{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,31]],"date-time":"2026-03-31T16:02:31Z","timestamp":1774972951850,"version":"3.50.1"},"reference-count":15,"publisher":"Association for Computing Machinery (ACM)","issue":"5","license":[{"start":{"date-parts":[[2018,10,1]],"date-time":"2018-10-01T00:00:00Z","timestamp":1538352000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["Queue"],"published-print":{"date-parts":[[2018,10]]},"abstract":"<jats:p>With the dramatic improvement in both computer speeds and the efficiency of SAT and other NP-hard solvers in the last decade, DRAs on statistical databases are no longer just a theoretical danger. The vast quantity of data products published by statistical agencies each year may give a determined attacker more than enough information to reconstruct some or all of a target database and breach the privacy of millions of people. 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