A testbed to simulate cyber attacks on nuclear power plants

Nuclear power plants are critical infrastructures that must be safe and secure from undesirable intrusions: these intrusions are both physical and cyber. The increasing usage of digital control and computer systems, for supervisory control and data acquisition in the control rooms of new generation nuclear reactors, has introduced several cyber security issues that must be addressed. One of the most significant problems is that this new technology has increased the vulnerability of the nuclear power plant to cyber security threats. Furthermore, this exposed vulnerability is one of the main reasons that the transition to digital control rooms connected to enterprise network (or the internet) has been slow and hesitant. In order to address these issues and ensure that a digital control system is safe and secure from undesirable intrusions, the system must go through extensive tests and validation. These tests will verify that systems are safe and properly functioning. The vulnerabilities of a nuclear power plant can be determined through conducting cyber security exercises, cyber security attacks scenarios, and simulated attacks. All these events can be performed using the control room in the nuclear power plant, but it is a complicated and hampered process because of the complex hardware and software interactions that must be considered. Control rooms are also not ideal places to test various cyber attacks and scenarios because any mishap can lead to detrimental impacts on the nearby surroundings. This research attempts to present our approach to build a comparative testbed that captures the relevant complexity of a nuclear power plant. A testbed is developed and designed to assess the vulnerabilities that are introduced by using public networks for communications. The testbed is also used to simulate different cyber attack scenarios and it will serve to present detection mechanisms that are based on the understanding of the controlled physical system

Metformin Pharmacogenetics: Effects of SLC22A1, SLC22A2, and SLC22A3 Polymorphisms on Glycemic Control and HbA1c Levels

Type 2 diabetes mellitus (T2DM) constitutes a major portion of Jordan’s disease burden, and incidence rates are rising at a rapid rate. Due to variability in the drug’s response between ethnic groups, it is imperative that the pharmacogenetics of metformin be investigated in the Jordanian population. The objective of this study was to investigate the relationship between twenty-one single nucleotide polymorphisms (SNPs) in the SLC22A1, SLC22A2, and SLC22A3 genes and their effects on metformin pharmacogenetics in Jordanian patients diagnosed with type 2 diabetes mellitus. Blood samples were collected from 212 Jordanian diabetics who fulfilled the inclusion criteria, which were then used in SNP genotyping and determination of HbA1c levels. The rs12194182 SNP in the SLC22A3 gene was found to have a significant association (p < 0.05) with lower mean HbA1c levels, and this association more pronounced in patients with the CC genotype (i.e., p-value was significant before correcting for multiple testing). Moreover, the multinomial logistic regression analysis showed that SNP genotypes within the SLC22A1, SLC22A2, and SLC22A3 genes, body mass index (BMI) and age of diagnosis were significantly associated with glycemic control (p < 0.05). The results of this study can be used to predict response to metformin and other classes of T2DM drugs, making treatment more individualized and resulting in better clinical outcomes