{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,10]],"date-time":"2025-09-10T22:37:46Z","timestamp":1757543866804,"version":"3.40.3"},"publisher-location":"Cham","reference-count":35,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031651748"},{"type":"electronic","value":"9783031651755"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024]]},"DOI":"10.1007\/978-3-031-65175-5_4","type":"book-chapter","created":{"date-parts":[[2024,7,25]],"date-time":"2024-07-25T14:43:01Z","timestamp":1721918581000},"page":"46-60","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["PRIDA: PRIvacy-Preserving Data Aggregation with\u00a0Multiple Data Customers"],"prefix":"10.1007","author":[{"given":"Beyza","family":"Bozdemir","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bet\u00fcl A\u015fk\u0131n","family":"\u00d6zdemir","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Melek","family":"\u00d6nen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,7,26]]},"reference":[{"doi-asserted-by":"crossref","unstructured":"Addanki, S., Garbe, K., Jaffe, E., Ostrovsky, R., Polychroniadou, A.: Prio+: privacy preserving aggregate statistics via boolean shares. In: SCN (2022)","key":"4_CR1","DOI":"10.1007\/978-3-031-14791-3_23"},{"unstructured":"Albrecht, M., et al.: Homomorphic encryption security standard (2018)","key":"4_CR2"},{"key":"4_CR3","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"483","DOI":"10.1007\/978-3-642-29011-4_29","volume-title":"Advances in Cryptology \u2013 EUROCRYPT 2012","author":"G Asharov","year":"2012","unstructured":"Asharov, G., Jain, A., L\u00f3pez-Alt, A., Tromer, E., Vaikuntanathan, V., Wichs, D.: Multiparty computation with low communication, computation and interaction via threshold FHE. In: Pointcheval, D., Johansson, T. (eds.) EUROCRYPT 2012. LNCS, vol. 7237, pp. 483\u2013501. Springer, Heidelberg (2012). https:\/\/doi.org\/10.1007\/978-3-642-29011-4_29"},{"doi-asserted-by":"crossref","unstructured":"Bagdasaryan, E., et al.: Towards sparse federated analytics: location heatmaps under distributed differential privacy with secure aggregation. In: PoPETs (2022)","key":"4_CR4","DOI":"10.56553\/popets-2022-0104"},{"doi-asserted-by":"crossref","unstructured":"Balle, B., Bell, J., Gasc\u00f3n, A., Nissim, K.: Private summation in the multi-message shuffle model. In: CCS (2020)","key":"4_CR5","DOI":"10.1145\/3372297.3417242"},{"key":"4_CR6","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"420","DOI":"10.1007\/3-540-46766-1_34","volume-title":"Advances in Cryptology \u2014 CRYPTO \u201991","author":"D Beaver","year":"1992","unstructured":"Beaver, D.: Efficient multiparty protocols using circuit randomization. In: Feigenbaum, J. (ed.) CRYPTO 1991. LNCS, vol. 576, pp. 420\u2013432. Springer, Heidelberg (1992). https:\/\/doi.org\/10.1007\/3-540-46766-1_34"},{"doi-asserted-by":"crossref","unstructured":"Bell, J., Bonawitz, K.A., Gasc\u00f3n, A., Lepoint, T., Raykova, M.: Secure single-server aggregation with (poly)logarithmic overhead. In: CCS (2020)","key":"4_CR7","DOI":"10.1145\/3372297.3417885"},{"key":"4_CR8","first-page":"1","volume":"18","author":"F Benhamouda","year":"2016","unstructured":"Benhamouda, F., Joye, M., Libert, B.: A new framework for privacy-preserving aggregation of time-series data. TIFS 18, 1\u201321 (2016)","journal-title":"TIFS"},{"doi-asserted-by":"crossref","unstructured":"Bilogrevic, I., Freudiger, J., Cristofaro, E.D., Uzun, E.: What\u2019s the gist? privacy-preserving aggregation of user profiles. In: ESORICS (2014)","key":"4_CR9","DOI":"10.1007\/978-3-319-11212-1_8"},{"doi-asserted-by":"crossref","unstructured":"Bonawitz, K., et al.: Practical secure aggregation for privacy-preserving machine learning. In: CCS (2017)","key":"4_CR10","DOI":"10.1145\/3133956.3133982"},{"unstructured":"Bozdemir, B., Askin\u00a0\u00d6zdemir, B., \u00d6nen, M.: PRIDA: PRIvacy-preserving Data Aggregation with multiple data customers (2024). https:\/\/eprint.iacr.org\/2024\/074.pdf","key":"4_CR11"},{"unstructured":"Burkhart, M., Strasser, M., Many, D., Dimitropoulos, X.: Sepia: privacy-preserving aggregation of multi-domain network events and statistics. In: USENIX Security (2010)","key":"4_CR12"},{"unstructured":"Corrigan-Gibbs, H., Boneh, D.: Prio: private, robust, and scalable computation of aggregate statistics. In: NSDI (2017)","key":"4_CR13"},{"doi-asserted-by":"crossref","unstructured":"Davidson, A., Snyder, P., Quirk, E.B., Genereux, J., Livshits, B.: STAR: distributed secret sharing for private threshold aggregation reporting. In: CCS (2022)","key":"4_CR14","DOI":"10.1145\/3548606.3560631"},{"doi-asserted-by":"crossref","unstructured":"Erkin, Z.: Private data aggregation with groups for smart grids in a dynamic setting using crt. In: WIFS (2015)","key":"4_CR15","DOI":"10.1109\/WIFS.2015.7368584"},{"doi-asserted-by":"crossref","unstructured":"Fereidooni, H., et al.: Safelearn: secure aggregation for private FEderated Learning (2021)","key":"4_CR16","DOI":"10.1109\/SPW53761.2021.00017"},{"doi-asserted-by":"crossref","unstructured":"Froelicher, D., et al.: Unlynx: a decentralized system for privacy-conscious data sharing. In: PoPETs (2017)","key":"4_CR17","DOI":"10.1515\/popets-2017-0047"},{"doi-asserted-by":"crossref","unstructured":"Froelicher, D., et al.: Scalable privacy-preserving distributed learning. In: PoPETs (2021)","key":"4_CR18","DOI":"10.2478\/popets-2021-0030"},{"doi-asserted-by":"crossref","unstructured":"Froelicher, D., Troncoso-Pastoriza, J.R., Sousa, J.S., Hubaux, J.: Drynx: decentralized, secure, verifiable system for statistical queries and machine learning on distributed datasets. CoRR (2019)","key":"4_CR19","DOI":"10.1109\/TIFS.2020.2976612"},{"doi-asserted-by":"crossref","unstructured":"Goldreich, O., Micali, S., Wigderson, A.: How to play any mental game, or a completeness theorem for protocols with honest majority. In: STOC (2019)","key":"4_CR20","DOI":"10.1145\/3335741.3335755"},{"unstructured":"Ion, M., et al.: Private intersection-sum protocols with applications to attributing aggregate ad conversions. In: EuroS & P (2020)","key":"4_CR21"},{"doi-asserted-by":"crossref","unstructured":"Karako\u00e7, F., \u00d6nen, M., Bilgin, Z.: Secure aggregation against malicious users. In: SACMAT (2021)","key":"4_CR22","DOI":"10.1145\/3450569.3463572"},{"doi-asserted-by":"crossref","unstructured":"Kursawe, K., Danezis, G., Kohlweiss, M.: Privacy-friendly aggregation for the smart-grid. In: PoPETs (2011)","key":"4_CR23","DOI":"10.1007\/978-3-642-22263-4_10"},{"doi-asserted-by":"crossref","unstructured":"Leontiadis, I., Elkhiyaoui, K., Molva, R.: Private and dynamic time-series data aggregation with trust relaxation. In: CANS (2014)","key":"4_CR24","DOI":"10.1007\/978-3-319-12280-9_20"},{"doi-asserted-by":"crossref","unstructured":"Leontiadis, I., Elkhiyaoui, K., \u00d6nen, M., Molva, R.: PUDA - privacy and unforgeability for data aggregation. In: CANS (2015)","key":"4_CR25","DOI":"10.1007\/978-3-319-26823-1_1"},{"doi-asserted-by":"crossref","unstructured":"Lindell, Y.: How to simulate it - a tutorial on the simulation proof technique. Tutorials on the Foundations of Cryptography: Dedicated to Oded Goldreich (2017)","key":"4_CR26","DOI":"10.1007\/978-3-319-57048-8"},{"unstructured":"Lopez-Alt, A., Tromer, E., Vaikuntanathan, V.: Cloud-assisted multiparty computation from fully homomorphic encryption. ePrint (2011)","key":"4_CR27"},{"doi-asserted-by":"crossref","unstructured":"Mohamad, M., \u00d6nen, M., Ben\u00a0Jaballah, W., Conti, M.: Sok: secure aggregation based on cryptographic schemes for federated learning. In: PoPETs (2023)","key":"4_CR28","DOI":"10.56553\/popets-2023-0009"},{"unstructured":"Polyakov, Y.: PALISADE: introduction to multiparty homomorphic encryption (2020). https:\/\/palisade-crypto.org\/wp-content\/uploads\/2020\/10\/PALISADE-10-30-MULTIPARTY.pdf","key":"4_CR29"},{"doi-asserted-by":"crossref","unstructured":"Rastogi, V., Nath, S.: Differentially private aggregation of distributed time-series with transformation and encryption. In: SIGMOD (2010)","key":"4_CR30","DOI":"10.1145\/1807167.1807247"},{"doi-asserted-by":"crossref","unstructured":"Sav, S., et al.: POSEIDON: privacy-preserving federated neural network learning. In: NDSS (2021)","key":"4_CR31","DOI":"10.14722\/ndss.2021.24119"},{"unstructured":"Shi, E., Chan, T.H., Rieffel, E.G., Chow, R., Song, D.: Privacy-preserving aggregation of time-series data. In: NDSS (2011)","key":"4_CR32"},{"key":"4_CR33","first-page":"479","volume":"2","author":"J So","year":"2021","unstructured":"So, J., Guler, B., Avestimehr, A.S.: Turbo-aggregate: breaking the quadratic aggregation barrier in secure federated learning. IEEE SAIT 2, 479\u2013489 (2021)","journal-title":"IEEE SAIT"},{"doi-asserted-by":"crossref","unstructured":"Zhang, A., Ghazi, B., Kamal, N., Manurangsi, P., Ravikumar, R.K.: Private aggregation of trajectories. In: PoPETs (2022)","key":"4_CR34","DOI":"10.56553\/popets-2022-0125"},{"doi-asserted-by":"crossref","unstructured":"Zhou, M., Wang, T., Chan, T.H., Fanti, G., Shi, E.: Locally differentially private sparse vector aggregation. In: S &P (2022)","key":"4_CR35","DOI":"10.1109\/SP46214.2022.9833635"}],"container-title":["IFIP Advances in Information and Communication Technology","ICT Systems Security and Privacy Protection"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-65175-5_4","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,7,25]],"date-time":"2024-07-25T14:43:16Z","timestamp":1721918596000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-65175-5_4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9783031651748","9783031651755"],"references-count":35,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-65175-5_4","relation":{},"ISSN":["1868-4238","1868-422X"],"issn-type":[{"type":"print","value":"1868-4238"},{"type":"electronic","value":"1868-422X"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"26 July 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"SEC","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"IFIP International Conference on ICT Systems Security and Privacy Protection","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Edinburgh","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"United Kingdom","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12 June 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14 June 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"39","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"sec2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/ifipsec2024.co.uk\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}