Efficient in-network adaptation of encrypted H.264/SVC content

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This paper addresses the efficient adaptation of encrypted scalable video content (H.264/SVC). RTP-based in-network adaptation schemes on a media aware network element (MANE) in an IPTV and VoD scenario are considered.Two basic alternatives to implement encryption and adaptation of H.264/SVC content are investigated: (i) full, format-independent encryption making use of Secure RTP (SRTP); (ii) SVC-specific encryption that leaves the metadata relevant for adaptation (NAL unit headers) unencrypted.The SRTP-based scheme (i) is straightforward to deploy, but requires the MANE to be in the security context of the delivery, i.e., to be a trusted node. For adaptation, the content needs to be decrypted, scaled, and re-encrypted. The SVC-specific approach (ii) enables both full and selective encryption, e.g., of the base layer only. SVC-specific encryption is based on own previous work, which is substantially extended and detailed in this paper. The adaptation MANE can now be an untrusted node; adaptation becomes a low-complexity process, avoiding full decryption and re-encryption of the content.This paper presents the first experimental comparison of these two approaches and evaluates whether multimedia-specific encryption can lead to performance and application benefits. Potential security threats and security properties of the two approaches in the IPTV and VoD scenario are elementarily analyzed. In terms of runtime performance on the MANE our SVC-specific encryption scheme significantly outperforms the SRTP-based approach. SVC-specific encryption is also superior in terms of induced end-to-end delays. The performance can even be improved by selective application of the SVC-specific encryption scheme. The results indicate that the efficient adaptation of SVC-encrypted content on low-end, untrusted network devices is feasible.

论文关键词:Scalable video coding (H.264/SVC),In-network adaptation,RTP/RTSP MANE,Video encryption,Format compliance

论文评审过程:Received 15 November 2008, Accepted 10 July 2009, Available online 18 July 2009.

论文官网地址:https://doi.org/10.1016/j.image.2009.07.002