The need for secure information exchange is increasingly felt with an exponential rise in the number of small devices often associated with critical processes, which frequently share sensitive data. Recently, 5G networks provided integrated platforms for the connectivity of an enormous number of small devices in the form of Internet of Things (IoT), across diversified and heterogeneous networks. The growth in connectivity is also spreading the threat surface exponentially, requiring tailored security approaches suited to the specific needs of these devices. Compressive sensing (CS) has proven to be an appropriate choice for the security needs of small devices. This research proposes the construction of a single combined measurement matrix built from two discrete chaotic sequences for enhanced randomness in the data. Additionally, a separate chaotic system is used in a novel way to construct orthogonal matrices. The initial values and other parameters of the chaotic systems are calibrated to build considerable diffusion and confusion in the data, thereby enhancing security. Besides, these parameters also serve as keys enabling layered security. The combination of multi-chaotic systems further reinforces the encryption process with enriched coding and heightening security. Both theoretical analysis and simulation suggest that the proposed scheme has significantly improved the overall security, which in particular makes it resilient against known statistical, brute-force and differential attacks. Moreover, the use of CS also significantly improves the transmission efficiency. The proposed scheme is effective in both security enhancement and improving efficiency, particularly for small resource-constrained devices (i.e., IoTs, D2D and sensor networks).
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