The large-scale data exchange envisioned to occur in distributed IoTs is prone to raise issues regarding privacy, confidentiality and authentication at the cyberspace level. This work focuses to preserve privacy and confidentiality of data in an insecure environment of multimedia exchange between two IoT hops. In order to thwart an adversary, and ensure data confidentiality, we propose a robust multi-level security approach based on information hiding and chaotic theory. Although, some existing block-based robust data hiding schemes based on transform domain offer good results; but the inefficient block and coefficient selection/modification results in poor performance to various commonly occurring cyber-attacks. The proposed scheme is based on Random Coefficient Selection and Mean Modification Approach (RCSMMA). Unlike conventional approaches, which use single coefficient from a block to embed an information bit, RCSMMA uses multiple Discrete Cosine Transform coefficients selected randomly from two non-neighbourhood blocks to ensure information spread over different areas of the cover image. The proposed approach results in very high robustness of the information transferred between two nodes, for all signal processing and the region-oriented attacks, acting simultaneous or standalone. For attacks like rotation, cropping, histogram equalization and sharpening, a very high robustness is achieved with Normalized Cross Correlation close to unity. For other singular/combined attacks average Normalized Cross Correlation is greater than 0.95. The average Peak Signal to Noise Ratio obtained for various images is greater than 40 dB with the payload of 4Kb. The experimental results demonstrate the superiority of the proposed scheme over other state-of-art techniques.