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Streaming Algorithms for Robust Distinct Elements

Di Chen, Qin Zhang
2016 Proceedings of the 2016 International Conference on Management of Data - SIGMOD '16  
In this paper, we formalize the problem of robust distinct elements, and develop space and time-efficient streaming algorithms for datasets in the Euclidean space, using a novel technique we call bucket  ...  Moreover, we formally prove that our algorithms are still effective under small distinct elements ambiguity. Our experiments demonstrate the practicality of our algorithms.  ...  algorithm for distinct elements in the hashing space.  ... 
doi:10.1145/2882903.2882915 dblp:conf/sigmod/ChenZ16 fatcat:eqa23f2fxjbpjm4xbpqamlv7km

Adversarially Robust Streaming Algorithms via Differential Privacy [article]

Avinatan Hassidim, Haim Kaplan, Yishay Mansour, Yossi Matias, Uri Stemmer
2020 arXiv   pre-print
This connection allows us to design new adversarially robust streaming algorithms that outperform the current state-of-the-art constructions for many interesting regimes of parameters.  ...  We establish a connection between adversarial robustness of streaming algorithms and the notion of differential privacy.  ...  Acknowledgments The authors are grateful to Amos Beimel and Edith Cohen for many helpful discussions.  ... 
arXiv:2004.05975v1 fatcat:kgdgss37gjdb5k4zlxo3cmw22m

A Framework for Adversarially Robust Streaming Algorithms [article]

Omri Ben-Eliezer and Rajesh Jayaram and David P. Woodruff and Eylon Yogev
2021 arXiv   pre-print
In this work, we show that the answer is positive for various important streaming problems in the insertion-only model, including distinct elements and more generally F_p-estimation, F_p-heavy hitters,  ...  This raises the natural question of whether there exist efficient adversarially robust (randomized) streaming algorithms for these problems.  ...  Acknowledgments The authors wish to thank Arnold Filtser for invaluable feedback, and the anonymous reviewers for many helpful suggestions.  ... 
arXiv:2003.14265v3 fatcat:4aiym236pff4ferums5uknwmim

Connecting Robust Shuffle Privacy and Pan-Privacy [article]

Victor Balcer, Albert Cheu, Matthew Joseph, Jieming Mao
2020 arXiv   pre-print
Focusing on the dependence on the domain size k, we find that robust approximate shuffle privacy and approximate pan-privacy have additive error Θ(√(k)) for counting distinct elements.  ...  First, we give robustly shuffle private protocols and upper bounds for counting distinct elements and uniformity testing.  ...  Acknowledgments We thank Clément Canonne for simplifying the form of the uniformity testing lower bound and Adam Smith for useful discussions regarding the pan-privacy definition.  ... 
arXiv:2004.09481v4 fatcat:wiwpkpu32fgpzgfweqw65aez6e

Adversarially Robust Streaming via Dense–Sparse Trade-offs [article]

Omri Ben-Eliezer, Talya Eden, Krzysztof Onak
2021 arXiv   pre-print
More specifically, our space complexity for F_2-estimation is Õ(m^2/5) and for F_0-estimation, i.e., counting the number of distinct elements, it is Õ(m^1/3).  ...  A streaming algorithm is adversarially robust if it is guaranteed to perform correctly even in the presence of an adaptive adversary.  ...  algorithm (Algorithm 2) for (1 ± .25)-approximation of number of distinct elements with error parameter δ/2 7 A approx ← (m/interval)-query adversarially robust streaming algorithm (Algorithm 2) for  ... 
arXiv:2109.03785v1 fatcat:5lckm4uzczbybmlz5r25vbuo2i

Streaming Algorithms for Robust, Real-Time Detection of DDoS Attacks

Sumit Ganguly, Minos Garofalakis, Rajeev Rastogi, Krishan Sabnani
2007 27th International Conference on Distributed Computing Systems (ICDCS '07)  
In this paper, we propose novel data-streaming algorithms for the robust, real-time detection of DDoS activity in large ISP networks.  ...  The key element of our solution is a new, hashbased synopsis data structure for network-data streams that allows us to efficiently track, in guaranteed small space and time, destination IP addresses in  ...  Conclusions We have proposed novel data-streaming algorithms for the robust, real-time detection of DDoS activity in large ISP networks.  ... 
doi:10.1109/icdcs.2007.142 dblp:conf/icdcs/GangulyGRS07 fatcat:bfiipr52szddjdfyjzjdiabi4q

AnKLe: Detecting Attacks in Large Scale Systems via Information Divergence

E. Anceaume, Y. Busnel, S. Gambs
2012 2012 Ninth European Dependable Computing Conference  
To address this issue, we propose AnKLe (for Attack-tolerant eNhanced Kullback-Leibler divergence Estimator), a novel algorithm for estimating the KL divergence of an observed stream compared to the expected  ...  Experimental results show that the estimation provided by AnKLe remains accurate even for different adversarial settings for which the quality of other methods dramatically decreases.  ...  [22] , which is so far the most efficient space and time algorithm for approximating the number of distinct elements in a stream in a single pass (and this even if the stream is adversarially ordered  ... 
doi:10.1109/edcc.2012.9 dblp:conf/edcc/AnceaumeBG12 fatcat:f5uqp2eipvd2xcz6wgnivcomwq

Distinct Sampling on Streaming Data with Near-Duplicates [article]

Jiecao Chen, Qin Zhang
2018 arXiv   pre-print
The goal of distinct sampling is to return a distinct element uniformly at random from the universe of elements, given that all the near-duplicates are treated as the same element.  ...  In this paper we study how to perform distinct sampling in the streaming model where data contain near-duplicates.  ...  DISTINCT ELEMENTS In this section we show that our algorithms for robust ℓ 0 -sampling can be used for approximating the number of robust distinct elements in both infinite window and sliding window settings  ... 
arXiv:1810.12388v1 fatcat:mc7lyekkora3lpwyoyg4hiqqkm

Distinct-Values Estimation over Data Streams [chapter]

Phillip B. Gibbons
2016 Data-Centric Systems and Applications  
In this chapter, we consider the problem of estimating the number of distinct values in a data stream with repeated values.  ...  Distinctvalues estimation was one of the first data stream problems studied: In the mid-1980's, Flajolet and Martin gave an effective algorithm that uses only logarithmic space.  ...  Summary of the main algorithms presented in this chapter for distinct-values estimation over a data stream of values distributed streams, and sensor networks.  ... 
doi:10.1007/978-3-540-28608-0_6 fatcat:tzyj7cs5f5ftfnu2joy3gyhhbq

Separating Adaptive Streaming from Oblivious Streaming [article]

Haim Kaplan, Yishay Mansour, Kobbi Nissim, Uri Stemmer
2021 arXiv   pre-print
We present a streaming problem for which every adversarially-robust streaming algorithm must use polynomial space, while there exists a classical (oblivious) streaming algorithm that uses only polylogarithmic  ...  This is the first separation between oblivious streaming and adversarially-robust streaming, and resolves one of the central open questions in adversarial robust streaming.  ...  Algorithm used: An adversarially robust streaming algorithm A for the SADA problem with (α, β)-accuracy for streams of length m.  ... 
arXiv:2101.10836v2 fatcat:5tgvfkkhjvfg7i2dvzbeloicyi

Data Streams and Applications in Computer Science

David P. Woodruff
2014 Bulletin of the European Association for Theoretical Computer Science  
], who studied the distinct elements problem.  ...  One should note that the randomness is in the random coin tosses of the algorithm rather than in the Distinct Elements One of the earliest works on streaming was that of Flajolet and Martin in 1985 [25  ...  Here, though, the hashing is a bit different than that for the distinct elements problem.  ... 
dblp:journals/eatcs/Woodruff14 fatcat:jdm57pkrrbejlh5xuhcxmrd4mu

Efficient Distinct Heavy Hitters for DNS DDoS Attack Detection [article]

Yehuda Afek and Anat Bremler-Barr and Edith Cohen and Shir Landau Feibish and Michal Shagam
2016 arXiv   pre-print
When stream elements consist of a pairs, () a distinct heavy hitter (dhh) is a key that is paired with a large number of different subkeys.  ...  Efficient algorithms are also presented for cHH detection.  ...  We have presented new and efficient algorithms for distinct Heavy Hitters and combined Heavy Hitters detection, as well as a system for detection of RSDDoS attacks on the DNS service.  ... 
arXiv:1612.02636v1 fatcat:vniqmmzqpzhhzmpvfoplqcwrci

Processing set expressions over continuous update streams

Sumit Ganguly, Minos Garofalakis, Rajeev Rastogi
2003 Proceedings of the 2003 ACM SIGMOD international conference on on Management of data - SIGMOD '03  
There is growing interest in algorithms for processing and querying continuous data streams (i.e., data that is seen only once in a fixed order) with limited memory resources.  ...  In this paper, we propose the first space-efficient algorithmic solution for estimating the cardinality of full-fledged set expressions over general update streams.  ...  the distinct elements in the input streams that is then used for estimation.  ... 
doi:10.1145/872788.872790 fatcat:2msjvie3n5fnnbgx5jyo4usxta

Processing set expressions over continuous update streams

Sumit Ganguly, Minos Garofalakis, Rajeev Rastogi
2003 Proceedings of the 2003 ACM SIGMOD international conference on on Management of data - SIGMOD '03  
There is growing interest in algorithms for processing and querying continuous data streams (i.e., data that is seen only once in a fixed order) with limited memory resources.  ...  In this paper, we propose the first space-efficient algorithmic solution for estimating the cardinality of full-fledged set expressions over general update streams.  ...  the distinct elements in the input streams that is then used for estimation.  ... 
doi:10.1145/872757.872790 dblp:conf/sigmod/GangulyGR03 fatcat:x35osvh3xnbgdghzoyojuoxsbm

Histogramming Data Streams with Fast Per-Item Processing [chapter]

Sudipto Guha, Piotr Indyk, S. Muthukrishnan, Martin J. Strauss
2002 Lecture Notes in Computer Science  
Our algorithm is the rst that simultaneously uses small space as well as runs fast, taking O1 worst case time for per-item processing. In addition, our algorithm is quite simple.  ...  Our algorithm is eminently suitable to emerging applications where signal is presented in a stream, size of the signal is very large, and one must construct the histogram using signi cantly smaller space  ...  r k 2 k A , Hk 2 : In 13 , an algorithm for constructing a robust approximation was given.  ... 
doi:10.1007/3-540-45465-9_58 fatcat:33aezxdlafchpbcax6h6obez6m
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