[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-120186-en":3,"doc-seo-120186-105":29,"detail-sidebar-cat-0-en-105":90},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":11,"language":21,"language_code":22,"site_id":23,"html_lang":22,"table_of_contents":24,"faqs":25,"seo_title":26,"seo_description":14,"update_tm":27,"read_time":28},120186,1099514068035,"Ezra","https://ap-avatar.wpscdn.com/davatar_276721f389ce27ea32af1340a28f341c",8,"Research & Report","PRIVACY PRESERVING LOCATION DATA PUBLISHING - A MACHINE LEARNING APPROACH","Publishing datasets supports open-data research and transparency, yet it can expose users’ private information. Spatiotemporal trajectory datasets are especially sensitive because removing unique identifiers does not fully prevent re-identification when adversaries know trajectory fragments or can link the published data with external sources. A privacy-preserving step is therefore required before releasing these datasets. This paper presents a robust machine learning–based anonymization (MLA) framework using k-means clustering and a variant for highly sensitive data, enhanced by a multiple-sequence-alignment step, validated on T-Drive, Geolife, and Gowalla with improved dataset utility.","Journal of Science and Technology  \nISSN: 2456-5660 Volume 8, Issue 12 (Dec-2023)  \n[www.jst.org.in](www.jst.org.in) DOI:[https://doi.org/10.46243/jst.2023.v8.i12.pp23-30](https://doi.org/10.46243/jst.2023.v8.i12.pp23-30)  \nPRIVACY PRESERVING LOCATION DATA PUBLISHING: A MACHINE LEARNING APPROACH  \nD Nikhil Teja1, Patan Abdulsalam Khan2, A Sunny3, R Shashi Rekha4  \n1,2,3B. Tech Student, Department ofCSE (Cyber Security), Malla Reddy College of Engineering and  \nTechnology, Hyderabad, India.  \n4Assistant Professor, Department OfCSE (Data Science), Malla Reddy College Of Engineering and  \nTechnology, Hyderabad, India.  \nTo Cite this Article  \nD Nikhil Teja, Patan Abdulsalam Khan , A Sunny, R Shashi Rekha,“ PRIVACY PRESERVING LOCATION DATA PUBLISHING: A MACHINE LEARNING APPROACH”  \nJournal of Science and Technology, Vol. 08, Issue 12,- Dec 2023, pp23-30  \nArticle Info  \nReceived: 12-11-2023 Revised: 22-11-2023 Accepted: 02-12-2023 Published: 12-12-2023  \nABSTRACT:  \nPublishing datasets plays an essential role in open data research and promoting transparency of government agencies. However, such data publication might reveal users‟ private information. One of the most sensitive sources of data is spatiotemporal trajectory datasets. Unfortunately, merely removing unique identifiers cannot preserve the privacy of users. Adversaries may know parts of the trajectories or be able to link the published dataset to other sources for the purpose of user identification. Therefore, it is crucial to apply privacy preserving techniques before the publication ofspatiotemporal trajectory datasets. In this paper, we propose a robust framework for the anonymization of spatiotemporal trajectory datasets termed as machine learning based anonymization (MLA) . By introducing a new formulation of the problem, weare able to apply machine learning algorithms for clustering the trajectories and propose to use k-means algorithm for this purpose. A variation of k-means algorithm is also proposed to preserve the privacy in overly sensitive datasets. Moreover, we improve the alignment process by considering multiple sequence alignment as part of the MLA. The framework and all the proposed algorithms are applied to T-Drive, Geolife, and Gowalla location datasets. The experimental results indicate a significantly higher utility of datasets by anonymization based on MLA framework.  \nKeywords: Publishing of data, Machine learning, Privacy preserving.  \nI INTRODUCTION  \nPrivacy preservation plays a major role on data mining and transfers the data between different users. Publishing the data or information can hide the user‟s id, latitude, longitude, time, date and can share the data to the third party. There are large amount data  \nincludes person‟s private details like id, gender, location etc. The admin can generate key to the third party to identify the hidden details of a person for analyzing the data. One of the most sensitive data is location trajectories. Spatiotemporal dataset is used in this framework, which include GPS trajectories for mobile users. The database  \nJournal of Science and Technology  \nISSN: 2456-5660 Volume 8, Issue 12 (Dec-2023)  \n[www.jst.org.in](www.jst.org.in) DOI:[https://doi.org/10.46243/jst.2023.v8.i12.pp23-30](https://doi.org/10.46243/jst.2023.v8.i12.pp23-30)  \nincludes k-anonymity for grouping the similar trajectories. The privacy metric for the publication of Spatiotemporal datasets is k- anonymity. The proposed algorithm is based on signature generation method, which is used to generate a key for the users ina digital manner. In signature generation method we use ECC algorithm for digital signature. We improved clustering approach and propose the k-means clustering. By using k-anonymity the similar trajectories were grouped and removed the dissimilar ones. Splitting techniques are used to protect the data privacy. In this paper, the proposed method is used to enhance the MLA framework to preserve the users privacy publication of ","cbCaigNOFIA8HMhl","https://ap.wps.com/l/cbCaigNOFIA8HMhl","pdf",848104,1,"English","en",105,"# Introduction\n## Problem Background and Privacy Risks\n## Proposed MLA Framework Overview\n# Literature Survey\n## Optical K-Anonymization\n## Mondrian Multidimensional K-Anonymity","[{\"question\":\"Why does publishing spatiotemporal trajectory data require privacy-preserving techniques?\",\"answer\":\"Because adversaries can still identify users even after removing unique identifiers, either by knowing parts of trajectories or by linking the published dataset with other sources.\"},{\"question\":\"What is the core idea of the proposed machine learning based anonymization (MLA) framework?\",\"answer\":\"MLA anonymizes spatiotemporal trajectories by clustering similar trajectories using k-means (and a variation for highly sensitive datasets) and improving alignment via multiple sequence alignment.\"},{\"question\":\"Which datasets and what evaluation outcome are reported for the proposed approach?\",\"answer\":\"The framework is applied to T-Drive, Geolife, and Gowalla, and experimental results show significantly higher dataset utility after anonymization using the MLA framework.\"}]","PRIVACY PRESERVING LOCATION DATA PUBLISHING - A MACHINE LEARNING APPROACH | PDF",1785728605,20,{"code":4,"msg":30,"data":31},"ok",{"site_id":23,"language":22,"slug":32,"title":13,"keywords":33,"description":14,"schema_data":34,"social_meta":85,"head_meta":87,"extra_data":89,"updated_unix":27},"privacy-preserving-location-data-publishing-a-machine-learning-approach","",{"@graph":35,"@context":84},[36,53,67],{"@type":37,"itemListElement":38},"BreadcrumbList",[39,43,47,50],{"item":40,"name":41,"@type":42,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":44,"name":45,"@type":42,"position":46},"https://docshare.wps.com/document/","Document",2,{"item":48,"name":12,"@type":42,"position":49},"https://docshare.wps.com/document/research-report/",3,{"item":51,"name":13,"@type":42,"position":52},"https://docshare.wps.com/document/privacy-preserving-location-data-publishing-a-machine-learning-approach/120186/",4,{"url":51,"name":13,"@type":54,"author":55,"headline":13,"publisher":57,"fileFormat":60,"inLanguage":22,"description":14,"dateModified":61,"datePublished":61,"encodingFormat":60,"isAccessibleForFree":62,"interactionStatistic":63},"DigitalDocument",{"name":9,"@type":56},"Person",{"url":40,"name":58,"@type":59},"DocShare","Organization","application/pdf","2026-08-03",true,{"@type":64,"interactionType":65,"userInteractionCount":4},"InteractionCounter",{"@type":66},"ViewAction",{"@type":68,"mainEntity":69},"FAQPage",[70,76,80],{"name":71,"@type":72,"acceptedAnswer":73},"Why does publishing spatiotemporal trajectory data require privacy-preserving techniques?","Question",{"text":74,"@type":75},"Because adversaries can still identify users even after removing unique identifiers, either by knowing parts of trajectories or by linking the published dataset with other sources.","Answer",{"name":77,"@type":72,"acceptedAnswer":78},"What is the core idea of the proposed machine learning based anonymization (MLA) framework?",{"text":79,"@type":75},"MLA anonymizes spatiotemporal trajectories by clustering similar trajectories using k-means (and a variation for highly sensitive datasets) and improving alignment via multiple sequence alignment.",{"name":81,"@type":72,"acceptedAnswer":82},"Which datasets and what evaluation outcome are reported for the proposed approach?",{"text":83,"@type":75},"The framework is applied to T-Drive, Geolife, and Gowalla, and experimental results show significantly higher dataset utility after anonymization using the MLA framework.","https://schema.org",{"og:url":51,"og:type":86,"og:title":13,"og:site_name":58,"og:description":14},"article",{"robots":88,"canonical":51},"index,follow",{"doc_id":7,"site_id":23},{"code":4,"msg":5,"data":91},[92,96,100,104,109,114,119,122,126,129,133],{"id":20,"doc_module":4,"doc_module_name":45,"category_name":93,"show_sort_weight":94,"slug":95},"Story & Novel",90,"story-novel",{"id":46,"doc_module":4,"doc_module_name":45,"category_name":97,"show_sort_weight":98,"slug":99},"Literature",80,"literature",{"id":52,"doc_module":4,"doc_module_name":45,"category_name":101,"show_sort_weight":102,"slug":103},"Exam",70,"exam",{"id":105,"doc_module":4,"doc_module_name":45,"category_name":106,"show_sort_weight":107,"slug":108},5,"Comic",60,"comic",{"id":110,"doc_module":4,"doc_module_name":45,"category_name":111,"show_sort_weight":112,"slug":113},6,"Technology",50,"technology",{"id":115,"doc_module":4,"doc_module_name":45,"category_name":116,"show_sort_weight":117,"slug":118},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":45,"category_name":12,"show_sort_weight":120,"slug":121},30,"research-report",{"id":123,"doc_module":4,"doc_module_name":45,"category_name":124,"show_sort_weight":28,"slug":125},9,"Religion & Spirituality","religion-spirituality",{"id":28,"doc_module":4,"doc_module_name":45,"category_name":127,"show_sort_weight":28,"slug":128},"World Cup","world-cup",{"id":130,"doc_module":4,"doc_module_name":45,"category_name":131,"show_sort_weight":130,"slug":132},10,"Lifestyle","lifestyle",{"id":134,"doc_module":4,"doc_module_name":45,"category_name":135,"show_sort_weight":105,"slug":136},19,"General","general"]