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With the advent of IoT, Device-to-Device (D2D) communications has afforded a new paradigm that reliably facilitates data exchange among devices in proximity without necessarily involving the base (core) network. It is geared towards the need to improve network performance where short-range communications is concerned, as well as supporting proximitybased services. However, the relentless growth in the number of network end-users as well as interconnected communication-capable devices, in the next-generation IoT-based 5G cellular networks has resulted in novel services and applications, most of which are security-sensitive. It is thus of paramount importance that security issues be addressed. A posing challenge is that the devices are mostly resource-constrained in both power and computing. As such, it is not practical to implement present day as well as traditional security frameworks and protocols under such a scenario, unless strides are taken towards the improvements of data throughput rates, higher bandwidth provisioning, lower round trip latencies, enhanced spectral efficiencies, and energy efficiency (leading to even lower power consumption, by the already constrained devices) in IoT 5G/LTE networks. Therefore, this work focused on exploring and designing schemes that enhance security and privacy among communicating parties. Otherwise, without reliable as well as robust privacy and security preservation measures in the network, most services and applications will be exposed to various forms of malicious attacks. With such a widened cyber-attack space, both privacy and security for end users can easily be compromised. The work herein addresses privacy for subscribers to the various available services and applications as well as security of the associated data. Ultimately, we propose a Fog-Cloud computing paradigm-assisted security framework that comprises two schemes. The aim is to implement a lightweight-based cartographic algorithm that ensures that communication overheads, round trip latencies, computational loads as well as energy consumption by the otherwise resource-constrained surveillance cameras deployed remotely, are kept minimal. Overall, by way of both analysis and simulation, we ascertain that a Fog-Cloud computing-based lightweight security-based scheme has the potential to greatly improve security and privacy preservation, as well as overall performance despite the resource-constrained nature of the devices.