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This paper aims at building the causal relations and event structures [13] to study the complex and evolving cyber – physical systems with illustrations of the reasoning based on Robotics [24] and Policy Analysis [25] for Communication Systems. An empirical analysis points to the realism that network security is also a geometric theory with safety and authentication tending to geometric formulae that make the larger structures. Security is very much a matter of perception too. The proposed approach also factors the perceptual aspects of the human mind. This paper includes several interesting possibilities for using linear algebra, discrete mathematics, analysis, and topology in the domains such as economics, game theory, robotics and biology to mention a few.

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Reinforcement learning (RL) is a type of ML, which involves learning from interactions with the environment to accomplish certain long-term objectives connected to the environmental condition. RL takes place when action sequences, observations, and rewards are used as inputs, and is hypothesis-based and goal-oriented. The key asynchronous RL algorithms are Asynchronous one-step Q learning, Asynchronous one-step SARSA, Asynchronous n-step Q-learning and Asynchronous Advantage Actor-Critic (A3C). The paper ascertains the Reinforcement Learning (RL) paradigm for cybersecurity education and training. The research was conducted using a largely positivism research philosophy, which focuses on quantitative approaches of determining the RL paradigm for cybersecurity education and training. The research design was an experiment that focused on implementing the RL Q-Learning and A3C algorithms using Python. The Asynchronous Advantage Actor-Critic (A3C) Algorithm is much faster, simpler, and scores higher on Deep Reinforcement Learning task. The research was descriptive, exploratory and explanatory in nature. A survey was conducted on the cybersecurity education and training as exemplified by Zimbabwean commercial banks. The study population encompassed employees and customers from five commercial banks in Zimbabwe, where the sample size was 370. Deep reinforcement learning (DRL) has been used to address a variety of issues in the Internet of Things. DRL heavily utilizes A3C algorithm with some Q-Learning, and this can be used to fight against intrusions into host computers or networks and fake data in IoT devices.

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System security is very important, especially in the age that we live in. One of the ways to secure data is by creating a password that makes it difficult for unauthorized user to gain access to the system. However, what makes it difficult for the system to be attacked is directly dependent on approach used to create it, and how secured it is. Text based approach is the oldest authentication approach. It requires that the user supplies textual password in order to gain access to the system. However, this approach has shown a significant drawback and several vulnerabilities, one of which is the difficulty in recalling or remembering textual passwords. Several other attacks that textual passwords are vulnerable to include brute force attacks, shoulder spying, dictionary attacks etc. The introduction of graphical schemes made things a lot better. Graphical passwords make use of images. However, most graphical schemes are vulnerable to shoulder surfing attacks. In this research work, we developed two systems; A position-based multi-layer graphical user authentication system and an Image-based multi-layer graphical user authentication system. The reason behind this research work is to compare the two systems, and evaluate them based on three major performance metrics: (1) Security, (2) Reliability (3) Individual preference.

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Wearable tracking gadget that school-age children can wear is the topic of this paper. It doesn't need any pricy technology to operate.. This technology is usable by persons of all educational levels. It has got two buttons one is alert button and another is panic button The major objective of this gadget is to ensure that the youngster may contact their parents in an emergency. The alert button allows the child to notify their parents of an emergency and provide their current location. For communication, the current technology includes Bluetooth, WI-FI, and RFID. It is hard to communicate across a great distance with these technologies because they only have a narrow range of coverage. Also they are not that accurate. This device solves the issue by utilizing GSM technology. Parents do not need to submit any special code to the device to determine the child's location's latitude and longitude. If a child is in any emergency situation and wants his/her parents to know their current exact location. If a child feels uneasy, there are two methods to let the parents know. The cell phone of the parents or guardian receives the alarm message via SMS by pressing alert button and if the child wants to communicate to parents immediately, a call can also be made via this device using the panic button and the child can talk to the parent in real time.

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COVID-19 is an ongoing pandemic and dangerous of coronavirus disease 2019. It caused by the transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). COVID-19 spreads most often when people are physically close. And, it spreads very easily and sustainably through the air, primarily via small droplets or aerosols, as an infected person breaths, coughs, sneezes, sings or speaks. The recommended preventive measures include hand washing, covering one’s mouth when sneezing or coughing, physical distancing, wearing a face mask in public, ventilation and air-filtering, disinfecting surfaces, and monitoring and self-isolation for people exposed or symptomatic. Hence, this paper proposed the architecture of physical distancing detection system with distance sensor which deployed on UAV System with the help of BTS (2G/3G/4G/5G) to enrich the COVID-19 preventive measures, as well as I have also developed a few algorithms for distance sensor (on UAV System) operations which sensing, tagging and disseminating the current distance, position and waiting time of resident’s information, and forwarding schemes to respective infrastructures and suspected residents including the security forces.

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