Empirical analysis of attack graphs for mitigating critical paths and vulnerabilities. - Urvashi Garg; Geeta Sikka; Lalit Kumar Awasthi (Comput. Secur., 2018)

An ensemble approach for optimization of penetration layout in wide area networks. - Urvashi Garg; Geeta Sikka; Lalit Kumar Awasthi (Comput. Commun., 2021)

Empirical risk assessment of attack graphs using time to compromise framework. - Urvashi Garg; Geeta Sikka; Lalit Kumar Awasthi (Int. J. Inf. Comput. Secur., 2021)

Modified silhouette based segmentation outperforming in the presence of intensity inhomogeneity in the hyperspectral images. - Kriti Mahajan; Urvashi Garg (Int. J. Intell. Eng. Informatics, 2021)

CPIDM: A Clustering-Based Profound Iterating Deep Learning Model for HSI Segmentation. - Kriti Mahajan; Urvashi Garg; Mohammad Shabaz (Wirel. Commun. Mob. Comput., 2021)

Moving Target Depth Information Extraction Based on Nonlinear Strategy Network. - Wei Liu; Mohammad Shabaz; Urvashi Garg (J. Interconnect. Networks, 2022)

An enhancement to the existing cyclostationary feature detection in CRN. - Kriti Mahajan; Urvashi Garg (Multim. Tools Appl., 2022)

Detection of cross-site scripting (XSS) attacks using machine learning techniques: a review. - Jasleen Kaur; Urvashi Garg; Gourav Bathla (Artif. Intell. Rev., 2023)

An adaptive randomized and secured approach against adversarial attacks. - Lovi Dhamija; Urvashi Garg (Inf. Secur. J. A Glob. Perspect., 2023)

The Role of Feature Based Classification Models in Early Detection of Brain Stroke. - Monika; Urvashi Garg; Kanika (ICCCNT, 2024)

Unveiling vulnerabilities: evading YOLOv5 object detection through adversarial perturbations and steganography. - Gauri Sharma; Urvashi Garg (Multim. Tools Appl., 2024)