## 1 Introduction  
Smart-traffic management systems make use of sensors, car dash cams, street and traffic light cameras, mobile networks, and many other technologies to monitor, regulate, and respond to traffic congestion and vehicular accidents [1]. It mainly relies on the video feeds received from these technologies, which are processed by servers. Any unauthorized access to these feeds during their transmission can result in a confidentiality breach of the system. Therefore, ensuring the confidentiality of such video feeds is of paramount importance in smart-traffic management. Unfortunately, due to the huge volumes of data generated by such sources [2] and their low computational power and memory capacity, applying classical encryption schemes [3] such as Advanced Encryption Standard (AES) [4] and Data Encryption Standard (DES) [5] is not feasible. In addition, certain properties in multimedia content, such as redundancies and high correlation, makes the use of such classical encryption schemes inefficient and expensive in terms of computational time and power required [6], especially in real-time applications such as smart-traffic management.  
Fortunately, chaos-based cryptography presents a solution where certain properties of chaotic systems, such as the high sensitivity to initial condition (IC) and control parameter (CP) and random-alike appearance, can be used to yield strong encryption but with less computational and memory capacity required [7]. It is relatively easy to generate such chaotic system using differential or recursive equations. Over the last two decades, various chaotic-based image encryption schemes were proposed [8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24]. However, as the volume of data increases, the computational and memory capacity requirements also increase. To overcome this problem, selective encryption can be used to select and encrypt only the most significant parts of the data [25, 26, 27, 28, 29]. If the selection is done properly, encryption using chaotic maps of the selected parts of an image (or a video sequence) results in strong encryption with a significantly less requirement of computational and memory capacity for encrypting huge volumes of data in real time [30]. This selective encryption can be done in a spatial domain where only the four most significant bits (MSBs) of each pixel are selected and encrypted [31], or in a frequency domain where the image is decomposed using discrete cosine transform (DCT); then, only 25% of the frequencies are selected to be encrypted [30].  
In this paper, a study on the singular value decomposition (SVD) [32] is conducted, and experiments were drawn to understand the properties of the decomposition and identify the coefficients that needs to be selected for encryption; this is done in order to reduce the amount of data that needs to encrypted given the huge size of the video feeds and the limitations in the computational power. Chaotic maps [8; 30] were used in the design of the cryptosystem to increase the complexity and take advantage of the random-alike appearance. The proposed scheme is implemented and evaluated, and the results suggests that the scheme dramatically reduces the computational overhead.  
The rest of the paper is organized as follows: Section 2 presents the background and related work, Section 3 discusses the proposed scheme, Section 4 describes the experiments and results, and finally, Section 5 presents the conclusion.