{"id":2160,"date":"2026-02-12T11:35:38","date_gmt":"2026-02-12T16:35:38","guid":{"rendered":"https:\/\/carleton.ca\/cybersea\/?p=2160"},"modified":"2026-02-12T11:35:39","modified_gmt":"2026-02-12T16:35:39","slug":"new-publication-secmlops-a-comprehensive-framework-for-integrating-security-throughout-the-machine-learning-operations-lifecycle","status":"publish","type":"post","link":"https:\/\/carleton.ca\/cybersea\/2026\/new-publication-secmlops-a-comprehensive-framework-for-integrating-security-throughout-the-machine-learning-operations-lifecycle\/","title":{"rendered":"New Publication: SecMLOps: A comprehensive framework for integrating security throughout the machine learning operations lifecycle"},"content":{"rendered":"\n<section class=\"w-screen px-6 cu-section cu-section--white ml-offset-center md:px-8 lg:px-14\">\n    <div class=\"space-y-6 cu-max-w-child-5xl  md:space-y-10 cu-prose-first-last\">\n\n            <div class=\"cu-textmedia flex flex-col lg:flex-row mx-auto gap-6 md:gap-10 my-6 md:my-12 first:mt-0 max-w-5xl\">\n        <div class=\"justify-start cu-textmedia-content cu-prose-first-last\" style=\"flex: 0 0 100%;\">\n            <header class=\"font-light prose-xl cu-pageheader md:prose-2xl cu-component-updated cu-prose-first-last\">\n                                    <h1 class=\"cu-prose-first-last font-semibold !mt-2 mb-4 md:mb-6 relative after:absolute after:h-px after:bottom-0 after:bg-cu-red after:left-px text-3xl md:text-4xl lg:text-5xl lg:leading-[3.5rem] pb-5 after:w-10 text-cu-black-700 not-prose\">\n                        New Publication: SecMLOps: A comprehensive framework for integrating security throughout the machine learning operations lifecycle\n                    <\/h1>\n                \n                                \n                            <\/header>\n\n                    <\/div>\n\n            <\/div>\n\n    <\/div>\n<\/section>\n\n\n\n<p>Our latest article published in <a href=\"https:\/\/link.springer.com\/journal\/10664\" type=\"link\" id=\"https:\/\/link.springer.com\/journal\/10664\">Empirical Software Engineering<\/a> builds upon the concept of Secure Machine Learning Operations (SecMLOps), providing a comprehensive framework designed to integrate robust security measures throughout the entire ML operations (MLOps) lifecycle. This framework is particularly focused on safeguarding against sophisticated attacks that target various stages of the MLOps lifecycle, thereby enhancing the resilience and trustworthiness of ML applications. Through extensive empirical evaluations, we highlight the trade-offs between security measures and system performance, providing critical insights into optimizing security without unduly impacting operational efficiency. Our findings underscore the importance of a balanced approach, offering valuable guidance for practitioners on how to achieve an optimal balance between security and performance in ML deployments across various domains.See <a href=\"https:\/\/carleton.ca\/cybersea\/publications\/\">Publications<\/a> for more details!<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Our latest article published in Empirical Software Engineering builds upon the concept of Secure Machine Learning Operations (SecMLOps), providing a comprehensive framework designed to integrate robust security measures throughout the entire ML operations (MLOps) lifecycle. This framework is particularly focused on safeguarding against sophisticated attacks that target various stages of the MLOps lifecycle, thereby enhancing [&hellip;]<\/p>\n","protected":false},"author":496,"featured_media":431,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":"","_links_to":"","_links_to_target":""},"categories":[41],"tags":[],"class_list":["post-2160","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-publication"],"acf":{"cu_post_thumbnail":""},"_links":{"self":[{"href":"https:\/\/carleton.ca\/cybersea\/wp-json\/wp\/v2\/posts\/2160","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/carleton.ca\/cybersea\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/carleton.ca\/cybersea\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/carleton.ca\/cybersea\/wp-json\/wp\/v2\/users\/496"}],"replies":[{"embeddable":true,"href":"https:\/\/carleton.ca\/cybersea\/wp-json\/wp\/v2\/comments?post=2160"}],"version-history":[{"count":1,"href":"https:\/\/carleton.ca\/cybersea\/wp-json\/wp\/v2\/posts\/2160\/revisions"}],"predecessor-version":[{"id":2161,"href":"https:\/\/carleton.ca\/cybersea\/wp-json\/wp\/v2\/posts\/2160\/revisions\/2161"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/carleton.ca\/cybersea\/wp-json\/wp\/v2\/media\/431"}],"wp:attachment":[{"href":"https:\/\/carleton.ca\/cybersea\/wp-json\/wp\/v2\/media?parent=2160"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/carleton.ca\/cybersea\/wp-json\/wp\/v2\/categories?post=2160"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/carleton.ca\/cybersea\/wp-json\/wp\/v2\/tags?post=2160"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}