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Mr

Sandamal Weerasinghe

Research Fellow In Adversarial Machine Learning
adversarial machine learning
anomaly detection
adversarial learning
computer science
science & technology
engineering
engineering, electrical & electronic
technology
integrity attack
Sandamal Weerasinghe's Profile Picture
Mr

Sandamal Weerasinghe

 
Division
Engineering
 
Primary Interest
Knowledge Representation and Machine Learning
Sandamal Weerasinghe's Profile Picture
Mr

Sandamal Weerasinghe

 

Sandamal is a researcher in the adversarial machine learning group at the School of Computing and Information Systems, University of Melbourne. His research interests include adversarial machine learning, anomaly detection, and game theory.

Scholarly Works

Displaying the 5 most recent scholarly works by Sandamal Weerasinghe.

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Support vector machines resilient against training data integrity attacks

S Weerasinghe, SM Erfani, T Alpcan, C Leckie

Journal article  |  2019  |  Pattern Recognition

Support Vector Machines (SVMs) are vulnerable to integrity attacks, where malicious attackers distort the training data in order t..

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Detection of Anomalous Communications with SDRs and Unsupervised Adversarial Learning

S Weerasinghe, SM Erfani, T Alpcan, C Leckie, J Riddle

Conference Proceedings  |  2019  |  2018 IEEE 43rd Conference on Local Computer Networks (LCN)

© 2018 IEEE. Software-defined radios (SDRs) with substantial cognitive (computing) and networking capabilities provide an opportun..

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Unsupervised Adversarial Anomaly Detection using One-Class Support Vector Machines

T Alpcan, Prameesha Weerasinghe, Margreta Kuijper, Sarah Monazam Erfani, Christopher Leckie

Conference Proceedings  |  2018

Anomaly detection discovers regular patterns in unlabeled data and identifies the non-conforming data points, which in some cases ..

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Deep learning based game-theoretical approach to evade jamming attacks

S Weerasinghe, T Alpcan, SM Erfani, C Leckie, P Pourbeik, J Riddle

Conference Proceedings  |  2018  |  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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Machine learning for understanding the contextual semantics of tabular web sources

J Weerasinghe, S Weerasinghe, A Panditha, V Weerasinghe

Conference Proceedings  |  2013  |  2013 IEEE 8th International Conference on Industrial and Information Systems

5

Scholarly Works

Keyword Analysis

Expanding Knowledge
Artificial Intelligence and Image Processing
Electrical and Electronic Engineering
Applied Mathematics
Cognitive Sciences
Communication Networks and Services
Computer Software and Services

Credentials

Positions

Casual

Electrical And Electronic Engineering

Research Fellow In Adversarial Machine Learning

Computing And Information Systems

Casual

Electrical And Electronic Engineering

Casual

Electrical And Electronic Engineering

Education

Bachelor of Science

University of Melbourne

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