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Using dynamic surveillance cameras for security has significantly increased the privacy concerns for captured individuals. Malicious users may misuse these videos by performing Replay and/or Man-in-the-Middle attacks during storage or recording over the network. Considering these risks, this paper proposes an effective security application SecureCam based on selective detection (focused moving objects) and protection using encryption. For object detection, this paper implements a novel low computational unsupervised learning algorithm, i.e., Motion-Fusion (MF) for more precise motion detection in the mobile camera videos. After that, selective encryption (SE) is applied by the lightweight Chacha20 cipher to the detected video parts. Proposed SecureCam is extensively evaluated based on performance analysis, security analysis and computational complexity. For object detection, the comparative evaluation …