[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-128137-en":3,"doc-seo-128137-105":31,"detail-sidebar-cat-0-en-105":92},{"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":20,"is_deleted":4,"is_public":21,"is_downloadable":21,"audit_status":21,"page_count":22,"language":23,"language_code":24,"site_id":25,"html_lang":24,"table_of_contents":26,"faqs":27,"seo_title":28,"seo_description":14,"update_tm":29,"read_time":30},128137,549768072016,"River Wang","https://ap-avatar.wpscdn.com/davatar_155a257f0dc6eb9ab79c44ca47cae57d",8,"Research & Report","Towards Improved Privacy in AI and Machine Learning Applications - Challenges and way forward","Artificial intelligence (AI) and machine learning (ML) systems rely on large datasets that often contain personal information such as names, addresses, account and credit card numbers, health records, and behavioural data. When collection, storage, and analysis are not handled with sufficient care, privacy violations can occur through insecure systems, illegal access, or hacking. The study identifies privacy concerns unique to AI and ML applications and evaluates the effectiveness of multiple privacy-preserving techniques, using a qualitative case-study approach and data drawn from secondary sources.","Central Lancashire Online Knowledge (CLoK)  \n\n| Title | Towards Improved Privacy in AI and Machine Learning Applications: Challenges and way forward. |\n| --- | --- |\n| Type | Article |\n| URL | [https://clok.uclan.ac.uk/id/eprint/55975/](https://clok.uclan.ac.uk/id/eprint/55975/) |\n| DOI |  |\n| Date | 2025 |\n| Citation | Egho-Promise, Ehiglator Iyobor, Asante, George, Balisane, Hewa, Aina, Folayo and Kure, Halima (2025) Towards Improved Privacy in AI and Machine Learning Applications: Challenges and way forward. Journal of Emerging Technologies and Innovative Research (JETIR), 12 (5) . k342-k357 . ISSN 2349-5162 |\n| Creators | Egho-Promise, Ehiglator Iyobor, Asante, George, Balisane, Hewa, Aina, Folayo and Kure, Halima |\n\nIt is advisable to refer to the publisher’s version if you intend to cite from the work. For information about Research at UCLan please go to [http://www.uclan.ac. uk/research/](http://www.uclan.ac. uk/research/)  \n[All outputs in CLoK are protected by Intellectual Property Rights law](All outputs in CLoK are protected by Intellectual Property Rights law), including Copyright law. Copyright, IPR and Moral Rights for the works on this site are retained by the individual authors and/or other copyright owners. Terms and conditions for use of this material are defined in the  \n[http://clok.uclan.ac.uk/policies/](http://clok.uclan.ac.uk/policies/)  \nTowards Improved Privacy in AI and Machine Learning Applications: Challenges and way  \nforward.  \nEhigiator Iyobor  \nEgho-Promise Department of  \nComputer Science  \nUniversity College Birmingham, Birmingham, United Kingdom  \nGeorge Asante  \nDepartment of Information Technology Education, Akenten Appiah-Menka University of Skills Training and Entrepreneurial Development, Kumasi, Ashanti Region, Ghana  \nHewa Balisane  \nBusiness School, The University of Law, Manchester, United Kingdom  \nFolayo Aina  \nDepartment of Computing, School of Engineering and Computing, University of Central Lancashire,  \nPreston, United Kingdom  \nHalima Kure  \nDepartment of Computer Science and Digital Technologies, University of East London, London,  \nUnited Kingdom  \nAbstract  \nArtificial intelligence (AI) and machine learning (ML) systems depend heavily on large datasets to function effectively. These datasets contain details of people and can be names, addresses, account numbers, credit card numbers, health data, and behaviour data, among others. Such enormous amounts of data are typically collected, stored, and analysed. This could lead to privacy violations if not sensitively done. Privacy violations are caused by causes such as inadequate security, illegal access, or hacking, all of which have negative repercussions for the individuals and businesses involved. This study aims to identify the privacy concerns unique to AI and ML applications and assess the efficacy of different privacy-preserving approaches. Specifically, the study seeks to identify the privacy challenges to AI and ML applications and evaluate the effectiveness of various privacy-preserving techniques that apply to AI and ML applications. This study used a qualitative research approach based on case studies, and data was acquired from secondary sources such as published papers, websites, and publications. It has been found that recent advances in  \n\n| JETIR2505B23 | Journal of Emerging Technologies and Innovative Research (JETIR) [www.jetir.org](www.jetir.org) | k342 |\n| --- | --- | --- |\n\nartificial intelligence (AI) and machine learning (ML) have shown a new dawn in corporate functions, guiding efficiency, innovations, and insights across several industries. Although the use of personal data by these technologies has been extensively adopted, it has raised several privacy issues. The research identified certain privacy issues specific to AI and ML applications, such as overfitting, data leakage, illegal access, model inversion attacks, re-identification, and Privacy audits. It can be concluded that, despite the continuous","cbCait16G957emba","https://ap.wps.com/l/cbCait16G957emba","pdf",436297,2,1,17,"English","en",105,"# Abstract\n# Keywords\n# 1. Introduction","[{\"question\":\"Why do AI and machine learning applications raise privacy risks?\",\"answer\":\"They depend on large datasets that include personal details. If data collection, storage, or analysis lacks sufficient safeguards, privacy violations can result from security weaknesses, illegal access, or hacking.\"},{\"question\":\"What does the study aim to accomplish?\",\"answer\":\"It identifies privacy challenges specific to AI and ML applications and assesses how effective different privacy-preserving approaches are in addressing those challenges.\"},{\"question\":\"Which privacy-preserving techniques are recommended to improve privacy?\",\"answer\":\"The paper highlights techniques such as data anonymisation and pseudonymisation, differential privacy, federated learning, homomorphic encryption, and secure multi-party computation.\"}]","Towards Improved Privacy in AI and Machine Learning Applications - Challenges and way forward | PDF",1785945026,43,{"code":4,"msg":32,"data":33},"ok",{"site_id":25,"language":24,"slug":34,"title":13,"keywords":35,"description":14,"schema_data":36,"social_meta":87,"head_meta":89,"extra_data":91,"updated_unix":29},"towards-improved-privacy-in-ai-and-machine-learning-applications-challenges-and-way-forward","",{"@graph":37,"@context":86},[38,54,69],{"@type":39,"itemListElement":40},"BreadcrumbList",[41,45,48,51],{"item":42,"name":43,"@type":44,"position":21},"https://docshare.wps.com","Home","ListItem",{"item":46,"name":47,"@type":44,"position":20},"https://docshare.wps.com/document/","Document",{"item":49,"name":12,"@type":44,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":44,"position":53},"https://docshare.wps.com/document/towards-improved-privacy-in-ai-and-machine-learning-applications-challenges-and-way-forward/128137/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":24,"description":14,"dateModified":62,"datePublished":63,"encodingFormat":61,"isAccessibleForFree":64,"interactionStatistic":65},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":42,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-27","2026-08-05",true,{"@type":66,"interactionType":67,"userInteractionCount":20},"InteractionCounter",{"@type":68},"ViewAction",{"@type":70,"mainEntity":71},"FAQPage",[72,78,82],{"name":73,"@type":74,"acceptedAnswer":75},"Why do AI and machine learning applications raise privacy risks?","Question",{"text":76,"@type":77},"They depend on large datasets that include personal details. If data collection, storage, or analysis lacks sufficient safeguards, privacy violations can result from security weaknesses, illegal access, or hacking.","Answer",{"name":79,"@type":74,"acceptedAnswer":80},"What does the study aim to accomplish?",{"text":81,"@type":77},"It identifies privacy challenges specific to AI and ML applications and assesses how effective different privacy-preserving approaches are in addressing those challenges.",{"name":83,"@type":74,"acceptedAnswer":84},"Which privacy-preserving techniques are recommended to improve privacy?",{"text":85,"@type":77},"The paper highlights techniques such as data anonymisation and pseudonymisation, differential privacy, federated learning, homomorphic encryption, and secure multi-party computation.","https://schema.org",{"og:url":52,"og:type":88,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":90,"canonical":52},"index,follow",{"doc_id":7,"site_id":25},{"code":4,"msg":5,"data":93},[94,98,102,106,111,116,121,124,129,132,136],{"id":21,"doc_module":4,"doc_module_name":47,"category_name":95,"show_sort_weight":96,"slug":97},"Story & Novel",90,"story-novel",{"id":20,"doc_module":4,"doc_module_name":47,"category_name":99,"show_sort_weight":100,"slug":101},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":47,"category_name":103,"show_sort_weight":104,"slug":105},"Exam",70,"exam",{"id":107,"doc_module":4,"doc_module_name":47,"category_name":108,"show_sort_weight":109,"slug":110},5,"Comic",60,"comic",{"id":112,"doc_module":4,"doc_module_name":47,"category_name":113,"show_sort_weight":114,"slug":115},6,"Technology",50,"technology",{"id":117,"doc_module":4,"doc_module_name":47,"category_name":118,"show_sort_weight":119,"slug":120},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":47,"category_name":12,"show_sort_weight":122,"slug":123},30,"research-report",{"id":125,"doc_module":4,"doc_module_name":47,"category_name":126,"show_sort_weight":127,"slug":128},9,"Religion & Spirituality",20,"religion-spirituality",{"id":127,"doc_module":4,"doc_module_name":47,"category_name":130,"show_sort_weight":127,"slug":131},"World Cup","world-cup",{"id":133,"doc_module":4,"doc_module_name":47,"category_name":134,"show_sort_weight":133,"slug":135},10,"Lifestyle","lifestyle",{"id":137,"doc_module":4,"doc_module_name":47,"category_name":138,"show_sort_weight":107,"slug":139},19,"General","general"]