{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T05:15:57Z","timestamp":1755839757533,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":44,"publisher":"ACM","license":[{"start":{"date-parts":[[2024,8,24]],"date-time":"2024-08-24T00:00:00Z","timestamp":1724457600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/https:\/\/doi.org\/10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62202169,62202170"],"award-info":[{"award-number":["62202169,62202170"]}],"id":[{"id":"10.13039\/https:\/\/doi.org\/10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Open Research Fund of The State Key Laboratory of Blockchain and Data Security, Zhejiang University"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2024,8,25]]},"DOI":"10.1145\/3637528.3671694","type":"proceedings-article","created":{"date-parts":[[2024,8,25]],"date-time":"2024-08-25T04:54:55Z","timestamp":1724561695000},"page":"3255-3266","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["DPSW-Sketch: A Differentially Private Sketch Framework for Frequency Estimation over Sliding Windows"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-7526-985X","authenticated-orcid":false,"given":"Yiping","family":"Wang","sequence":"first","affiliation":[{"name":"East China Normal University, Shanghai, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7661-3917","authenticated-orcid":false,"given":"Yanhao","family":"Wang","sequence":"additional","affiliation":[{"name":"East China Normal University, Shanghai, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0325-1705","authenticated-orcid":false,"given":"Cen","family":"Chen","sequence":"additional","affiliation":[{"name":"East China Normal University &amp; The State Key Laboratory of Blockchain and Data Security, Zhejiang University, Shanghai, China"}]}],"member":"320","published-online":{"date-parts":[[2024,8,24]]},"reference":[{"key":"e_1_3_2_2_1_1","first-page":"49133","article-title":"A Smooth Binary Mechanism for Efficient Private Continual Observation","volume":"36","author":"Andersson Joel Daniel","year":"2023","unstructured":"Joel Daniel Andersson and Rasmus Pagh. 2023. A Smooth Binary Mechanism for Efficient Private Continual Observation. Advances in Neural Information Processing Systems, Vol. 36 (2023), 49133--49145.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_2_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/1055558.1055598"},{"key":"e_1_3_2_2_3_1","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM.2016.7524364"},{"key":"e_1_3_2_2_4_1","first-page":"32450","article-title":"Archimedes Meets Privacy: On Privately Estimating Quantiles in High Dimensions Under Minimal Assumptions","volume":"35","author":"Ben-Eliezer Omri","year":"2022","unstructured":"Omri Ben-Eliezer, Dan Mikulincer, and Ilias Zadik. 2022. Archimedes Meets Privacy: On Privately Estimating Quantiles in High Dimensions Under Minimal Assumptions. Advances in Neural Information Processing Systems, Vol. 35 (2022), 32450--32464.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_2_5_1","volume-title":"The Eleventh International Conference on Learning Representations. OpenReview.net.","author":"Blocki Jeremiah","year":"2023","unstructured":"Jeremiah Blocki, Seunghoon Lee, Tamalika Mukherjee, and Samson Zhou. 2023. Differentially Private $L_2$-Heavy Hitters in the Sliding Window Model. In The Eleventh International Conference on Learning Representations. OpenReview.net."},{"key":"e_1_3_2_2_6_1","volume-title":"Smooth Histograms for Sliding Windows. In 48th Annual IEEE Symposium on Foundations of Computer Science. IEEE, 283--293","author":"Braverman Vladimir","year":"2007","unstructured":"Vladimir Braverman and Rafail Ostrovsky. 2007. Smooth Histograms for Sliding Windows. In 48th Annual IEEE Symposium on Foundations of Computer Science. IEEE, 283--293."},{"key":"e_1_3_2_2_7_1","volume-title":"TCC 2016-B, Beijing, China, October 31-November 3, 2016, Proceedings, Part I. Springer","author":"Bun Mark","year":"2016","unstructured":"Mark Bun and Thomas Steinke. 2016. Concentrated Differential Privacy: Simplifications, Extensions, and Lower Bounds. In Theory of Cryptography - 14th International Conference, TCC 2016-B, Beijing, China, October 31-November 3, 2016, Proceedings, Part I. Springer, Berlin, Heidelberg, 635--658."},{"key":"e_1_3_2_2_8_1","volume-title":"PETS 2012, Vigo, Spain, July 11--13, 2012, Proceedings. Springer","author":"Hubert Chan T.-H.","year":"2012","unstructured":"T.-H. Hubert Chan, Mingfei Li, Elaine Shi, and Wenchang Xu. 2012. Differentially Private Continual Monitoring of Heavy Hitters from Distributed Streams. In Privacy Enhancing Technologies - 12th International Symposium, PETS 2012, Vigo, Spain, July 11--13, 2012, Proceedings. Springer, Berlin, Heidelberg, 140--159."},{"key":"e_1_3_2_2_9_1","article-title":"Private and Continual Release of Statistics","volume":"14","author":"Hubert Chan T.-H.","year":"2011","unstructured":"T.-H. Hubert Chan, Elaine Shi, and Dawn Song. 2011. Private and Continual Release of Statistics. ACM Transactions on Information and System Security, Vol. 14, 3, Article 26 (2011), bibinfonumpages24 pages.","journal-title":"ACM Transactions on Information and System Security"},{"key":"e_1_3_2_2_10_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0304-3975(03)00400-6"},{"key":"e_1_3_2_2_11_1","doi-asserted-by":"publisher","DOI":"10.1561\/1900000004"},{"key":"e_1_3_2_2_12_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jalgor.2003.12.001"},{"key":"e_1_3_2_2_13_1","doi-asserted-by":"publisher","DOI":"10.1137\/S0097539701398363"},{"key":"e_1_3_2_2_14_1","volume-title":"2006 a. Our Data","author":"Dwork Cynthia","year":"2006","unstructured":"Cynthia Dwork, Krishnaram Kenthapadi, Frank McSherry, Ilya Mironov, and Moni Naor. 2006 a. Our Data, Ourselves: Privacy Via Distributed Noise Generation. In Advances in Cryptology -- EUROCRYPT 2006. Springer, Berlin, Heidelberg, 486--503."},{"volume-title":"Theory of Cryptography","author":"Dwork Cynthia","key":"e_1_3_2_2_15_1","unstructured":"Cynthia Dwork, Frank McSherry, Kobbi Nissim, and Adam D. Smith. 2006 b. Calibrating Noise to Sensitivity in Private Data Analysis. In Theory of Cryptography. Springer, Berlin, Heidelberg, 265--284."},{"volume-title":"Proceedings of the 42nd ACM Symposium on Theory of Computing (STOC '10)","author":"Dwork Cynthia","key":"e_1_3_2_2_16_1","unstructured":"Cynthia Dwork, Moni Naor, Toniann Pitassi, and Guy N. Rothblum. 2010. Differential privacy under continual observation. In Proceedings of the 42nd ACM Symposium on Theory of Computing (STOC '10). Association for Computing Machinery, New York, NY, USA, 715--724."},{"key":"e_1_3_2_2_17_1","volume-title":"Differentially Private Continual Releases of Streaming Frequency Moment Estimations. In 14th Innovations in Theoretical Computer Science Conference (ITCS","author":"Epasto Alessandro","year":"2023","unstructured":"Alessandro Epasto, Jieming Mao, Andres Munoz Medina, Vahab Mirrokni, Sergei Vassilvitskii, and Peilin Zhong. 2023. Differentially Private Continual Releases of Streaming Frequency Moment Estimations. In 14th Innovations in Theoretical Computer Science Conference (ITCS 2023). Schloss Dagstuhl -- Leibniz-Zentrum f\u00fcr Informatik, Dagstuhl, Germany, 48:1--48:24."},{"key":"e_1_3_2_2_18_1","doi-asserted-by":"publisher","DOI":"10.1145\/633025.633056"},{"key":"e_1_3_2_2_19_1","volume-title":"Proceedings of the 40th International Conference on Machine Learning. PMLR, 10072--10092","author":"Fichtenberger Hendrik","year":"2023","unstructured":"Hendrik Fichtenberger, Monika Henzinger, and Jalaj Upadhyay. 2023. Constant Matters: Fine-grained Error Bound on Differentially Private Continual Observation. In Proceedings of the 40th International Conference on Machine Learning. PMLR, 10072--10092."},{"key":"e_1_3_2_2_20_1","volume-title":"14th Innovations in Theoretical Computer Science Conference (ITCS","author":"Ghazi Badih","year":"2023","unstructured":"Badih Ghazi, Ravi Kumar, Jelani Nelson, and Pasin Manurangsi. 2023. Private Counting of Distinct and k-Occurring Items in Time Windows. In 14th Innovations in Theoretical Computer Science Conference (ITCS 2023). Schloss Dagstuhl -- Leibniz-Zentrum f\u00fcr Informatik, Dagstuhl, Germany, 55:1--55:24."},{"key":"e_1_3_2_2_21_1","volume-title":"Proceedings of the 38th International Conference on Machine Learning. PMLR, 3713--3722","author":"Gillenwater Jennifer","year":"2021","unstructured":"Jennifer Gillenwater, Matthew Joseph, and Alex Kulesza. 2021. Differentially Private Quantiles. In Proceedings of the 38th International Conference on Machine Learning. PMLR, 3713--3722."},{"key":"e_1_3_2_2_22_1","unstructured":"Google. 2024. How Google retains data we collect. https:\/\/policies.google.com\/technologies\/retention."},{"key":"e_1_3_2_2_23_1","doi-asserted-by":"publisher","DOI":"10.1145\/3394486.3403144"},{"key":"e_1_3_2_2_24_1","doi-asserted-by":"publisher","DOI":"10.1145\/3511808.3557257"},{"key":"e_1_3_2_2_25_1","volume-title":"Proceedings of the 40th International Conference on Machine Learning. PMLR, 12846--12865","author":"Hehir Jonathan","year":"2023","unstructured":"Jonathan Hehir, Daniel Ting, and Graham Cormode. 2023. Sketch-Flip-Merge: Mergeable Sketches for Private Distinct Counting. In Proceedings of the 40th International Conference on Machine Learning. PMLR, 12846--12865."},{"key":"e_1_3_2_2_26_1","doi-asserted-by":"publisher","DOI":"10.14778\/3547305.3547312"},{"key":"e_1_3_2_2_27_1","volume-title":"Proceedings of the 39th International Conference on Machine Learning. PMLR, 10751--10761","author":"Kaplan Haim","year":"2022","unstructured":"Haim Kaplan, Shachar Schnapp, and Uri Stemmer. 2022. Differentially Private Approximate Quantiles. In Proceedings of the 39th International Conference on Machine Learning. PMLR, 10751--10761."},{"key":"e_1_3_2_2_28_1","doi-asserted-by":"publisher","DOI":"10.1145\/3584372.3588673"},{"key":"e_1_3_2_2_29_1","volume-title":"Efficient Private Statistics with Succinct Sketches. In 23rd Annual Network and Distributed System Security Symposium (NDSS '16)","author":"Melis Luca","year":"2016","unstructured":"Luca Melis, George Danezis, and Emiliano De Cristofaro. 2016. Efficient Private Statistics with Succinct Sketches. In 23rd Annual Network and Distributed System Security Symposium (NDSS '16). The Internet Society, bibinfonumpages15 pages."},{"volume-title":"Proceedings of the Thirtieth ACM SIGMOD-SIGACT-SIGART Symposium on Principles of Database Systems (PODS '11)","author":"Mir Darakhshan J.","key":"e_1_3_2_2_30_1","unstructured":"Darakhshan J. Mir, S. Muthukrishnan, Aleksandar Nikolov, and Rebecca N. Wright. 2011. Pan-private algorithms via statistics on sketches. In Proceedings of the Thirtieth ACM SIGMOD-SIGACT-SIGART Symposium on Principles of Database Systems (PODS '11). Association for Computing Machinery, New York, NY, USA, 37--48."},{"key":"e_1_3_2_2_31_1","doi-asserted-by":"publisher","DOI":"10.1016\/0167-6423(82)90012-0"},{"key":"e_1_3_2_2_32_1","doi-asserted-by":"publisher","DOI":"10.1561\/0400000002"},{"key":"e_1_3_2_2_33_1","first-page":"25631","article-title":"Improved Utility Analysis of Private CountSketch","volume":"35","author":"Pagh Rasmus","year":"2022","unstructured":"Rasmus Pagh and Mikkel Thorup. 2022. Improved Utility Analysis of Private CountSketch. Advances in Neural Information Processing Systems, Vol. 35 (2022), 25631--25643.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_2_34_1","doi-asserted-by":"publisher","DOI":"10.14778\/2336664.2336672"},{"key":"e_1_3_2_2_35_1","volume-title":"Private Continual Release of Real-Valued Data Streams. In 26th Annual Network and Distributed System Security Symposium (NDSS '19)","author":"Perrier Victor","year":"2019","unstructured":"Victor Perrier, Hassan Jameel Asghar, and Dali Kaafar. 2019. Private Continual Release of Real-Valued Data Streams. In 26th Annual Network and Distributed System Security Symposium (NDSS '19). The Internet Society, bibinfonumpages13 pages."},{"key":"e_1_3_2_2_36_1","doi-asserted-by":"publisher","DOI":"10.1109\/NCA.2015.46"},{"key":"e_1_3_2_2_37_1","first-page":"19561","article-title":"The Flajolet-Martin Sketch Itself Preserves Differential Privacy: Private Counting with Minimal Space","volume":"33","author":"Smith Adam D.","year":"2020","unstructured":"Adam D. Smith, Shuang Song, and Abhradeep Thakurta. 2020. The Flajolet-Martin Sketch Itself Preserves Differential Privacy: Private Counting with Minimal Space. Advances in Neural Information Processing Systems, Vol. 33 (2020), 19561--19572.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_2_38_1","volume-title":"Proceedings of the 36th International Conference on Machine Learning. PMLR, 6363--6372","author":"Upadhyay Jalaj","year":"2019","unstructured":"Jalaj Upadhyay. 2019. Sublinear Space Private Algorithms Under the Sliding Window Model. In Proceedings of the 36th International Conference on Machine Learning. PMLR, 6363--6372."},{"key":"e_1_3_2_2_39_1","volume-title":"Differentially Private Fractional Frequency Moments Estimation with Polylogarithmic Space. In The Tenth International Conference on Learning Representations. OpenReview.net.","author":"Wang Lun","year":"2022","unstructured":"Lun Wang, Iosif Pinelis, and Dawn Song. 2022. Differentially Private Fractional Frequency Moments Estimation with Polylogarithmic Space. In The Tenth International Conference on Learning Representations. OpenReview.net."},{"key":"e_1_3_2_2_40_1","doi-asserted-by":"publisher","DOI":"10.1145\/3580305.3599432"},{"key":"e_1_3_2_2_41_1","volume-title":"Differentially Private Frequency Sketches for Intermittent Queries on Large Data Streams. In 2020 IEEE International Conference on Big Data. IEEE, 4083--4092","author":"Yildirim Sinan","year":"2020","unstructured":"Sinan Yildirim, Kamer Kaya, Soner Aydin, and Hakan Bugra Erentug. 2020. Differentially Private Frequency Sketches for Intermittent Queries on Large Data Streams. In 2020 IEEE International Conference on Big Data. IEEE, 4083--4092."},{"key":"e_1_3_2_2_42_1","first-page":"12691","article-title":"Differentially Private Linear Sketches: Efficient Implementations and Applications","volume":"35","author":"Zhao Fuheng","year":"2022","unstructured":"Fuheng Zhao, Dan Qiao, Rachel Redberg, Divyakant Agrawal, Amr El Abbadi, and Yu-Xiang Wang. 2022. Differentially Private Linear Sketches: Efficient Implementations and Applications. Advances in Neural Information Processing Systems, Vol. 35 (2022), 12691--12704.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_2_43_1","doi-asserted-by":"publisher","DOI":"10.1145\/3448016.3452775"},{"key":"e_1_3_2_2_44_1","volume-title":"Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics. PMLR, 3837--3847","author":"Zhu Wennan","year":"2020","unstructured":"Wennan Zhu, Peter Kairouz, Brendan McMahan, Haicheng Sun, and Wei Li. 2020. Federated Heavy Hitters Discovery with Differential Privacy. In Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics. PMLR, 3837--3847."}],"event":{"name":"KDD '24: The 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","sponsor":["SIGMOD ACM Special Interest Group on Management of Data","SIGKDD ACM Special Interest Group on Knowledge Discovery in Data"],"location":"Barcelona Spain","acronym":"KDD '24"},"container-title":["Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3637528.3671694","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3637528.3671694","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T00:06:00Z","timestamp":1750291560000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3637528.3671694"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,8,24]]},"references-count":44,"alternative-id":["10.1145\/3637528.3671694","10.1145\/3637528"],"URL":"https:\/\/doi.org\/10.1145\/3637528.3671694","relation":{},"subject":[],"published":{"date-parts":[[2024,8,24]]},"assertion":[{"value":"2024-08-24","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}