## 7 Research Directions  
Many monitoring, tracking and control applications will have to deal with security threats that may compromise the effectiveness of applications or even expose confidential data. However, although security mechanisms are highly required for many applications, wireless sensor networks have constraints in processing, memory, transmission and energy supply. In general, image sensing, coding and transmission will demand more resources than scalar data handling, putting security in a critical position. In this context, mechanisms to assure optimized security for image transmissions in WSN have become highly necessary. The reviewed works in previous sections bring promising solutions for this complex scenario, but much more research efforts are still required. In this section, we envisage promising investigations in this area. Cryptanalysis of different encryption algorithms, both symmetric and asymmetric, is extremely relevant for the use of cryptography in wireless sensor networks. Therefore, the study of the complexity of encryption algorithms is highly required, aiming at the evaluation of computational cost, code size, memory consumption, key size, package size, communication cost and power consumption. Additionally, such analyses may be performed in conjunction with the evaluation of image coding techniques. Significant future research will tend to use selective encryption for WISN applications. Due to restrictions imposed by wireless sensor networks, the use of security mechanisms may be too stringent for many applications. When applying selective encryption, centered on combining encryption and encoding algorithms in the context of visual data, processing burden can be softened. In such way, a promising research trend could be focused on the application of selective encryption of images in wireless sensor networks, using innovative coding and encrypting algorithms. In general, selective encryption can be designed to be used with other image coding algorithms beyond quadtree and DWT. Actually, even those algorithms may be exploited in different ways, considering, for example, others wavelet-based algorithms, such as EZW (Embedded Zerotrees Wavelet), SPIHT (Set Partitioning In Hierarchical Trees), EBCOT (Embedded Block Coding with Optimized Truncation) and SPECK (Set Partitioned Embedded Block) [20,86]. Furthermore, there are other transform-based algorithms based on DCT, which uses a cosine transform where the decomposed image is mathematically expressed as a sum of cosine functions oscillating at different frequencies [72]. A well-known DCT coding algorithm is JPEG, which is largely used for image compression. One possibility is to implement JPEG computations in fixed-point arithmetic instead of floating point [87]; or even to exploit interpolation for higher efficiency [88]. In addition to the transform-based compression schemes, there are the non-transform-based schemes. The two most well-known algorithms are vector quantization compression and fractal compression, which can also be considered in future research on selective encryption of images. The study of the complexity of both encoding and encryption algorithms is very important for traditional and selective encryption alike. Thus, we believe that this is also a very promising research trend for secure wireless image sensor networks. Another research trend is the combination of selective encryption with QoS parameters. Possible approaches may be based on QoS with different scopes, which may have a local or global significance. For QoS at the local level [57], encrypted packets containing the most relevant parts of images may have higher traffic priority over other packets. Doing so, those packets may have a better chance of reaching the destination, and as they contain vital information for reconstructing original images, QoS at the local level ensures optimized functioning of WSN applications. On the other hand, QoS can be applied so that some source nodes may have a global significance, defining a special optimization scope [89,90].