Detecting insider threat within institutions using CERT dataset and different ML techniques

The reason of countries development in industrial and commercial enterprises fields in those countries. The security of a particular country depends on its security institutions, the confidentiality of its employees, their information, the target's information, and information about the forensic evidence for those targets. One of the most important and critical problems in such institutions is the problem of discovering an insider threat that causes loss, damage, or theft the information to hostile or competing parties. This threat is represented by a person who represents one of the employees of the institution, the goal of that person is to steal information or destroy it for the benefit of another institution's desires. The difficulty in detecting this type of threat is due to the difficulty of analyzing the behavior of people within the organization according to their physiological characteristics. In this research, CERT dataset that produced by the University of Carnegie Mellon University has been used in this investigation to detect insider threat. The dataset has been preprocessed. Five effective features were selected to apply three ML techniques Random Forest, Naïve Bayes, and 1 Nearest Neighbor. The results obtained and listed sequentially as 89.75917519%, 91.96650826%, and 94.68205476% with an error rate of 10.24082481%, 8.03349174%, and 5.317945236%

Perception and Acceptance of Using Different Generic Types of COVID-19 Vaccine, the “Mix-and-Match” Strategy, in Saudi Arabia: Cross-Sectional Web-Based Survey

Background: Soon after the COVID-19 pandemic was declared, a pharmaceutical company expressed rapid interest in developing a safe and effective vaccine candidate to contain the spread of SARS-CoV-2 infections. The FDA approved the Pfizer-BioNTech, AstraZeneca, Moderna, and Janssen vaccines. Here, we investigated the attitude and acceptance of using different generic types of COVID-19 vaccines in Saudi Arabia. Methods: This study is a cross-sectional study using an online survey conducted in Saudi Arabia from the 19th of October to the 6th of December 2021. The questionnaire was distributed using social media platforms such as Twitter, WhatsApp, and Facebook. The inclusion criteria to participate in this study were adults who live in Saudi Arabia (Saudis or non-Saudis) and had two doses of COVID-19 vaccinations. Result: 3486 participants were included in this study, and 67.5% of the participants had side effects after the first dose. Similarly, 66.7% of the study participants had side effects after administering the second dose. Our data showed that most participants were unsure if the heterologous COVID-19 vaccination could cause severe side effects. In addition, 47.6% of the participants refused to receive a different generic type of COVID-19 vaccine due to fear of health problems. However, most participants obtained information regarding COVID-19 vaccination from the Saudi Ministry of Health. Conclusions: We found a low level of acceptance for receiving different generic types of vaccines if the participants had a choice. Therefore, plans should focus on increasing the acceptance level among the Saudi population through official platforms such as the Saudi Ministry of Health and private clinics