Dr Sutharshan Rajasegarar

STAFF PROFILE

Position

Senior Lecturer in Computer Science

Faculty

Faculty of Sci Eng & Built Env

Department

School of Info Technology

Campus

Melbourne Burwood Campus

Publications

Filter by

2020

VoterChoice: A ransomware detection honeypot with multiple voting framework

Chee Ng, Sutharshan Rajasegarar, Lei Pan, Frank Jiang, Yu Zhang

(2020), pp. 1-29, Concurrency and Computation: Practice and Experience, Hoboken, N.J., C1

journal article

Visual Structural Assessment and Anomaly Detection for High-Velocity Data Streams

Punit Rathore, Dheeraj Kumar, James Bezdek, Sutharshan Rajasegarar, Marimuthu Palaniswami

(2020), pp. 1-14, IEEE Transactions on Cybernetics, Piscataway, N.J., C1

journal article

Complex emotion profiling: An incremental active learning based approach with sparse annotations

Thuseethan Selvarajah, Sutharshan Rajasegarar, John Yearwood

(2020), Vol. 8, pp. 147711-147727, IEEE Access, Piscataway, N.J., C1

journal article

Deep metric learning based citrus disease classification with sparse data

Janarthan Sivasubramaniam, Thuseethan Selvarajah, Sutharshan Rajasegarar, Qiang Lyu, Yongqiang Zheng, John Yearwood

(2020), Vol. 8, pp. 162588-162600, IEEE Access, Piscataway, N.J., C1

journal article

IoT insider attack - survey

M Chowdhury, R Doss, B Ray, S Rajasegarar, S Chowdhury

(2020), Vol. 324, pp. 28-41, SGIoT 2019 : Proceedings of the Third European Alliance for Innovation International Conference on Smart Grid and Internet of Things 2019, TaiChung, Taiwan, E1

conference
2019

A rapid hybrid clustering algorithm for large volumes of high dimensional data

P Rathore, D Kumar, J Bezdek, S Rajasegarar, M Palaniswami

(2019), Vol. 31, pp. 641-654, IEEE transactions on knowledge and data engineering, Piscataway, N.J., C1

journal article

Bus travel time prediction with real-time traffic information

J Ma, J Chan, G Ristanoski, S Rajasegarar, C Leckie

(2019), Vol. 105, pp. 536-549, Transportation research part c: emerging technologies, Amsterdam, The Netherlands, C1

journal article

Investigation of complexity and regulatory role of physiological activities during a pacing exercise

Maia Angelova Turkedjieva, Sergiy Shelyag, Sutharshan Rajasegarar, Dinishen Chuckravanen, Sujan Rajbhandari, Paul Gastin, Alan St Clair Gibson

(2019), Vol. 7, pp. 152334-152346, IEEE Access, Piscataway, N.J., C1

journal article

Detection of smoking events from confounding activities of daily living

J Lu, J Wang, X Zheng, C Karmakar, S Rajasegarar

(2019), pp. 1-9, ACSW 2019 : Proceedings of the Australasian Computer Science Week Multiconference, Sydney, N.S.W., E1

conference

Detecting micro-expression intensity changes from videos based on hybrid deep CNN

S Thuseethan, S Rajasegarar, J Yearwood

(2019), Vol. 11441, pp. 387-399, PAKDD 2019 : Proceedings of the 23rd Pacific-Asia Conference on Knowledge Discoveri and Data Mining, Macau, China, E1

conference

Emotion intensity estimation from video frames using deep hybrid convolutional neural networks

S Thuseethan, S Rajasegarar, J Yearwood

(2019), pp. 1-10, IJCNN 2019 : Proceedings of the 2019 International Joint Conference on Neural Networks, Budapest, Hungary, E1

conference

Deep learning and one-class SVM based anomalous crowd detection

M Yang, S Rajasegarar, S Erfani, C Leckie

(2019), Vol. 2019-July, IJCNN 2019 : International Joint Conference on Neural Networks, Budapest, Hungary, E1

conference

Insider attacks on Zigbee based IoT networks by exploiting AT commands

W Piracha, M Chowdhury, B Ray, S Rajasegarar, R Doss

(2019), Vol. 1116, pp. 77-91, ATIS 2019 : Proceedings of the 10th Applications and Techniques in Information Security Conference 2019, Tamil Nadul, India, E1

conference

Deep hybrid spatiotemporal networks for continuous pain intensity estimation

S Thuseethan, S Rajasegarar, J Yearwood

(2019), Vol. 11955, pp. 449-461, APNNS 2019 : Proceedings of the 26th International Conference on Neural Information Processing of the Asia-Pacific Neural Network Society 2019, Sydney, N.S.W., E1

conference
2018

Real-time urban microclimate analysis using Internet of Things

P Rathore, P Rathore, A Rao, A Rao, S Rajasegarar, S Rajasegarar, E Vanz, E Vanz, J Gubbi, J Gubbi, M Palaniswami, M Palaniswami

(2018), Vol. 5, pp. 500-511, IEEE internet of things journal, Piscataway, N.J., C1

journal article

Ensemble fuzzy clustering using cumulative aggregation on random projections

P Rathore, J Bezdek, S Erfani, S Rajasegarar, M Palaniswami

(2018), Vol. 26, pp. 1510-1524, IEEE transactions on fuzzy systems, Piscataway, N.J., C1

journal article

Efficient unsupervised parameter estimation for one-class support vector machines

Z Ghafoori, S Erfani, S Rajasegarar, J Bezdek, S Karunasekera, C Leckie

(2018), Vol. 29, pp. 5057-5070, IEEE transactions on neural networks and learning systems, Piscataway, N.J., C1

journal article

User activity pattern analysis in telecare data

M Angelova, J Ellman, H Gibson, P Oman, S Rajasegarar, Y Zhu

(2018), Vol. 6, pp. 33306-33317, IEEE access, Piscataway, N.J., C1

journal article

Fast and scalable big data trajectory clustering for understanding urban mobility

D Kumar, H Wu, S Rajasegarar, C Leckie, S Krishnaswamy, M Palaniswami

(2018), Vol. 19, pp. 3709-3722, IEEE transactions on intelligent transportation systems, Piscataway, N.J., C1

journal article

Breast cancer recurrence prediction using random forest model

T Al-Quraishi, J Abawajy, M Chowdhury, S Rajasegarar, A Abdalrada

(2018), Vol. 700, pp. 318-329, SCDM 2018 : Concise and informative : Proceedings of the 3rd International Conference on Soft Computing and Data Mining, Johor, Malaysia, E1

conference

Relationship between Angiotensin Converting Enzyme gene and Cardiac Autonomic Neuropathy among Australian population

A Abdalrada, J Abawajy, M Chowdhury, S Rajasegarar, T Al-Quraishi, H Jelinek

(2018), Vol. 700, pp. 135-146, SCDM 2018 : Proceedings of the 3rd International Conference on Soft Computing and Data Mining 2018, Johor, Malaysia, E1

conference

Distributed detection of zero-day network traffic flows

Y Miao, L Pan, S Rajasegarar, J Zhang, C Leckie, Y Xiang

(2018), Vol. 845, pp. 173-191, AusDM 2017 : Proceedings of the 15th Australasian Data Mining Conference 2017, Melbourne, Vic., E1

conference

Bayesian maximum entropy and interacting multiple model based automatic sensor drift detection and correction in an IoT environment

P Rathore, D Kumar, S Rajasegarar, M Palaniswami

(2018), pp. 598-603, IEEE WF-IoT 2018 : Proceedings of 4th IEEE World Forum on Internet of Things, Singapore, E1

conference

Graph stream mining based anomalous event analysis

M Yang, L Rashidi, S Rajasegarar, C Leckie

(2018), Vol. 11012, pp. 891-903, PRICAI 2018: Proceedings of the Pacific Rim International Conference on Artifical Intelligence: Trends in Artificial Intelligence, Nanjing, China, E1

conference

Approximate cluster heat maps of large high-dimensional data

P Rathore, J Bezdek, D Kumar, S Rajasegarar, M Palaniswami

(2018), pp. 195-200, ICPR 2018 : Proceedings of the 24th International Conference on Pattern Recognition, Beijing, China, E1

conference

Crowd activity change point detection in videos via graph stream mining

M Yang, L Rashidi, S Rajasegarar, C Leckie, A Rao, M Palaniswami

(2018), pp. 328-336, CVPRW 2018 : Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, Salt Lake City, Ut., E1

conference

Scalable bottom-up subspace clustering using FP-trees for high dimensional data

M Doan, J Qi, S Rajasegarar, C Leckie

(2018), pp. 106-111, Big Data : Proceedings of the 2018 IEEE International Conference on Big Data, Seattle, Wash., E1

conference

Cluster-based crowd movement behavior detection

M Yang, L Rashidi, A Rao, S Rajasegarar, M Ganji, M Palaniswami, C Leckie

(2018), pp. 1-8, DICTA 2018 : Proceedings of the 2018 Digital Image Computing: Techniques and Applications, Canberra, A.C.T., E1

conference
2017

A visual-numeric approach to clustering and anomaly detection for trajectory data

D Kumar, J Bezdek, S Rajasegarar, C Leckie, M Palaniswami

(2017), Vol. 33, pp. 265-281, Visual computer, Berlin, Germany, C1-1

journal article

Maximum entropy-based auto drift correction using high- and low-precision sensors

P Rathore, D Kumar, S Rajasegarar, M Palaniswami

(2017), Vol. 13, pp. 1-41, ACM transactions on sensor networks, New York, N.Y., C1

journal article

Fog-empowered anomaly detection in IoT using hyperellipsoidal clustering

L Lyu, J Jin, S Rajasegarar, X He, M Palaniswami

(2017), Vol. 4, pp. 1174-1184, IEEE internet of things, Piscataway, N.J., C1

journal article

Clustering aided support vector machines

G Ristanoski, R Soni, S Rajasegarar, J Bailey, C Leckie

(2017), Vol. 10358, pp. 322-334, MLDM 2017 : Proceedings of the 13th International Machine Learning and Data Mining in Pattern Recognition Conference, New York, USA, E1

conference

Orness and cardinality indices for averaging inclusion-exclusion integrals

A Honda, S James, S Rajasegarar

(2017), Vol. 10571, pp. 51-62, MDAI 2017 : Proceedings of the 14th International Modeling Decisions for Artificial Intelligence Conference, Kitakyushu, Japan, E1

conference

Improving load forecasting based on deep learning and K-shape clustering

F Fahiman, S Erfani, S Rajasegarar, M Palaniswami, C Leckie

(2017), pp. 4134-4141, IJCNN 2017 : Proceedings of the International Joint Conference on Neural Networks 2017, Anchorage, Alaska, E1-1

conference

Non-invasive sensor based automated smoking activity detection

B Bhandari, JianChao Lu, Xi Zheng, S Rajasegarar, C Karmakar

(2017), pp. 845-848, EMBC 2017 : Proceedings of the 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Seogwipo, South Korea, E1

conference
2016

Acoustic and device feature fusion for load recognition

A Zoha, A Gluhak, M Nati, M Imran, S Rajasegarar

(2016), Vol. 586, pp. 287-300, Novel applications of intelligent systems, Berlin, Germany, B1-1

book chapter

High-dimensional and large-scale anomaly detection using a linear one-class SVM with deep learning

S Erfani, S Rajasegarar, S Karunasekera, C Leckie

(2016), Vol. 58, pp. 121-134, Pattern recognition, Amsterdam, The Netherlands, C1-1

journal article

A hybrid approach to clustering in big data

D Kumar, J Bezdek, M Palaniswami, S Rajasegarar, C Leckie, T Havens

(2016), Vol. 46, pp. 2372-2385, IEEE transactions on cybernetics, Piscataway, N.J., C1-1

journal article

Adaptive cluster tendency visualization and anomaly detection for streaming data

D Kumar, J Bezdek, S Rajasegarar, M Palaniswami, C Leckie, J Chan, J Gubbi

(2016), Vol. 11, pp. 1-40, ACM transactions on knowledge discovery from data, New York, N.Y., C1-1

journal article

Pedestrian behaviour analysis using the microsoft kinect

J Chen, S Rajasegarar, C Leckie, A Gygax

(2016), pp. 1-6, PerCom Workshops 2016: Proceedings of the 13th IEEE International Conference on Pervasive Computing and Communication Workshops, Sydney, N.S.W., E1

conference

Unsupervised parameter estimation for one-class support vector machines

Z Ghafoori, S Rajasegarar, S Erfani, S Karunasekera, C Leckie

(2016), Vol. 9652, pp. 183-195, PAKDD 2016 : Advances in Knowledge Discovery and Data Mining : 20th Pacific-Asia Conference, PAKDD 2016 Auckland, New Zealand, April 19-22, 2016 Proceedings, Part II, Auckland, New Zealand, E1

conference

Node re-ordering as a means of anomaly detection in time-evolving graphs

L Rashidi, A Kan, J Bailey, J Chan, C Leckie, W Liu, S Rajasegarar, K Ramamohanarao

(2016), Vol. 9852, pp. 162-178, ECML PKDD 2016 : Machine learning and knowledge discovery in databases : Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, Riva del Garda, Italy, E1

conference

R1STM: one-class support tensor machine with randomised kernel

S Erfani, M Baktashmotlagh, S Rajasegarar, V Nguyen, C Leckie, J Bailey, K Ramamohanarao

(2016), pp. 198-206, SDM 2016 : Proceedings of 2016 SIAM International Conference on Data Mining, Miami, Fla., E1

conference

Anomalous behavior detection in crowded scenes using clustering and spatio-temporal features

M Yang, S Rajasegarar, A Rao, C Leckie, M Palaniswami

(2016), Vol. 486, pp. 132-141, IFIP 2016 : Proceedings of the 9th Intelligent Information Processing International Conference, Melbourne, Victoria, E1

conference

Anomaly detection in non-stationary data: ensemble based self-adaptive OCSVM

Z Ghafoori, S Erfani, S Rajasegarar, S Karunasekera, C Leckie

(2016), pp. 2476-2483, IJCNN 2016: Proceedings of the IEEE International Joint Conference on Neural Networks, Vancouver, Canada, E1

conference
2015

Geospatial estimation-based auto drift correction in wireless sensor networks

D Kumar, S Rajasegarar, M Palaniswami

(2015), Vol. 11, pp. 1-39, ACM transactions on sensor networks, New York, N. Y., C1-1

journal article

An embedding scheme for detecting anomalous block structured graphs

L Rashidi, S Rajasegarar, C Leckie

(2015), Vol. 9078, pp. 215-227, Advances in Knowledge Discovery and Data Mining: 19th Pacific-Asia Conference, PAKDD 2015. Proceedings, Part II, Ho Chi Minh City, Vietnam, E1-1

conference

Pattern based anomalous user detection in cognitive radio networks

S Rajasegarar, C Leckie, M Palaniswami

(2015), pp. 5605-5609, ICASSP 2015 : Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing, Brisbane, Qld., E1-1

conference

DP1SVM: a dynamic planar one-class support vector machine for Internet of Things environment

A Shilton, S Rajasegarar, C Leckie, M Palaniswami

(2015), pp. 1-6, RIoT 2015 : Proceedings of the 2015 International Conference on Recent Advances in Internet of Things, Singapore, Singapore, E1-1

conference

Parking availability prediction for sensor-enabled car parks in smart cities

Y Zheng, S Rajasegarar, C Leckie

(2015), pp. 1-6, ISSNIP 2015 : Proceedings of the 2015 IEEE Tenth International Conference on Intelligent Sensors, Sensor Networks and Information Processing, Singapore, E1-1

conference

Profiling pedestrian distribution and anomaly detection in a dynamic environment

M Doan, S Rajasegarar, M Salehi, M Moshtaghi, C Leckie

(2015), Vol. 19-23-Oct-2015, pp. 1827-1830, CIKM 2015: Proceedings of the Information and Knowledge Management 2015 International Conference, Melbourne, Vic., E1-1

conference

R1SVM: a randomised nonlinear approach to large-scale anomaly detection

S Erfani, M Baktashmotlagh, S Rajasegarar, S Karunasekera, C Leckie

(2015), Vol. 1, pp. 432-438, AAAI 2015: Proceedings of the Artificial Intelligence 2015 Conference, Austin, Texas, E1-1

conference

DPISVM: a dynamic planar one-class support vector machine for internet of things environment

A Shilton, S Rajasegarar, C Leckie, M Palaniswami

(2015), pp. 1-6, RIoT 2015 : Proceedingins of the International Conference on Recent Advances in Internet of Things, Singapore, E1-1

conference
2014

Streaming analysis in wireless sensor networks

M Moshtaghi, J Bezdek, T Havens, C Leckie, S Karunasekera, S Rajasegarar, M Palaniswami

(2014), Vol. 14, pp. 905-921, Wireless communications and mobile computing, Chichester, Eng., C1-1

journal article

An adaptive elliptical anomaly detection model for wireless sensor networks

M Moshtaghi, C Leckie, S Karunasekera, S Rajasegarar

(2014), Vol. 64, pp. 195-207, Computer networks, Amsterdam, The Netherlands, C1-1

journal article

Ellipsoidal neighbourhood outlier factor for distributed anomaly detection in resource constrained networks

S Rajasegarar, A Gluhak, M Ali Imran, M Nati, M Moshtaghi, C Leckie, M Palaniswami

(2014), Vol. 47, pp. 2867-2879, Pattern recognition, Chatswood, N.S.W., C1-1

journal article

Anomaly detection in wireless sensor networks in a non-stationary environment

C Oreilly, A Gluhak, M Imran, S Rajasegarar

(2014), Vol. 16, pp. 1413-1432, IEEE communications surveys and tutorials, Piscataway, N.J., C1-1

journal article

Hyperspherical cluster based distributed anomaly detection in wireless sensor networks

S Rajasegarar, C Leckie, M Palaniswami

(2014), Vol. 74, pp. 1833-1847, Journal of parallel and distributed computing, Amsterdam, The Netherlands, C1-1

journal article

High-resolution monitoring of atmospheric pollutants using a system of low-cost sensors

S Rajasegarar, T Havens, S Karunasekera, C Leckie, J Bezdek, M Jamriska, A Gunatilaka, A Skvortsov, M Palaniswami

(2014), Vol. 52, pp. 3823-3832, IEEE transactions on geoscience and remote sensing, Piscataway, N. J., C1-1

journal article

Profiling spatial and temporal behaviour in sensor networks: a case study in energy monitoring

L Rashidi, S Rajasegarar, C Leckie, M Nati, A Gluhak, M Imran, M Palaniswami

(2014), pp. 1-7, IEEE ISSNIP 2014 : Proceedings of the 2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing, Singapore, Singapore, E1-1

conference

Smart car parking: temporal clustering and anomaly detection in urban car parking

Y Zheng, S Rajasegarar, C Leckie, M Palaniswami

(2014), pp. 1-6, IEEE ISSNIP 2014 : Proceedings of the 2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing, Singapore, Singapore, E1-1

conference

High resolution spatio-temporal monitoring of air pollutants using wireless sensor networks

S Rajasegarar, P Zhang, Y Zhou, S Karunasekera, C Leckie, M Palaniswami

(2014), pp. 1-6, IEEE ISSNIP 2014 : Proceedings of the 2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing, Singapore, Singapore, E1-1

conference

Detection of anomalous crowd behaviour using hyperspherical clustering

A Rao, J Gubbi, S Rajasegarar, S Marusic, M Palaniswami

(2014), pp. 1-8, DICTA 2014 : Proceedings of the Digital Image Computing : Techniques and Applications International Conference, Wollongong, New South Wales, E1-1

conference

Spatio-temporal estimation with Bayesian maximum entropy and compressive sensing in communication constrained networks

S Rajasegarar, C Leckie, M Palaniswami

(2014), pp. 4536-4541, IEEE ICC 2014 : Communications: the centrepoint of the digital economy : Proceedings of the 2014 IEEE International Conference on Communications, Sydney, N.S.W., E1-1

conference
2013

Combined multiclass classification and anomaly detection for large-scale wireless sensor networks

A Shilton, S Rajasegarar, M Palaniswami

(2013), pp. 491-496, IEEE ISSNIP 2013 : Proceedings of the 2013 IEEE Eighth International Conference on Intelligent Sensors, Sensor Networks and Information Processing, Melbourne, Vic., E1-1

conference

Automatic sensor drift detection and correction using spatial kriging and kalman filtering

D Kumar, S Rajasegarar, M Palaniswami

(2013), pp. 183-190, DCoSS 2013 : Proceedings of the 2013 IEEE International Conference on Distributed Computing in Sensor Systems, Cambridge, Mass., E1-1

conference

ClusiVAT: a mixed visual/numerical clustering algorithm for big data

D Kumar, M Palaniswami, S Rajasegarar, C Leckie, J Bezdek, T Havens

(2013), pp. 112-117, Big Data 2013 : Proceedings of the 2013 IEEE International Conference on Big Data, Silicon Valley, Calif., E1-1

conference

Optimization of an energy harvesting buoy for coral reef monitoring

A Pirisi, F Grimaccia, M Mussetta, R Zich, R Johnstone, M Palaniswami, S Rajasegarar

(2013), pp. 629-634, CEC 2013 : Proceedings of the 2013 IEEE Congress on Evolutionary Computation, Cancun, Mexico, E1-1

conference
2012

Non-intrusive load monitoring approaches for disaggregated energy sensing: a survey.

A Zoha, A Gluhak, M Imran, S Rajasegarar

(2012), Vol. 12, pp. 16838-16866, Sensors, Basel, Switzerland, C1-1

journal article

Measures for clustering and anomaly detection in sets of higher dimensional ellipsoids

S Rajasegarar, J Bezdek, M Moshtaghi, C Leckie, T Havens, M Palaniswami

(2012), pp. 1-8, WCCI 2012 : Proceedings of the IEEE World Congress on Computational Intelligence, Brisbane, Queensland, E1-1

conference

Acoustic and device feature fusion for load recognition

A Zoha, A Gluhak, M Nati, M Imran, S Rajasegarar

(2012), pp. 386-392, IS 2012 : Intelligent systems: methodology, systems, applications in emerging technologies : Proceedings of the 2012 6th IEEE International Conference Intelligent Systems, Sofia, Bulgaria, E1-1

conference

Online anomaly rate parameter tracking for anomaly detection in wireless sensor networks

C O'Reilly, A Gluhak, M Imran, S Rajasegarar

(2012), Vol. 1, pp. 191-199, SECON 2012 : Proceedings of the 2012 9th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks, Seoul, South Korea, E1-1

conference
2011

Anomaly detection in environmental monitoring networks

J Bezdek, S Rajasegarar, M Moshtaghi, C Leckie, M Palaniswami, T Havens

(2011), Vol. 6, pp. 52-58, IEEE Computational Intelligence Magazine, Piscataway, N.J., C1-1

journal article

Clustering ellipses for anomaly detection

M Moshtaghi, T Havens, J Bezdek, L Park, C Leckie, S Rajasegarar, J Keller, M Palaniswami

(2011), Vol. 44, pp. 55-69, Pattern Recognition, Amsterdam, The Netherlands, C1-1

journal article

An efficient hyperellipsoidal clustering algorithm for resource-constrained environments

M Moshtaghi, S Rajasegarar, C Leckie, S Karunasekera

(2011), Vol. 44, pp. 2197-2209, Pattern recognition, Amsterdam, The Netherlands, C1-1

journal article

Spatio-temporal modelling-based drift-aware wireless sensor networks

M Takruri, S Rajasegarar, S Challa, C Leckie, M Palaniswami

(2011), Vol. 1, pp. 110-122, IET Wireless Sensor Systems, Stevenage, Eng., C1-1

journal article

Incremental elliptical boundary estimation for anomaly detection in wireless sensor networks

M Moshtaghi, C Leckie, S Karunasekera, J Bezdek, S Rajasegarar, M Palaniswami

(2011), pp. 467-476, ICDM 2011 : Proceedings of the 2011 IEEE 11th International Conference on Data Mining, Vancouver, Canada, E1-1

conference

An efficient approach to detecting concept-evolution in network data streams

S Erfani, S Rajasegarar, C Leckie

(2011), pp. 1-7, ATNAC 2011 : Proceedings of the 2011 Australasian Telecommunication Networks and Applications Conference, Melbourne, Vic., E1-1

conference
2010

Centered hyperspherical and hyperellipsoidal one-class support vector machines for anomaly detection in sensor networks

S Rajasegarar, C Leckie, J Bezdek, M Palaniswami

(2010), Vol. 5, pp. 518-533, IEEE transactions on information forensics and security, Piscataway, N.J., C1-1

journal article
2009

Elliptical anomalies in wireless sensor networks

S Rajasegarar, J Bezdek, C Leckie, M Palaniswami

(2009), Vol. 6, pp. 7:1-7:28, ACM transactions on sensor networks, New York, N.Y., C1-1

journal article
2008

Anomaly detection in wireless sensor networks

S Rajasegarar, C Leckie, M Palaniswami

(2008), Vol. 15, pp. 34-40, IEEE Wireless Communications, Piscataway, N.J., C1-1

journal article

Funded Projects at Deakin

Australian Competitive Grants

Learning the Focus of Attention to Detect Distributed Coordinated Attacks

Prof Christopher Leckie, Prof Ramamohanarao Kotagiri, Dr Sarah Erfani, Dr Sutharshan Rajasegarar, Prof Vipin Kumar

ARC - Discovery Projects

  • 2020: $13,500

Supervisions

Associate Supervisor
2019

Chee Keong (Allan) Ng

Thesis entitled: VoterChoice: A Ransomware Detection Honeypot with Multiple Voting Concept

Doctor of Philosophy (Information Technology), School of Information Technology