{"id":166114,"date":"2008-06-01T00:00:00","date_gmt":"2008-06-01T00:00:00","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/parallelizing-dynamic-information-flow-tracking\/"},"modified":"2018-10-16T20:08:51","modified_gmt":"2018-10-17T03:08:51","slug":"parallelizing-dynamic-information-flow-tracking","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/parallelizing-dynamic-information-flow-tracking\/","title":{"rendered":"Parallelizing Dynamic Information Flow Tracking"},"content":{"rendered":"<div class=\"asset-content\">\n<p>Dynamic information flow tracking (DIFT) is an important tool for detecting common security attacks and memory bugs. A DIFT tool tracks the flow of information through a monitored program&#8217;s registers and memory locations as the program executes, detecting and containing\/fixing problems on-the-fly. Unfortunately, sequential DIFT tools are quite slow, and DIFT is quite challenging to parallelize. In this paper, we present a new approach to parallelizing DIFT-like functionality. Extending our recent work on accelerating sequential DIFT, we consider a variant of DIFT that tracks the information flow only through unary operations relaxed DIFT, and yet makes sense for detecting security attacks and memory bugs. We present a parallel algorithm for relaxed DIFT, based on symbolic inheritance tracking, which achieves linear speed-up asymptotically. Moreover, we describe techniques for reducing the constant factors, so that speed-ups can be obtained even with just a few processors. We implemented the algorithm in the context of a Log-Based Architectures (LBA) system, which provides hardware support for logging a program trace and delivering it to other (monitoring) processors. Our simulation results on SPEC benchmarks and a video player show that our parallel relaxed DIFT reduces the overhead to as low as 1.2X using 9 monitoring cores on a 16-core chip multiprocessor<\/p>\n<\/div>\n<p><!-- .asset-content --><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Dynamic information flow tracking (DIFT) is an important tool for detecting common security attacks and memory bugs. A DIFT tool tracks the flow of information through a monitored program&#8217;s registers and memory locations as the program executes, detecting and containing\/fixing problems on-the-fly. Unfortunately, sequential DIFT tools are quite slow, and DIFT is quite challenging to [&hellip;]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","footnotes":""},"msr-content-type":[3],"msr-research-highlight":[],"research-area":[13560,13547],"msr-publication-type":[193716],"msr-product-type":[],"msr-focus-area":[],"msr-platform":[],"msr-download-source":[],"msr-locale":[268875],"msr-post-option":[],"msr-field-of-study":[],"msr-conference":[],"msr-journal":[],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-166114","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-programming-languages-software-engineering","msr-research-area-systems-and-networking","msr-locale-en_us"],"msr_publishername":"Symposium on Parallelism in Algorithms and Architectures (SPAA)","msr_edition":"","msr_affiliation":"","msr_published_date":"2008-06-01","msr_host":"","msr_duration":"","msr_version":"","msr_speaker":"","msr_other_contributors":"","msr_booktitle":"","msr_pages_string":"","msr_chapter":"","msr_isbn":"","msr_journal":"","msr_volume":"","msr_number":"","msr_editors":"","msr_series":"","msr_issue":"","msr_organization":"","msr_how_published":"","msr_notes":"","msr_highlight_text":"","msr_release_tracker_id":"","msr_original_fields_of_study":"","msr_download_urls":"","msr_external_url":"","msr_secondary_video_url":"","msr_longbiography":"","msr_microsoftintellectualproperty":1,"msr_main_download":"208172","msr_publicationurl":"","msr_doi":"","msr_publication_uploader":[{"type":"file","title":"fp094-ruwase.pdf","viewUrl":"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2016\/02\/fp094-ruwase.pdf","id":208172,"label_id":0}],"msr_related_uploader":"","msr_attachments":[{"id":208172,"url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2016\/02\/fp094-ruwase.pdf"}],"msr-author-ordering":[{"type":"user_nicename","value":"olruwase","user_id":33157,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=olruwase"},{"type":"text","value":"Phillip B. 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