendation Services Using Switchable Homomorphic Encryption[C]//Security,Privacy,and Applied Cryptography Engineering:11th International Conference,SPACE 2021,Kolkata,India,December 10-13,2021,Proceedings.Cham:Springer International Publishing,2022:63-80. [50]KHAZBAK Y,FAN J,ZHU S,et al.Preserving personalized location privacy in ride-hailing service[J].Tsinghua Science and Technology,2020,25(6):743-757. [51]MA B,WANG X,NI W,et al.Personalized Location PrivacyWith Road Network-Indistinguishability[J].IEEE Transactions on Intelligent Transportation Systems,2022,23(11):20860-20872. [52]XU C,DING Y,ZHAO G,et al.Personalized location privacy protection for location-based services in vehicular networks[J].IEEE Transactions on Intelligent Transportation Systems,2022,24(1):1163-1177. [53]MIN M,ZHU H,DING J,et al.Personalized 3D Location Privacy Protection With Differential and Distortion Geo-Perturbation[J].IEEE Transactions on Dependable and Secure Computing.2024,21(4):3629-3643. [54]WANG Z,HU J,LV R,et al.Personalized privacy-preservingtask allocation for mobile crowdsensing[J].IEEE Transactions on Mobile Computing,2018,18(6):1330-1341. [55]FAN Y,LIU L,ZHANG X,et al.MAPP:An efficient multi-location task allocation framework with personalized location privacy-protecting in spatial crowdsourcing[J].Information Sciences,2023,619:654-678. [56]LV C,ZHANG L,LI X Y.Personalized Differentially Private Online Minimum Bipartite Matching IN Spatial Crowdsourcing[C]//2022 8th International Conference on Big Data Computing and Communications(BigCom).IEEE,2022:134-143. [57]ZHANG C,WANG Y,WANG W,et al.A Personalized Location Privacy Protection System in Mobile Crowdsourcing[J].IEEE Internet of Things Journal,2024,11(6):9995-10006. [58]WEN R,CHENG W,HUANG H,et al.Privacy preserving trajectory data publishing with personalized differential privacy[C]//2020 IEEEIntl Conf on Parallel & Distributed Processing with Applications,Big Data & Cloud Computing,Sustainable Computing & Communications,Social Computing & Networking.IEEE,2020:313-320. [59]ZHI W,GONG X,WANG Y.Personalized Differential Privacy Preservation Method for Trajectory Based on Regional Density Analysis[C]//2023 2nd International Conference on Big Data,Information and Computer Network(BDICN).IEEE,2023:43-48. [60]YUQI O.Trajectory Synthesis Method Based on PersonalizedLocal Differential Privacy[C]//2023 IEEE 14th International Conference on Software Engineering and Service Science.IEEE,2023:230-234. [61]ISLAM F T,HASHEM T,SHAHRIYAR R.A Crowd-Enabled Approach for Privacy-Enhanced and Personalized Safe Route Planning for Fixed or Flexible Destinations[J].IEEE Transactions on Knowledge and Data Engineering,2023,53(11):10922-10936. [62]YI K,CHEN Y,SU Y,et al.Towards Efficient Privacy-Preserving Top-k Trajectory Similarity Query[C]//2023 IEEE International Conference on Mobile Ad Hoc and Smart Systems.IEEE,2023:512-520. [63]MIN M H,YANG S,XU J H,et al.Intelligent Semantic Location Privacy Protection Method in Three-Dimensional Spatial Location Services[J].Journal of Electronics and Information Engineering,2024,46(6):2627-2637. [64]MIN M,ZHU H,ZHANG H,et al.Semantic Adaptive Geo-Indistinguishability for Location Privacy Protection in Mobile Networks[J].IEEE Transactions on Vehicular Technology,2024,73(6):9193-9198. [65]QIU G,GUO D,SHEN Y,et al.Mobile semantic-aware trajectory for personalized location privacy preservation[J].IEEE Internet of Things Journal,2020,8(21):16165-16180. [66]QIU G,TANG G,LI C,et al.DSG-BTra:Differentially Semantic-Generalized Behavioral Trajectory for Privacy-Preserving Mobile Internet Services[J].IEEE Internet of Things Journal,2023,11(7):13029-13038. [67]ZHONG H,NI J,CUI J,et al.Personalized location privacy protection based on vehicle movement regularity in vehicular networks[J].IEEE Systems Journal,2021,16(1):755-766. [68]WANG J,LIU H,DONG X,et al.Personalized Location Privacy Trading in Double Auction for Mobile Crowdsensing[J].IEEE Internet of Things Journal,2022,10(10):8971-8983. [69]SHEN Z,HE S,WANG H,et al.A Differential Privacy Budget Allocation Method Combining Privacy Security Level[J].Journal of Communications and Information Networks,2023,8(1):90-98. [70]YANG M,WU Y,CHEN Y.A K-anonymity Optimization AlgorithmUnder Attack Model[C]//2022 IEEE International Conferences on Internet of Things and IEEE Green Computing &Communications.IEEE,2022:357-362. [71]NIU B,LI Q,WANG H,et al.A framework for personalized lo-cation privacy[J].IEEE Transactions on Mobile Computing,2021,21(9):3071-3083. [72]LIN Y,JIANG Y,LI Y,et al.Privacy-preserving batch-basedtask assignment over spatial crowdsourcing platforms[J].Computer Networks,2024,241:110196. [73]BI R,ZHAO M,YING Z,et al.Achieving dynamic privacymeasurement and protection based on reinforcement learning for mobile edge crowdsensing of IoT[J].Digital Communications and Networks,2022,10(2):380-388. [74]HAN P X,LIU Z B,SUN Z,et al.A novel prediction model for ship fuel consumption considering shipping data privacy:An XGBoost-IGWO-LSTM-based personalized federated learning approach[J].Ocean Engineering,2024,302:117668. [75]PANDEY M,KAUR H,BASAK S,et al.Privacy-PreservingLocation-Based Services:A DQN Algorithmic Perspective[C]//2024 International Conference on Advanced Information Networking and Applications(AINA).Cham:Springer Nature Switzerland,2024:384-399. [76]SUN X,WANG Y,DUAN P,et al.Bilateral Privacy Protection Scheme Based on Adaptive Location Generalization and Grouping Aggregation in Mobile Crowdsourcing[J].IEEE Internet of Things Journal,2024,11(10):17740-17756. [77]HUANG H,HUANG T,WANG W,et al.Federated Learningand Convex Hull Enhancement for Privacy Preserving Wi-Fi-Based Device-Free Localization [J].IEEE Transactions on Consumer Electronics,2024,70(1):2577-2585. [78]MACHAM,FOUTZ N Z,LI B,et al.Personalized privacy preservation in consumer mobile trajectories [J].Information Systems Research,2024,35(1):249-271. [79]LI Y,BAI L,ZHANG Y.Framework of privacy metric for location-based services [C]//3rd International Symposium on Electrical,Electronics and Information Engineering(ISEEIE 2023).Hangzhou,China:IEEE,2023:120-125. [80]APOLLONIO F,BEDOGNI L,GORI G,et al.On the Trade-Off Between Privacy and Information Quality in Location Based Services[C]//IEEE 21st Consumer Communications & Networking Conference(CCNC).IEEE,2024:994-997. [81]MIN M H,ZHU H P,LI S Y,et al.Semantic Adaptive Geo-Indistinguishability for Location Privacy Protection in Mobile Networks [J].IEEE Transactions on Vehicular Technology,2024,73(6):9193-9198. [82]汪玉洁,刘涛,包象琳,潘正高.基于社区划分的社交推荐隐私保护方法[J].重庆工商大学学报(自然科学版),2024(6):30-38. [83]ZHANGW,XIE Z,VERA VENKATA SAI A M,et al.A Local Differential Privacy Trajectory Protection Method Based on Temporal and Spatial Restrictions for Staying Detection[J].Tsinghua Science and Technology,2024,29(2):617-633. [84]FEI G,LIU Y,HU G,et al.Online Social Network User Home Location Inference Based on Heterogeneous Networks[J].IEEE Transactions on Dependable and Secure Computing,2024,21(6):5509-5525. [85]TOTH A.Toward privacy-focused personalization:Designing a learning experience to facilitate privacy-personalization trade-off[C]//2024 Adjunct Proceedings of the 32nd ACM Conference on User Modeling,Adaptation and Personalization(UMAP).2024:61-65. [86]WANG W,LI B.Learning Personalized Privacy Preference From Public Data [C]//ICIS 2023 Proceedings.2023. |
| [1] | LIU Bing, XU Pengyu, LU Sijin, WANG Shijing, SUN Hongjian, JING Liping, YU Jian. Sequential Tag Recommendation [J]. Computer Science, 2025, 52(1): 142-150. |
| [2] | WANG Zihong, SHAO Yingxia, HE Jiyuan, LIU Jinbao. Sequential Recommendation Based on Multi-space Attribute Information Fusion [J]. Computer Science, 2024, 51(3): 102-108. |
| [3] | LIN Yidi, LI Bicheng, YANG Haijun. Rumor Detection Based on Similarity-enhanced Propagation Structure [J]. Computer Science, 2024, 51(11A): 240200116-8. |
| [4] | ZENG Congai, LIU Yali, CHEN Shuyi, ZHU Xiuping, NING Jianting. Multi-type K-nearest Neighbor Query Scheme with Mutual Privacy-preserving in Road Networks [J]. Computer Science, 2024, 51(11): 400-417. |
| [5] | ZHOU Yangtao, CHU Hua, ZHU Feifei, LI Xiangming, HAN Zihan, ZHANG Shuai. Survey on Deep Learning-based Personalized Learning Resource Recommendation [J]. Computer Science, 2024, 51(10): 17-32. |
| [6] | ZHANG Xuejun, YANG Yixing, LI Jiale, TIAN Feng, HUANG Haiyan, HUANG Shan. Dummy Location Generation Algorithm Against Side Information Inference Attack [J]. Computer Science, 2023, 50(11A): 221000036-9. |
| [7] | ZHANG Jia, DONG Shou-bin. Cross-domain Recommendation Based on Review Aspect-level User Preference Transfer [J]. Computer Science, 2022, 49(9): 41-47. |
| [8] | SHAO Zi-hao, YANG Shi-yu, MA Guo-jie. Foundation of Indoor Information Services:A Survey of Low-cost Localization Techniques [J]. Computer Science, 2022, 49(9): 228-235. |
| [9] | PU Qian-qian, LEI Hang, LI Zhen-hao, LI Xiao-yu. Personalized News Recommendation Algorithm with Enhanced List Information and User Interests [J]. Computer Science, 2022, 49(6): 142-148. |
| [10] | REN Sheng-lan, GUO Hui-juan, HUANG Wen-hao, TANG Zhi-hong, Qi Hui. Recommendation Method Based on Attention Mechanism Interactive Convolutional Neural Network [J]. Computer Science, 2022, 49(10): 126-131. |
| [11] | CHEN Jin-peng, HU Ha-lei, ZHANG Fan, CAO Yuan, SUN Peng-fei. Convolutional Sequential Recommendation with Temporal Feature and User Preference [J]. Computer Science, 2022, 49(1): 115-120. |
| [12] | ZHANG Xue-jun, YANG Hao-ying, LI Zhen, HE Fu-cun, GAI Ji-yang, BAO Jun-da. Differentially Private Location Privacy-preserving Scheme withSemantic Location [J]. Computer Science, 2021, 48(8): 300-308. |
| [13] | WANG Hui, ZHU Guo-yu, SHEN Zi-hao, LIU Kun, LIU Pei-qian. Dummy Location Generation Method Based on User Preference and Location Distribution [J]. Computer Science, 2021, 48(7): 164-171. |
| [14] | LIU Xiao-fei, ZHU Fei, FU Yu-chen, LIU Quan. Personalized Recommendation Algorithm Based on User Preference Feature Mining [J]. Computer Science, 2020, 47(4): 50-53. |
| [15] | ZHOU Yi-hua, LI Guang-hui, YANG Yu-guang, SHI Wei-min. Location Privacy Preserving Nearest Neighbor Querying Based on GeoHash [J]. Computer Science, 2019, 46(8): 212-216. |
|
||
Home