Privacy and security are among the significant challenges of the Internet of Things (IoT). Improper device updates, lack of efficient and robust security protocols, user unawareness, and famous active device monitoring are among the challenges that IoT is facing. In this work, we are exploring the background of IoT systems and security measures, and identifying (a) different security and privacy issues, (b) approaches used to secure the components of IoT-based environments and systems, (c) existing security solutions, and (d) the best privacy models necessary and suitable for different layers of IoT driven applications. In this work, we proposed a new IoT layered model: generic and stretched with the privacy and security components and layers identification. The proposed cloud/edge supported IoT system is implemented and evaluated. The lower layer represented by the IoT nodes generated from the Amazon Web Service (AWS) as Virtual Machines. The middle layer (edge) implemented as a Raspberry Pi 4 hardware kit with support of the Greengrass Edge Environment in AWS. We used the cloud-enabled IoT environment in AWS to implement the top layer (the cloud). The security protocols and critical management sessions were between each of these layers to ensure the privacy of the users’ information. We implemented security certificates to allow data transfer between the layers of the proposed cloud/edge enabled IoT model. Not only is the proposed system model eliminating possible security vulnerabilities, but it also can be used along with the best security techniques to countermeasure the cybersecurity threats facing each one of the layers; cloud, edge, and IoT.

The global spread of the COVID-19 pandemic and its unprecedented impact not only on health and economy but almost on all aspects of our lives, including how we work, meet, communicate, collaborate, etc. Unfortunately, these changes and the transition to the virtual space in such a short time without proper planning created opportunities for bad actors in cyberspace. In the last few months, we have witnessed new treads and waves of cyber-attacks targeting businesses, governments, health, and other critical services. Attackers try to take advantage of people's fear of the virus, vulnerabilities associated with data collection sensors and IoT devices, and eagerness to look for solutions or protections. In this study, we will survey the nature of cyberattacks related to the COVID-19 outbreak. Them, we will analyze related data to phishing attacks using Neural Networks. This analysis is covering different technical and socio-economical aspects. We will also evaluate states' countermeasures in response to such attacks. We propose a new IoT model. We define three layers; End User, Device or Sensors, and Cloud. We can combine the proposed model with the security and privacy policies to countermeasure the cybersecurity threats facing each layer.

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