Browsing Technological University of the Shannon: Midlands Midwest by Author "Shifa, Amna"
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Fuzzy‑logic threat classification for multi‑level selective encryption over real‑time video streams.
Shifa, Amna; Asghar, Mamoona Naveed; Ahmed, Adeel; Martin, Fleury (Springer, 2020-04-22)This paper proposes a Fuzzy-logic Threat Classification (FTC) model as the basis of a method to auto-detect three different confidentiality levels for videos streamed from heterogeneous, mobile devices via web edge servers, ... -
Joint crypto-stego scheme for enhanced image protection with nearest-centroid clustering.
Shifa, Amna; Afgan, Muhammad Sher; Asghar, Mamoona Naveed; Fleury, Martin; Memon, Imran; Abdullah, Saima; Rasheed, Nadia (IEEE, 2018-03-12)Owing to the exceptional growth of information exchange over open communication channels within the public Internet, confidential transmission of information has become a vital current concern for organizations and ... -
Lightweight cipher for H.264 videos in the Internet of Multimedia Things with encryption space ratio diagnostics
Shifa, Amna; Asghar, Mamoona Naveed; Noor, Salma; Gohar, Neelam (MDPI, 2019-03-11)Within an Internet of Multimedia Things, the risk of disclosing streamed video content, such as that arising from video surveillance, is of heightened concern. This leads to the encryption of that content. To reduce the ... -
MuLViS: multi-level encryption based security system for surveillance videos
Shifa, Amna; Asghar, Mamoona Naveed; Fleury, Martin; Kanwal, Nadia; Ansari, Mohammad Samar; Lee, Brian; Herbst, Marco; Qiao, Yuansong (IEEE, 2020-09-18)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, ... -
Skin detection and lightweight encryption for privacy protection in real-time surveillance applications
Shifa, Amna; Imtiaz, Muhammad Babar; Ashgar, Mamoona Naveed; Fleury, Martin (Elsevier, 2020-02)An individual’s privacy protection is the concerning issue in surveillance videos. Existing research work for individual’s identification on the bases of their skin detection is focused either on different human skin ...