VCDeepFL: Vector Convolutional Deep Feature Learning Approach for Identification of Known and Unknown Denial of Service Attacks. - Narayanavadivoo Gopinathan Bhuvaneswari Amma; Subramanian Selvakumar (TENCON, 2018)

Deep Radial Intelligence with Cumulative Incarnation approach for detecting Denial of Service attacks. - Bhuvaneswari Amma N. G.; S. Selvakumar 001 (Neurocomputing, 2019)

SAGRU: A Stacked Autoencoder-Based Gated Recurrent Unit Approach to Intrusion Detection. - N. G. Bhuvaneswari Amma; S. Selvakumar 001; R. Leela Velusamy (FICTA (2), 2020)

Anomaly detection framework for Internet of things traffic using vector convolutional deep learning approach in fog environment. - Narayanavadivoo Gopinathan Bhuvaneswari Amma; S. Selvakumar 001 (Future Gener. Comput. Syst., 2020)

A Statistical Approach for Detection of Denial of Service Attacks in Computer Networks. - N. G. Bhuvaneswari Amma; S. Selvakumar 001; R. Leela Velusamy (IEEE Trans. Netw. Serv. Manag., 2020)

A statistical class center based triangle area vector method for detection of denial of service attacks. - N. G. Bhuvaneswari Amma; S. Selvakumar 001 (Clust. Comput., 2021)

IoTInDet: Detecting Internet of Things Intrusions with Class Scatter Ratio and Hellinger Distance Statistics. - N. G. Bhuvaneswari Amma; P. Valarmathi (ICISS, 2022)

A vector convolutional deep autonomous learning classifier for detection of cyber attacks. - N. G. Bhuvaneswari Amma (Clust. Comput., 2022)

LPCOCN: A Layered Paddy Crop Optimization-Based Capsule Network Approach for Anomaly Detection at IoT Edge. - Narayanavadivoo Gopinathan Bhuvaneswari Amma; Velliangiri Sarveshwaran; Vinayakumar Ravi; Rajasekhar Chaganti (Inf., 2022)

Optimization of vector convolutional deep neural network using binary real cumulative incarnation for detection of distributed denial of service attacks. - N. G. Bhuvaneswari Amma; S. Selvakumar 001 (Neural Comput. Appl., 2022)

Detection of DoS Attacks in Smart City Networks With Feature Distance Maps: A Statistical Approach. - S. Velliangiri; N. G. Bhuvaneswari Amma; Namkyun Baik (IEEE Internet Things J., 2023)

Towards improving the performance of traffic sign recognition using support vector machine based deep learning model. - N. G. Bhuvaneswari Amma; Vikrant Rajput (Multim. Tools Appl., 2024)

A Novel Split Learning-Based Consumer Electronics Network Traffic Anomaly Detection Framework for Smart City Environment. - Dong-Jo Kim; N. G. Bhuvaneswari Amma; Velliangiri Sarveshwaran (IEEE Trans. Consumer Electron., 2024)

CLNet: a contactless fingerprint spoof detection using deep neural networks with a transfer learning approach. - Kanchana Rajaram; Bhuvaneswari Amma N. G.; Ashwin S. Guptha; S. Selvakumar 001 (Multim. Tools Appl., 2024)

Class Scatter Ratio Based Mahalanobis Distance Approach for Detection of Internet of Things Traffic Anomalies. - Daegeon Kim; S. Velliangiri; Bhuvaneswari Amma N. G.; Dongoun Lee (Mob. Networks Appl., 2024)

Towards improving the security of wireless networks using secured session keys. - N. G. Nageswari Amma; T. Jayaraj; N. G. Bhuvaneswari Amma (Inf. Secur. J. A Glob. Perspect., 2025)