HyperLogLog: Exponentially Bad in Adversarial Settings
暂无分享,去创建一个
[1] Jean-Philippe Aumasson,et al. SipHash: A Fast Short-Input PRF , 2012, INDOCRYPT.
[2] Alexander Hall,et al. HyperLogLog in practice: algorithmic engineering of a state of the art cardinality estimation algorithm , 2013, EDBT '13.
[3] Lajos Rónyai,et al. Factoring polynomials over finite fields , 1987, 28th Annual Symposium on Foundations of Computer Science (sfcs 1987).
[4] Dan S. Wallach,et al. Denial of Service via Algorithmic Complexity Attacks , 2003, USENIX Security Symposium.
[5] Kyu-Young Whang,et al. A linear-time probabilistic counting algorithm for database applications , 1990, TODS.
[6] Haim Kaplan,et al. Adversarially Robust Streaming Algorithms via Differential Privacy , 2020, NeurIPS.
[7] Raja Chiky,et al. How can sliding HyperLogLog and EWMA detect port scan attacks in IP traffic? , 2014, EURASIP J. Inf. Secur..
[8] David P. Woodruff,et al. A Framework for Adversarially Robust Streaming Algorithms , 2020, SIGMOD Rec..
[9] P. Flajolet,et al. Loglog counting of large cardinalities , 2003 .
[10] Jacob Nelson,et al. Evaluating the Power of Flexible Packet Processing for Network Resource Allocation , 2017, NSDI.
[11] P. Flajolet,et al. HyperLogLog: the analysis of a near-optimal cardinality estimation algorithm , 2007 .
[12] Chao Li,et al. Improved Cryptanalysis on SipHash , 2019, CANS.
[13] Russ Bubley,et al. Randomized algorithms , 1995, CSUR.
[14] Georges Hébrail,et al. Sliding HyperLogLog: Estimating Cardinality in a Data Stream over a Sliding Window , 2010, 2010 IEEE International Conference on Data Mining Workshops.
[15] Pedro Reviriego,et al. Security of HyperLogLog (HLL) Cardinality Estimation: Vulnerabilities and Protection , 2020, IEEE Communications Letters.
[16] Tight Bounds for Adversarially Robust Streams and Sliding Windows via Difference Estimators , 2020, 2021 IEEE 62nd Annual Symposium on Foundations of Computer Science (FOCS).
[17] Haim Kaplan,et al. Separating Adaptive Streaming from Oblivious Streaming Using the Bounded Storage Model , 2021, CRYPTO.
[18] Cédric Lauradoux,et al. The Power of Evil Choices in Bloom Filters , 2015, 2015 45th Annual IEEE/IFIP International Conference on Dependable Systems and Networks.
[19] Marcos Dias de Assunção,et al. Apache Spark , 2019, Encyclopedia of Big Data Technologies.
[20] Otmar Ertl,et al. New Cardinality Estimation Methods for HyperLogLog Sketches , 2017, ArXiv.
[21] Christopher Patton,et al. Probabilistic Data Structures in Adversarial Environments , 2019, CCS.
[22] Alexander Hall,et al. Processing a Trillion Cells per Mouse Click , 2012, Proc. VLDB Endow..
[23] Jeffrey F. Naughton,et al. Clocked adversaries for hashing , 1993, Algorithmica.
[24] Sujata Garera,et al. Challenges in teaching a graduate course in applied cryptography , 2009, SGCS.
[25] Florian Mendel,et al. Differential Cryptanalysis of SipHash , 2014, Selected Areas in Cryptography.
[26] Moni Naor,et al. Bloom Filters in Adversarial Environments , 2015, CRYPTO.
[27] David A. Basin,et al. Cardinality Estimators do not Preserve Privacy , 2018, Proc. Priv. Enhancing Technol..