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A new encryption scheme for surveillance videos

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Abstract

In this paper, we propose a novel framework to encrypt surveillance videos. Although a few encryption schemes have been proposed in the literature, they are not sufficiently efficient due to the lack of full consideration of the characteristics of surveillance videos, i.e., intensive global redundancy. By taking advantage of such redundancy, we design a novel method for encrypting such videos. We first train a background dictionary based on several frame observations. Then every single frame is parsed into the background and foreground components. Separation is the key to improve the efficiency of the proposed technique, since encryption is only carried out in the foreground, while the background is skillfully recorded by corresponding background recovery coefficients. Experimental results demonstrate that, compared to the state of the art, the proposed method is robust to known cryptanalytic attacks, and enhances the overall security due to the foreground and background separation. Additionally, our encryption method is faster than competing methods, which do not conduct foreground extraction.

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Author information

Authors and Affiliations

  1. School of Computer Science and Technology, Tianjin University, Tianjin, 300072, China

    Xiaochun Cao, Meili Ma & Ling Du

  2. SKL Of Information Security, Institute of Information Engineering, Chinese Academy of Sciences, Beijing, 100093, China

    Xiaochun Cao, Xiaojie Guo & Dongdai Lin

Authors
  1. Xiaochun Cao
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  2. Meili Ma
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  3. Xiaojie Guo
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  4. Ling Du
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  5. Dongdai Lin
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Corresponding author

Correspondence to Xiaochun Cao.

Additional information

Xiaochun Cao received his BS and MS in computer science from Beihang University, China, in 1999 and 2002, and his PhD in computer science from the University of Central Florida, USA in 2006. He spent around three years at ObjectVideo Inc., Reston, VA, USA, as a research scientist. He is now a professor with the Institute of Information Engineering, Chinese Academy of Sciences. From 2008 to 2012, he was a professor with Tianjin University, China. He has authored and co-authored over 80 journals and conference papers. He was the recipient of the Piero Zamperoni Best Student Paper Award at the International Conference on Pattern Recognition, in 2004 and 2010, respectively, and his PhD dissertation was nominated for the University Level Outstanding Dissertation Award.

Meili Ma is an MS candidate in the School of Computer Science and Technology in Tianjin University, China. She received her BS in computer science and Technology from Hebei University, China in 2012. Her main research interests are multimedia information security and computer vision.

Xiaojie Guo received his BS in software engineering from the School of Computer Science and Technology, Wuhan University of Technology, China, in 2008. He received his MS and PhD in computer science from the School of Computer Science and Technology, Tianjin University, China in 2010 and 2013, respectively. He is currently with the Institute of Information Engineering, Chinese Academy of Sciences as an assistant professor. He was the recipient of the Piero Zamperoni Best Student Paper Award at the International Conference on Pattern Recognition, 2010.

Ling Du is a PhD candidate in the School of Computer Science and Technology in Tianjin University, China. She received her MS and BS both in computer science, from Liaoning University, China. She was a lecturer at Shenyang Aerospace University from 2007 to 2011. Her research interests include multimedia information security and computer vision.

Dongdai Lin received his MS and PhD in fundamental mathematics from the Institute of Systems Science, Chinese Academy of Sciences, China, in 1987 and 1990, respectively. He is currently the director of the National Engineering Research Center for Information Security and deputy director of the State Key Laboratory of Information Security, Institute of Information Engineering of the Chinese Academy of Sciences. He has published more than 150 research papers in journals and conference proceedings. His current research interests include cryptology, security protocols, symbolic computation, software development, multivariate public key cryptography, sequences and stream ciphers, zero knowledge proof, and network-based cryptographic computation.

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Cite this article

Cao, X., Ma, M., Guo, X. et al. A new encryption scheme for surveillance videos. Front. Comput. Sci. 9, 765–777 (2015). https://doi.org/10.1007/s11704-015-3362-4

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  • DOI: https://doi.org/10.1007/s11704-015-3362-4

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