# Cryptography in Wireless Multimedia Sensor Networks: A Survey and Research Directions
## 3 Multimedia Data Encryption
### Video Cryptography  
Some sensing applications directly benefit from the use of cameras to retrieve video streams, potentially providing an enhanced understanding of the monitored target or scene. However, the nature of the video media imposes more stringent requirements for processing, memory, energy consumption, transmission delay and jitter, also demanding more bandwidth than image transmissions. Besides, we may expect that there is an inherent trade-off between using minimum power and achieving high video quality, which may guide the design of secure video-based wireless sensor networks.  
In general, video quality will depend on the resolution, the frame rate, the color pattern and the similarity between the reconstructed and original (source) video. Additionally, these variables add complexity to cryptography, since the costs for video compression and transmission are already high. Thus, an encryption algorithm for video streaming should possess at least two characteristics [56]. First, the encryption time should be low to avoid transmission delays, and second, the compression rate of the video should not decrease. However, in many cases, low energy consumption will be also a major concern [5; 8].  
In order to optimize the cryptography of video streams in wireless sensor networks, selective encryption approaches may also be employed. For predictive video codecs, compression is achieved exploiting information in the video frames: the redundancy within one frame is typically reduced exploiting spatial correlation, while inter-frame coding reduces the redundancy in subsequent frames exploiting both spatial and temporal correlation [56]. As a result, frames with different relevancies for reconstruction are created, and the most relevant ones may be encrypted for security reasons.  
An example of selective video encryption is presented in Figure 2. In that example, for a segment encoded using H.264/AVC codec, I-frames receive strong cryptography (e.g., with more robust algorithms or larger keys); P-frames are weakly encrypted (e.g., employing small keys); and B-frames are not encrypted at all.  
Other video coding approaches may also be exploited for optimized cryptography. The Distributed Video Coding (DVC) employs less complex encoders, leaving most of the complexity to the decoders [57]. In other words, most of the computational and energy costs are shifted to the destination side (sink), which is usually expected to be resource-full. As fewer resources are allocated to video compression, stronger cryptography may be applied at source nodes.  
Still concerning video coding, the compressive sensing paradigm exploits the information rate within a particular signal, removing redundancy in the signal during the sampling process [58; 59]. As compression is performed \"during\" sensing functions, encryption before transmission may also be relieved, which may benefit security mechanisms.  
Figure 2: Example of selective encryption for predictive video coding.  
Multipath routing is another relevant issue when addressing video cryptography. Different transmission paths may be used to transmit different video streams or different frames of the same source stream [60; 61]. Additionally, cryptography can be optimized to adapt to such a scenario.