Robustness Security of Data Hiding for H.265/HEVC Video Streams
Grace C.-W. Ting1, Bok-Min Goi2, Sze-Wei Lee3

1Grace C.-W. Ting, Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman, Malaysia.
2Bok-Min Goi, Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman, Malaysia.
3Sze-Wei Lee, Tunku Abdul Rahman University College, Malaysia. Research Was Funded Ministry of Education Fundamental Research Grant Scheme (FRGS) Project .
Manuscript received on 26 September 2019 | Revised Manuscript received on 05 October 2019 | Manuscript Published on 22 October 2019 | PP: 146-151 | Volume-8 Issue-3S October 2019 | Retrieval Number: C10261083S19/2019©BEIESP | DOI: 10.35940/ijrte.C1026.1083S19
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: In the current age of IoT and Industry 4.0, vast amounts of big data are exchanged in the cloud, social media and among sensing devices, at times causing videos to go viral and proliferating fake news. Ultra high quality videos such as in the latest H.265/HEVC standard format have the capacity for data to be embedded in them for different security applications. Security for high quality videos is a concern in our current technological age where netizens often share videos with others through social media and video hosting sites like YouTube. In this paper, we focus on data hiding for H.265/ HEVC and perform detailed security analysis of a recent H. 265/HEVC data hiding scheme. Our security consideration includes the hiding properties of secrecy and undetectability, as well as the robustness security property of tamper resistance. We show specifically an attack against the robustness security of this data hiding scheme. We discuss reasons causing the insecurity against robustness and justify strategies to improve the scheme’s protection against these types of attacks.
Keywords: IoT, Cloud Computing, H.265/ HEVC, Video Sharing.
Scope of the Article: Data Mining