A Survey of Modern Deep Learning based Object Detection Models (2022)
Journal Article
Zaidi, S., Ansari, M., Aslam, A., Kanwal, N., Asghar, M., & Lee, B. (2022). A Survey of Modern Deep Learning based Object Detection Models. Digital Signal Processing, 1-19. https://doi.org/10.1016/j.dsp.2022.103514

Object Detection is the task of classification and
localization of objects in an image or video. It has gained
prominence in recent years due to its widespread applications.
This article surveys recent developments in deep learning based
object d... Read More about A Survey of Modern Deep Learning based Object Detection Models.

SLEPX: An Efficient Lightweight Cipher for Visual Protection of Scalable HEVC Extension (2020)
Journal Article
Asghar, M., Abdullah, S., Kanwal, N., Fleury, M., & Shah, R. (2020). SLEPX: An Efficient Lightweight Cipher for Visual Protection of Scalable HEVC Extension. IEEE Access, 187784 - 187807. https://doi.org/10.1109/ACCESS.2020.3030608

This paper proposes a lightweight cipher scheme aimed at the scalable extension of the High Efficiency Video Coding (HEVC) codec, referred to as the Scalable HEVC (SHVC) standard. This stream cipher, Symmetric Cipher for Lightweight Encryption based... Read More about SLEPX: An Efficient Lightweight Cipher for Visual Protection of Scalable HEVC Extension.

MuLViS: Multi-Level Encryption Based Security System for Surveillance Videos (2020)
Journal Article
Qiao, Y., Ansari, M., Lee, B., Shifa, A., Asghar, M., Fleury, M., …Herbst, M. (2020). MuLViS: Multi-Level Encryption Based Security System for Surveillance Videos. IEEE Access, 177131 - 177155. https://doi.org/10.1109/ACCESS.2020.3024926

Video Surveillance (VS) systems are commonly deployed for real-time abnormal event detection and autonomous video analytics. Video captured by surveillance cameras in real-time often contains identifiable personal information, which must be privacy p... Read More about MuLViS: Multi-Level Encryption Based Security System for Surveillance Videos.

Preserving Chain-of-Evidence in Surveillance Videos for Authentication and Trust-Enabled Sharing (2020)
Journal Article
Kanwal, N., Asghar, M., Ansari, M., Fleury, M., Lee, B., Herbst, M., & Qiao, Y. (2020). Preserving Chain-of-Evidence in Surveillance Videos for Authentication and Trust-Enabled Sharing. IEEE Access, 153413 - 153424. https://doi.org/10.1109/access.2020.3016211

Surveillance video recording is a powerful method of deterring unlawful activities. A robust data protection-by-design solution can be helpful in terms of making a captured video immutable, as such recordings cannot become a piece of evidence until p... Read More about Preserving Chain-of-Evidence in Surveillance Videos for Authentication and Trust-Enabled Sharing.