Anomalous Edge Detection in Edge Exchangeable Social Network Models

Rui Luo; Buddhika Nettasinghe; Vikram Krishnamurthy

Anomalous Edge Detection in Edge Exchangeable Social Network Models

Rui Luo, Buddhika Nettasinghe, Vikram Krishnamurthy

Department of Systems Engineering

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

16 Citations (Scopus)

Abstract

This paper studies detecting anomalous edges in directed graphs that model social networks. We exploit edge exchangeability as a criterion for distinguishing anomalous edges from normal edges. Then we present an anomaly detector based on conformal prediction theory; this detector has a guaranteed upper bound for false positive rate. In numerical experiments, we show that the proposed algorithm achieves superior performance to baseline methods. © 2023 R. Luo, B. Nettasinghe & V. Krishnamurthy.

Original language	English
Title of host publication	Proceedings of the Twelfth Symposium on Conformal and Probabilistic Prediction with Applications
Editors	Harris Papadopoulos, Khuong An Nguyen, Henrik Boström, Lars Carlsson
Publisher	ML Research Press
Pages	287-310
Publication status	Published - Sept 2023
Event	12th Symposium on Conformal and Probabilistic Prediction with Applications (COPA 2023) - Limassol, Cyprus Duration: 13 Sept 2023 → 15 Sept 2023

Publication series

Name	Proceedings of Machine Learning Research
ISSN (Print)	2640-3498

Conference

Conference	12th Symposium on Conformal and Probabilistic Prediction with Applications (COPA 2023)
Place	Cyprus
City	Limassol
Period	13/09/23 → 15/09/23

Bibliographical note

Full text of this publication does not contain sufficient affiliation information. With consent from the author(s) concerned, the Research Unit(s) information for this record is based on the existing academic department affiliation of the author(s).

Research Keywords

Anomaly Detection
Conformal Prediction
Edge Exchangeable Model
Social Networks

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Luo, R., Nettasinghe, B., & Krishnamurthy, V. (2023). Anomalous Edge Detection in Edge Exchangeable Social Network Models. In H. Papadopoulos, K. A. Nguyen, H. Boström, & L. Carlsson (Eds.), Proceedings of the Twelfth Symposium on Conformal and Probabilistic Prediction with Applications (pp. 287-310). (Proceedings of Machine Learning Research). ML Research Press. https://proceedings.mlr.press/v204/luo23a.html

Luo, Rui ; Nettasinghe, Buddhika ; Krishnamurthy, Vikram. / Anomalous Edge Detection in Edge Exchangeable Social Network Models. Proceedings of the Twelfth Symposium on Conformal and Probabilistic Prediction with Applications. editor / Harris Papadopoulos ; Khuong An Nguyen ; Henrik Boström ; Lars Carlsson. ML Research Press, 2023. pp. 287-310 (Proceedings of Machine Learning Research).

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Luo, R, Nettasinghe, B & Krishnamurthy, V 2023, Anomalous Edge Detection in Edge Exchangeable Social Network Models. in H Papadopoulos, KA Nguyen, H Boström & L Carlsson (eds), Proceedings of the Twelfth Symposium on Conformal and Probabilistic Prediction with Applications. Proceedings of Machine Learning Research, ML Research Press, pp. 287-310, 12th Symposium on Conformal and Probabilistic Prediction with Applications (COPA 2023), Limassol, Cyprus, 13/09/23. <https://proceedings.mlr.press/v204/luo23a.html>

Anomalous Edge Detection in Edge Exchangeable Social Network Models. / Luo, Rui; Nettasinghe, Buddhika; Krishnamurthy, Vikram.
Proceedings of the Twelfth Symposium on Conformal and Probabilistic Prediction with Applications. ed. / Harris Papadopoulos; Khuong An Nguyen; Henrik Boström; Lars Carlsson. ML Research Press, 2023. p. 287-310 (Proceedings of Machine Learning Research).

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

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T1 - Anomalous Edge Detection in Edge Exchangeable Social Network Models

AU - Luo, Rui

AU - Nettasinghe, Buddhika

AU - Krishnamurthy, Vikram

N1 - Full text of this publication does not contain sufficient affiliation information. With consent from the author(s) concerned, the Research Unit(s) information for this record is based on the existing academic department affiliation of the author(s).

PY - 2023/9

Y1 - 2023/9

N2 - This paper studies detecting anomalous edges in directed graphs that model social networks. We exploit edge exchangeability as a criterion for distinguishing anomalous edges from normal edges. Then we present an anomaly detector based on conformal prediction theory; this detector has a guaranteed upper bound for false positive rate. In numerical experiments, we show that the proposed algorithm achieves superior performance to baseline methods. © 2023 R. Luo, B. Nettasinghe & V. Krishnamurthy.

AB - This paper studies detecting anomalous edges in directed graphs that model social networks. We exploit edge exchangeability as a criterion for distinguishing anomalous edges from normal edges. Then we present an anomaly detector based on conformal prediction theory; this detector has a guaranteed upper bound for false positive rate. In numerical experiments, we show that the proposed algorithm achieves superior performance to baseline methods. © 2023 R. Luo, B. Nettasinghe & V. Krishnamurthy.

KW - Anomaly Detection

KW - Conformal Prediction

KW - Edge Exchangeable Model

KW - Social Networks

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M3 - RGC 32 - Refereed conference paper (with host publication)

T3 - Proceedings of Machine Learning Research

SP - 287

EP - 310

BT - Proceedings of the Twelfth Symposium on Conformal and Probabilistic Prediction with Applications

A2 - Papadopoulos, Harris

A2 - Nguyen, Khuong An

A2 - Boström, Henrik

A2 - Carlsson, Lars

PB - ML Research Press

T2 - 12th Symposium on Conformal and Probabilistic Prediction with Applications (COPA 2023)

Y2 - 13 September 2023 through 15 September 2023

ER -

Anomalous Edge Detection in Edge Exchangeable Social Network Models

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