[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-128700-en":3,"doc-seo-128700-105":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},128700,962084926284,"Aurora","https://ap-avatar.wpscdn.com/davatar_29158cc5080c5b710cf443261637dec0",8,"Research & Report","The Impact of Machine Learning on Future Defense Strategies","Machine learning (ML) plays an increasingly pivotal role in shaping future defense strategies, with demonstrated advancements across cybersecurity, resource allocation, and autonomous systems. This research examines ML’s multifaceted impact through three core directions: improving threat detection and mitigation in defense cybersecurity, optimizing resource allocation and military logistics, and addressing ethical and strategic implications of autonomous defense systems. Using qualitative research and secondary data from governmental reports, academic works, industry white papers, and ethical frameworks, findings show ML strengthens cyber threat detection, enhances logistical efficiency, and requires robust governance.","| PELITA Jurnal Penelitian dan Karya Ilmiah\u003Cbr>Volume 24, Issue 2, 2024, pp. 71-82\u003Cbr>P-ISSN: 1907-5693 E-ISSN: 2684-8856\u003Cbr>Open Access: [https://dx.doi.org/10.33592/pelita.v24i2.5130](https://dx.doi.org/10.33592/pelita.v24i2.5130) |  |\n| --- | --- |\n| The Impact of Machine Learning on Future Defense Strategies |  |\n| \u003Cbr>Aris Sarjito1*\u003Cbr> |  |\n| 1 Fakultas Manajemen Pertahanan, Universitas Pertahanan Republik Indonesia, Jakarta, Indonesia |  |\n| A R T I C L E I N F O\u003Cbr>Article history:\u003Cbr>Received Aug 21, 2024 Revised Sep 29, 2024\u003Cbr>Accepted Oct 09, 2024\u003Cbr>Available online Jan 31, 2025\u003Cbr>Kata Kunci :\u003Cbr>alokasi sumber daya. keamanan siber pertahanan, logistik,\u003Cbr>pembelajaran mesin, sistem pertahanan otonom,\u003Cbr>A B S TRA K\u003Cbr>Machine learning (ML) semakin penting dalam membentuk strategi pertahanan masa depan, menawarkan kemajuan di berbagai bidang penting sepertikeamanan siber, alokasi sumber daya, dan sistem otonom. Penelitian ini mengeksplorasi dampak multifaset ML di bidang pertahanan, denganfokuspada tiga bidang utama: meningkatkan deteksi dan mitigasi ancaman dalam keamanan siber, mengoptimalkan alokasi sumber daya dan logistik dalam operasi militer, dan menavigasi implikasi etis dan strategis dari sistempertahanan otonom. Studi ini menggunakan metode penelitian kualitatif, khususnya melalui analisis data sekunder dari laporan pemerintah, publikasi akademis, kertas putih industri, dan kerangka etika. Temuan menunjukkan bahwa algoritme ML secara signifikan mendukung deteksi ancaman denganmemanfaatkan Teori Deteksi Anomali dan Teori Permainan, sehinggameningkatkan respons terhadap ancaman dunia maya. Dalam logistik militer, model ML berdasarkan Riset Operasi dan Teori Manajemen Rantai Pasokan mengoptimalkan distribusi sumber daya, meningkatkan efisiensi operasional, dan mendukung kesiapan misi. Secara etis, penerapan ML dalam sistempertahanan otonom memicu pertimbangan tanggung jawab moral, bias, dan risiko strategis, sehingga memerlukan kerangka tata kelola yang komprehensif. Kesimpulannya, meskipun ML menawarkan potensi transformatif dalam strategi pertahanan, penerapan yang efektif memerlukan pedoman etika yang kuat,\u003Cbr>tinjauan ke masa depan yang strategis, dan kolaborasi antar disiplin ilmu untuk memitigasi risiko dan memaksimalkan manfaat.\u003Cbr>Keywords:\u003Cbr>autonomous defense systems, defense cybersecurity, logistics, machine learning, resource allocation\u003Cbr>\u003Cbr>A B S T R A C T |  |\n| Machine learning (ML) is increasingly pivotal in shaping future defense strategies, offering advancements across critical domains such as cybersecurity, resource allocation, and autonomous systems. This research explores the multifaceted impact of ML in defense, focusing on three primary areas: enhancing threat detection and mitigation in cybersecurity, optimizing resource allocation and logistics in military operations, and navigating the ethical and strategic implications of autonomous defense systems. The study utilizes qualitative research methods, particularly through secondary data analysis from government reports, academic publications, industry white papers, and ethical frameworks. Findings indicate that ML algorithms significantly bolster threat detection by leveraging Anomaly Detection Theory and Game Theory, thereby enhancing responsiveness to cyber threats. In military logistics, ML models informed by Operations Research and Supply Chain Management Theory optimize resource distribution, improve operational efficiencies, and support mission readiness. Ethically, the deployment of ML in autonomous defense systems prompts considerations of moral responsibilities, biases, and strategic risks, necessitating comprehensive governance frameworks. In conclusion, while ML offers transformative potential in defense strategies, effective implementation requires robust ethical guidelines, strategic foresight, and interdisciplinary collaboration to mitigate risks and maximize benefits. |  |\n\n*Corresponding author.  \nE-mail addresses:","cbCaipVHV7rZOt3l","https://ap.wps.com/l/cbCaipVHV7rZOt3l","pdf",643722,3,1,12,"English","en",105,"# Introduction\n## Cybersecurity threat detection and mitigation\n## Predictive analytics for threat forecasting\n## Autonomous defense systems","[{\"question\":\"How does machine learning improve defense cybersecurity?\",\"answer\":\"The study indicates ML algorithms strengthen threat detection and response to cyber threats by leveraging Anomaly Detection Theory and Game Theory.\"},{\"question\":\"What role does machine learning play in military logistics and resource allocation?\",\"answer\":\"ML models, informed by Operations Research and Supply Chain Management Theory, optimize distribution of resources, improve operational efficiency, and support mission readiness.\"},{\"question\":\"What ethical issues arise from deploying machine learning in autonomous defense systems?\",\"answer\":\"The research highlights concerns about moral responsibility, bias, and strategic risk, requiring comprehensive governance frameworks and robust ethical guidelines.\"}]","The Impact of Machine Learning on Future Defense Strategies | PDF",1786002734,30,{"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},"the-impact-of-machine-learning-on-future-defense-strategies","",{"@graph":37,"@context":86},[38,54,69],{"@type":39,"itemListElement":40},"BreadcrumbList",[41,45,49,51],{"item":42,"name":43,"@type":44,"position":21},"https://docshare.wps.com","Home","ListItem",{"item":46,"name":47,"@type":44,"position":48},"https://docshare.wps.com/document/","Document",2,{"item":50,"name":12,"@type":44,"position":20},"https://docshare.wps.com/document/research-report/",{"item":52,"name":13,"@type":44,"position":53},"https://docshare.wps.com/document/the-impact-of-machine-learning-on-future-defense-strategies/128700/",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","2026-08-25","2026-08-06",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},"How does machine learning improve defense cybersecurity?","Question",{"text":76,"@type":77},"The study indicates ML algorithms strengthen threat detection and response to cyber threats by leveraging Anomaly Detection Theory and Game Theory.","Answer",{"name":79,"@type":74,"acceptedAnswer":80},"What role does machine learning play in military logistics and resource allocation?",{"text":81,"@type":77},"ML models, informed by Operations Research and Supply Chain Management Theory, optimize distribution of resources, improve operational efficiency, and support mission readiness.",{"name":83,"@type":74,"acceptedAnswer":84},"What ethical issues arise from deploying machine learning in autonomous defense systems?",{"text":85,"@type":77},"The research highlights concerns about moral responsibility, bias, and strategic risk, requiring comprehensive governance frameworks and robust ethical guidelines.","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},[94,98,102,106,111,116,121,123,128,131,135],{"id":21,"doc_module":4,"doc_module_name":47,"category_name":95,"show_sort_weight":96,"slug":97},"Story & Novel",90,"story-novel",{"id":48,"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":30,"slug":122},"research-report",{"id":124,"doc_module":4,"doc_module_name":47,"category_name":125,"show_sort_weight":126,"slug":127},9,"Religion & Spirituality",20,"religion-spirituality",{"id":126,"doc_module":4,"doc_module_name":47,"category_name":129,"show_sort_weight":126,"slug":130},"World Cup","world-cup",{"id":132,"doc_module":4,"doc_module_name":47,"category_name":133,"show_sort_weight":132,"slug":134},10,"Lifestyle","lifestyle",{"id":136,"doc_module":4,"doc_module_name":47,"category_name":137,"show_sort_weight":107,"slug":138},19,"General","general"]