ICSrank: A Security Assessment Framework for Industrial Control Systems (ICS)

This thesis joins a lively dialogue in the technological arena on the issue of cybersecurity and specifically, the issue of infrastructure cybersecurity as related to Industrial Control Systems. Infrastructure cybersecurity is concerned with issues on the security of the critical infrastructure that have significant value to the physical infrastructure of a country, and infrastructure that is heavily reliant on IT and the security of such technology. It is an undeniable fact that key infrastructure such as the electricity grid, gas, air and rail transport control, and even water and sewerage services rely heavily on technology. Threats to such infrastructure have never been as serious as they are today. The most sensitive of them is the reliance on infrastructure that requires cybersecurity in the energy sector. The call to smart technology and automation is happening nowadays. The Internet is witnessing an increase number of connected industrial control system (ICS). Many of which don’t follow security guidelines. Privacy and sensitive data are also an issue. Sensitive leaked information is being manipulated by adversaries to accomplish certain agendas. Open Source intelligence (OSINT) is adopted by defenders to improve protection and safeguard data. This research presented in thesis, proposes “ICSrank” a novel security risk assessment for ICS devices based on OSINT. ICSrank ranks the risk level of online and offline ICS devices. This framework categorizes, assesses and ranks OSINT data using ICSrank framework. ICSrank provides an additional layer of defence and mitigation in ICS security, by identification of risky OSINT and devices. Security best practices always begin with identification of risk as a first step prior to security implementation. Risk is evaluated using mathematical algorithms to assess the OSINT data. The subsequent results achieved during the assessment and ranking process were informative and realistic. ICSrank framework proved that security and risk levels were more accurate and informative than traditional existing methods

A new concept for the contact at the interface of steel-concrete composite beams

International audienceThis paper deals with the problem of contact at the interface of steel-concrete composite beams. The F.E. model "Pontmixte", able to study continuous composite beams at real scale, was based on a finite element of composite beam which considers only 4 degrees of freedom per node: both longitudinal displacements of the slab and the steel beam and common vertical displacement and rotation of the whole composite cross-section. This assumption did not allow any uplift at the interface between both materials. A "new" finite element is proposed in this work with 6 degrees of freedom per node in the aim to include a contact algorithm in the model. The originality of the method is to use the Augmented Lagrangian Method to solve the contact problem at the steel-concrete interface including a new concept so-called:"Flying Node Concept". This concept solves the problem of "continuous" contact at the interface that could sometimes occur along the beam especially in the case of distributed loads. The influence on the loading capacity of the beam and also the influence on some design variables are highlighted

The Power of Social Media in Supporting Warehouse Location Decisions for Online Retailers Using GIS

While online shopping is one of the fastest growing sectors in the U.S. economy and is quickly surpassing traditional retailers (Enright 2014), shopper demand data used to place warehouses is either proprietary or expensive. To address this, we present an alternative approach to identifying where online shopping demand occurs in Los Angeles County and therefore where to most efficiently place warehouses for online retailers. Twitter data was harvested identifying the location of tweets about Amazon or EBay. This information was used as a proxy to model location of online shoppers. When compared with U.S. Census population data for ages 18 to 40, the Twitter-derived data was found to be a much more effective means to model the location of online shoppers and more efficiently place online warehouses of goods

Design of a Mobile-App for Non-Invasively Detecting High Blood Cholesterol Using Eye Images

Medical research proves that high blood cholesterol is identifiable through the iris portion of the human eyes. Currently, a clinical blood test is the only method used in identifying high cholesterol. This study proposed an IT-based approach to prove the concept of monitoring cholesterol content in the blood using the human irises. We have developed a conceptual framework and a smartphone application aimed at capturing an image of the eye and analyzing it for symptoms associated with high blood cholesterol. This is a break-through innovation for a non-invasive way of finding out blood-cholesterol. The application captures the eye image and necessary metadata from a user. Then, a software code will examine the textural pattern of the eye, thus detecting the presence of high blood cholesterol. The result will be displayed on the user\u27s mobile application. Primarily, the feedback to the user will be either No or Yes cholesterol content in the blood. The results presented through this app will form the basis for a further medical checkup if necessary

Survival analysis approaches for prostate cancer.

Survival time has become an essential outcome of clinical trial, which began to emerge among the latter half of the 20th century. A present study was carried out on the survival analysis for patients with prostate cancer. The data was obtained from Memorial Sloan Kettering where each sample was collected from the recipients of the treatment of radical prostatectomy. The Kaplan-Meier method was used to obtain and estimate the survival function and median time among the primary and metastatic tumor of prostate cancer. Results showed that the metastatic tumor has a poor survival rate compared to the primary tumor, which give us a hint that primary tumor has a higher probability of surviving. The log-rank test was used to test the differences in the survival curves. The results showed that the difference in survival rate between the patients of the two groups of tumor was significant with a p-value of 4.44e-15. The second approach was based on the efficiency of cox proportional hazards model and parametric model. Some criteria of residuals were used for judging the goodness of fit among the candidate models. The cox proportional hazard (PH) model provided an effective covariate on the hazard function. As a result of cox PH model, the influence of standard clinical prognostic factors is based on the hazard rate of prostate cancer patients. These prognostic factors are: prostate specific antigen (PSA) level at diagnosis, tumor size, Secondary Gleason grade, and Gleason score which is helpful to determine the treatment. The Gleason score [HR 4.835, 95% CI 2.7847- 8.3937, p=2.20E-08] has the most significant progression-associated prognosticators and reveal to be an effective criteria leading to death in prostate cancer. The Accelerated Failure Time (AFT) was applied to the data with four distortions. AFT with Weibull distortions was chosen to be the best model for our data by testing the AIC.Master of Science (MSc) in Computational Science

Metabolic engineering aimed at the production of keto acids from glycerol : an industrial by-product

Worldwide, energy consumption is at an all-time high and projected to increasingly grow in the upcoming years. Thus, it is critical to uncover alternative sources of energy that are independent of fossil fuels and environmentally neutral. The transformation of biomass into various energy-rich chemicals is an important strategy that is being pursued globally. Biodiesel can be an interesting substitute to fossil fuels. However, this process generates excessive amounts of glycerol, a byproduct that needs to be converted into valuable products if the biodiesel industry is to be sustainable. The principle objective of this thesis is to study how glycerol can be used as a raw material by microbial systems to produce valuable products. The soil microbe, Pseudomonas fluorescens widely utilized in the numerous biotechnological applications due to its nutritional versatility is an obvious choice to tailor into a glycerol-transforming nanofactory. The abiotic modulators namely hydrogen peroxide (H2O2) and manganese (Mn) afforded uniquely facile means of triggering metabolic reprogramming aimed at the enhanced formation of pyruvate and α-ketoglutarate (KG). Under the influence of H2O2, P. fluorescens engineers an intricate metabolic network to synthesize ATP and pyruvate. As oxidative phosphorylation is severely impeded, the microbe invokes substrate level phosphorylation to generate energy. This is accomplished via the increased activities of various enzymes including pyruvate carboxylase (PC) and phosphoenolpyruvate carboxylase (PEPC) that were analyzed by blue-native polyacrylamide gel electrophoresis (BN-PAGE) and high performance liquid chromatography (HPLC). The high-energy phosphoenolpyruvate (PEP) is then converted into ATP and pyruvate, a process mediated by pyruvate phosphate dikinase (PPDK), phosphoenolpyruvate synthase (PEPS) and pyruvate kinase (PK). Supplementation with a micro-nutrient such as Mn, a divalent metal involved in a variety of enzymes results in the reprogramming of the metabolic networks aimed at the accumulation of KG. The increased activities of isocitrate dehydrogenase (ICDH)- (NAD)P dependent and aminotransaminases aided the exocellular secretion of KG. The overexpression of pyruvate carboxylase (PC) that is evident in the Mn-treated cells provides oxaloacetate, an important precursor to the synthesis of citrate, a key ingredient in the synthesis of KG. Isocitrate lyase (ICL), fumarate reductase (FUMR), succinate semialdehyde dehydrogenase (SSADH), α-ketoglutarate decarboxylase (KDC) and γ-aminobutyric acid transaminases (GABAT) work in concert to produce KG. 13C-NMR helped identify the metabolites participating in the metabolic networks. Immunoblot experiments confirmed the presence of overexpressed enzymes. These disparate metabolic pathways that promote the overproduction of the keto-acids in P. fluorescens have the potential of converting glycerol to value-added products commercially. As the process utilized is devoid of any genetic manipulation, it can be readily implemented in an industrial setting. In conclusion, both H2O2 and Mn can orchestrate metabolic changes in P. fluorescens inducing the production of pyruvate and KG from glycerol respectively. These chemical manipulations may also be applied to other microbial systems.Doctor of Philosophy (PhD) in Biomolecular Science

Microstructural imaging of the eye and mechanical mapping of retinal tissue using Atomic Force Microscopy (AFM)

The objective of this study is to investigate the structures and mechanical properties of mouse eyes in correspondence with their functions. Moreover, my work places particular emphasis on the retina as it is associated with several diseases. To measure the mechanical properties of retinal tissue, eye samples of mice are taken and analyzed utilizing Force Spectroscopy to determine the Young’s modulus. Force mapping of the sample is done by nanoindentation (force curves), and Atomic Force Microscopy (AFM) is used to image the topography of our sample. AFM and force mapping provide key information on the nanoscale mechanical properties and structure of normal tissue. This fine level of detail provides insight on a length scale relevant to an individual cell. Our results also provide a baseline structure to enable the identification of mechanical indicators for disease. Most of the diseases that affect the eyes, including glaucoma and macular degenerations involve structural changes in the eyes, for example, affecting the photoreceptor or degeneration of layers thus causing eye damage. Damage on the nanoscale is not obvious given that research in that area is still underdeveloped. Therefore, the use of nanomechanical mapping has proved to be very useful because of providing in-depth knowledge regarding the characteristic microstructure and mechanical features of the normal eye

Efficient implementation of a component-based joint model

This paper deals with a nonlinear analysis of beam-to-column steel joint. The connection uses an end-plate welded to the steel cross-section of a steel-concrete composite beam and bolted to the column flange. The proposed model developed herein combines the knowledge of prior studies that used the component-based approach, on one hand and the Finite Element algorithmsin plasticity, on second hand. The originality of this work is to efficiently take into account possible gaps between the end-plate and the column flange in case of plastic deformation of some components of the joint during the cyclic loading. The numerical investigation aims topredict the behavior of this type of joint in presence of the gap during the cyclic loading

Unleashing the power of internet of things and blockchain: A comprehensive analysis and future directions.

As the fusion of the Internet of Things (IoT) and blockchain technology advances, it is increasingly shaping diverse fields. The potential of this convergence to fortify security, enhance privacy, and streamline operations has ignited considerable academic interest, resulting in an impressive body of literature. However, there is a noticeable scarcity of studies employing Latent Dirichlet Allocation (LDA) to dissect and categorize this field. This review paper endeavours to bridge this gap by meticulously analysing a dataset of 4455 journal articles drawn solely from the Scopus database, cantered around IoT and blockchain applications. Utilizing LDA, we have extracted 14 distinct topics from the collection, offering a broad view of the research themes in this interdisciplinary domain. Our exploration underscores an upswing in research pertaining to IoT and blockchain, emphasizing the rising prominence of this technological amalgamation. Among the most recurrent themes are IoT and blockchain integration in supply chain management and blockchain in healthcare data management and security, indicating the significant potential of this convergence to transform supply chains and secure healthcare data. Meanwhile, the less frequently discussed topics include access control and management in blockchain-based IoT systems and energy efficiency in wireless sensor networks using blockchain and IoT. To the best of our knowledge, this paper is the first to apply LDA in the context of IoT and blockchain research, providing unique perspectives on the existing literature. Moreover, our findings pave the way for proposed future research directions, stimulating further investigation into the less explored aspects and sustaining the growth of this dynamic field