Cyberinfrastructure Research Articles

A Threat Computation Model using a Markov Chain and Common Vulnerability Scoring System and its Application to Cloud Security

Securing cyber infrastructures has become critical because they are increasingly exposed to attackers while accommodating a huge number of IoT devices and supporting numerous sophisticated emerging applications. Security metrics are essential for assessing the security risks and making effective decisions concerning system security. Many security metrics rely on mathematical models, but are mainly based on empirical data, qualitative methods, or compliance checking, and this renders the outcome far from satisfactory. Computing the probability of an attack, or more precisely a threat that materialises into an attack, forms an essential basis for a quantitative security metric. This paper proposes a novel approach to compute the probability distribution of cloud security threats based on a Markov chain and Common Vulnerability Scoring System. Moreover, the paper introduces the method to estimate the probability of security attacks. The use of the new security threat model and its computation is demonstrated through their application to estimating the probabilities of cloud threats and types of attacks.

Identifier Services: Modeling and Implementing Distributed Data Management in Cyberinfrastructure

The Identifier Services (IDS) project conducted research into and built a prototype to manage distributed genomics datasets remotely and over time. Inspired by archival concepts, IDS allows researchers to track dataset evolution through multiple copies, modifications, and derivatives, independent of where data are located – both symbolically, in the research lifecycle, and physically, in a repository or storage facility. The prototype implementation is based on a three-step data modeling process involving: a) understanding and recording of different researcher workflows, b) mapping the workflows and data to a generic data model and identifying functions, and c) integrating the data model as architecture and interactive functions into cyberinfrastructure (CI). Identity functions are operationalized as continuous tracking of authenticity attributes including data location, differences between seemingly identical datasets, metadata, data integrity, and the roles of different types of local and global identifiers used during the research lifecycle. CI resources were used to conduct identity functions at scale, including scheduling content comparison tasks on high-performance computing resources. The prototype was developed and evaluated considering six data test cases, and feedback was received through a focus-group activity. While there are some technical roadblocks to overcome, our project demonstrates that identity functions are innovative solutions to manage large distributed genomic datasets.

Model selection for hybrid dynamical systems via sparse regression.

Hybrid systems are traditionally difficult to identify and analyse using classical dynamical systems theory. Moreover, recently developed model identification methodologies largely focus on identifying a single set of governing equations solely from measurement data. In this article, we develop a new methodology, Hybrid-Sparse Identification of Nonlinear Dynamics, which identifies separate nonlinear dynamical regimes, employs information theory to manage uncertainty and characterizes switching behaviour. Specifically, we use the nonlinear geometry of data collected from a complex system to construct a set of coordinates based on measurement data and augmented variables. Clustering the data in these measurement-based coordinates enables the identification of nonlinear hybrid systems. This methodology broadly empowers nonlinear system identification without constraining the data locally in time and has direct connections to hybrid systems theory. We demonstrate the success of this method on numerical examples including a mass–spring hopping model and an infectious disease model. Characterizing complex systems that switch between dynamic behaviours is integral to overcoming modern challenges such as eradication of infectious diseases, the design of efficient legged robots and the protection of cyber infrastructures.

Cyber-ARGUS - A mission assurance framework

The use of cyberspace as a platform for military operations has been growing at impressive rates. Yet, it is still a relatively new area that poses considerable research challenges. Security techniques are not sufficiently effective to protect IT systems and most fail to address the correlation between actions and effects across multiple domains. In other words, identifying how actions performed in the cyber domain affect the mission goals is yet an unsolved problem. This research presents a potential solution and proposes a framework that links the cyber and the operations domains, evaluating how actions in the first impact the effectiveness of missions in the latter. The framework, Cyber-ARGUS, is a Command and Control (C2) support system comprised of a set of tools that provides coherent and consistent mapping between the two domains. Relevant information about the nodes of a cyber infrastructure supporting an operation is stored in a knowledge base, and then used to build a Bayesian Network that provides impact assessment. The technique is illustrated through the simulation of an air transportation scenario in which the C2 infrastructure is subjected to various cyber-attacks, and Cyber-ARGUS is used to assess their associated impact to the air operations. The main contribution of this research is the methodology that enables assessing the cyber impact to ongoing missions. One major advantage of the technique is that it achieves this by calculating the combined effects produced by the attackers and defenders plans, without the requirement of knowing the hard-to-assess enemy's individual actions.

A Robust Approach for Mitigating Risks in Cyber Supply Chains.

In recent years, there have been growing concerns regarding risks in federal information technology (IT) supply chains in the United States that protect cyber infrastructure. A critical need faced by decisionmakers is to prioritize investment in security mitigations to maximally reduce risks in IT supply chains. We extend existing stochastic expected budgeted maximum multiple coverage models that identify "good" solutions on average that may be unacceptable incertain circumstances. We propose three alternative models that consider different robustness methods that hedge against worst-case risks, including models that maximize the worst-case coverage, minimize the worst-case regret, and maximize the average coverage in the worst cases (conditional value at risk). We illustrate the solutions to the robust methods with a case study and discuss the insights their solutions provide into mitigation selection compared to an expected-value maximizer. Our study provides valuable tools and insights for decisionmakers with different risk attitudes to manage cybersecurity risks underuncertainty.

Source-Load Coordinated Reserve Allocation Strategy Considering Cyber-Attack Risks

With the developing cyber physical power systems and emerging threat of cyber-attacks, the traditional power services are faced with higher risks of being compromised, as vulnerabilities in cyber infrastructure can be exploited to cause physical damage. Therefore, adjustments need to be made in current control scheme design methods to mitigate the impact of potential attacks on service quality. In this paper, focusing on the service of coordinated source-load participation in primary frequency regulation, a vulnerability analysis is performed with modelling the attack intrusion process, and the risk assessment of the service is made by further modelling the attack impacts on the service’s physical effects. On that basis, the traditional coordinated reserve allocation optimization model is modified and the allocation scheme is corrected according to the cyber-attack impacts. The proposed correction methods are validated through a case study, showing effectiveness in defending against the cyber-attack impacts.

Medical Cyber Physical Systems and Its Issues

Abstract In the previous decade, many technologies have attracted attention from several research communities. Internet of Things (IoT) is main invention of the recent/ past decade. When these smart devices or internet connected devices are interact together, then they create a cyber infrastructure. These cyber infrastructures face several serious concerns privacy, trust, security, etc. These smart devices make an automatic environment (executed without the intervention of a human) in applications likedefense, manufacturing, e-healthcare, etc. In e-healthcare, these devices built the structure of Medical Cyber Physical System (MCPS). MCPS are facing several critical issues and challenges in current era, i.e., several attacks, issues and challenges which we require to overcome in current and next decade to provide efficient and reliable service to patients. MCPS is need of smart healthcare and require attention from several research communities towards its raised issue. Hence, this article provides a detailed study about CPS, MCPS, mitigated attacks on same architecture (CPS and MCPS), issues and challenges in CPS/ MCPS, including several research gaps in CPS/ MCPS (with opportunities for future researchers).

Fragmenting Cybersecurity Norms Through the Language(s) of Subalternity: India in “the East” and the Global Community

The global cybersecurity discourse has never proved more fragmented than in the aftermath of the failure of the last United Nations Group of Governmental Experts on Developments in the Field of Information and Telecommunications in the Context of International Security. This discourse stands trapped in long-lasting and seemingly crystallized normative stances between “the West” and “the East,” yet it also calls upon the international community to regulate a wide spectrum of phenomena, ranging from thefts of digitally-stored trade secrets to large-scale pervasive attacks, which may soon reach the threshold of armed attacks. If one situates the major cybersecurity players on a sliding scale between freedom and control over cyber content and infrastructure, the mainstream stance would place the United States, the European Union, the United Kingdom, Brazil, India, China, and Russia in that order. Nonetheless, this scale is in practice more complex, in part due to the influence of the Shanghai Cooperation Organisation, a regional security forum which has witnessed major rebalancing after the membership expansion in June 2017. This paper scrutinizes India’s contribution towards a possible fragmentation of the “Eastern” cybersecurity discourse based on hard laws and state assertiveness, and the consequent disruption of the constructivist East-West binary dialectic about cyberwarfare, cyberterrorism, cyber espionage, and online data protection. By simultaneously negotiating its sub-alterity and rejecting its subalternity, India holds the potential to reshape an otherwise almost-coherent “cyber East.”

A machine vision platform for measuring imbibition of maize kernels: quantification of genetic effects and correlations with germination

BackgroundImbibition (uptake of water by a dry seed) initiates the germination process. An automated method for quantifying imbibition would enable research on the genetic elements that influence the underlying hydraulic and biochemical processes. In the case of crop research, a high throughput imbibition assay could be used to investigate seed quality topics or to improve yield by selecting varieties with superior germination characteristics.ResultsAn electronic force transducer measured imbibition of single maize kernels with very high resolution but low throughput. An image analysis method was devised to achieve high throughput and sufficient resolution. A transparent fixture held 90 maize kernels in contact with water on the imaging window of a flatbed document scanner that produced an image of the kernels automatically every 10 min for 22 h. Custom image analysis software measured the area A of each indexed kernel in each image to produce imbibition time courses. The ultimate change in area (ΔA) ranged from 19.3 to 23.4% in a population of 72 hybrids derived from 9 inbred parents. Kernel area as a function of time was fit well by Aleft( t right) = A_{f} left( {1 - e^{ - kt} } right) where Af is the final kernel area. The swelling coefficient, k, ranged from 0.098 to 0.159 h−1 across the genotypes. The full diallel structure of the population enabled maternal genotype effects to be assessed. In a separate experiment, measurements of kernels of the same 25 inbreds produced in three different years demonstrated that production and storage variables affected imbibition much less than genotype. In a third experiment, measurements of 30 diverse inbred lines showed that k varied inversely with germination time (r = − 0.7) and directly with germination percentage (r = 0.7).ConclusionsNonspecialized imaging hardware and custom analysis software running on public cyber infrastructure form a low-cost platform for measuring seed imbibition with high resolution and throughput. We measured imbibition of thousands of kernels to determine that genotype influenced imbibition of maize kernels much more than seed production and storage environments. In some hybrids, k depended on which inbred parent was maternal. Quantitative relationships between k and germination traits were discovered.

APPLICATION OF ARTIFICIAL INTELLIGENCE IN FIGHTING AGAINST CYBER CRIMES: A REVIEW

Cybercrimes have become a daily menace with the unprecedented progress made in the Information Technology (IT). Cyber infrastructures are exposed to serious Cybercrimes and attacksevery day. Physical devicesand human intervention have not been fully successful in monitoring and protection of these infrastructures; hence, there comes a need of highly effectivedefense systems that need to be flexible, adaptable and robust, which must be able to defend the IT infrastructure against innumerable and highly potential cyber-attacks. Umpteen techniques of artificial intelligence have been playing a key role in cybercrime detection and prevention. This study aims at putting forth the progress made in Artificial Intelligence in fighting against the numerous cybercrimes and shows the effectiveness of various AI techniques in detecting and preventing cyber-attacks, as well as to give the scope for future work.

Blockchain: a secure, decentralized, trusted cyber infrastructure solution for future energy systems

Modern power systems are rapidly evolving into complex cyber-physical systems. The increasingly complex interaction among different energy entities calls for a secure, efficient, and robust cyber infrastructure. As an emerging distributed computing technology, Blockchain provides a secure environment to support such interactions. This paper gives a prospective on using Blockchain as a secure, distributed cyber infrastructure for the future grid. Firstly, the basic principles of Blockchain and its state-of-the-art are introduced. Then, a Blockchain based smart grid cyber-physical infrastructure model is proposed. Afterwards, some promising application domains of Blockchain in future grids are presented. Following this, some potential challenges are discussed.

An efficient revenue distribution method in a cyber-enabled manufacturing system

Considering a group of suppliers fulfilling the orders in an e-commerce platform, it is desirable for the platform operator to distribute the revenue in a way that the total net utilities of the platform and of each supplier are optimized. Based on the game theory, this paper presents a nonlinear revenue distribution rule to achieve Nash Equilibrium. Simulation studies show that, compared to the proportional and equal distribution rules, the proposed method yields the highest net utility for all. The present work demonstrates an approach to promoting broader participation of manufacturing activities in an internet-based platform enabled by cyber infrastructure.

Contributions of citizen scientists to arthropod vector data in the age of digital epidemiology.

Citizen-collected arthropod vectors are useful for epidemiological studies of vector-borne disease, especially since the vectors encountered by the public are the subset of vectors in nature that have a disproportionate impact on health. Programs integrating educational efforts with collecting efforts may be particularly effective for public health initiatives, resulting in an empowered public with knowledge of vector-borne disease prevention. Citizen science programs have been successfully implemented for the collection of unprecedented sample sets of mosquitos, ticks, and triatomines. Cyber infrastructure employed in digital epidemiology-including websites, email, mobile phone apps, and social media platforms-has facilitated vector citizen science initiatives to assess disease risk over vast spatial and temporal scales, advancing research to mitigate vector-borne disease risk.

Best social and organizational practices of successful science gateways and cyberinfrastructure projects

The majority of research on science gateways has focused on technological tools. However, the teams behind the tools also play a critical role in determining whether science gateways are successful. This article reports 12 social and organizational practices of successful science gateways and cyberinfrastructure (CI) projects that emerged out of an analysis of 98 interviews with domain scientists, computational technologists, and supercomputing/research center administrators across the US and some in EU. Social practices include seeking multidisciplinary expertise, setting shared goals, using common language, having bridging liaisons, establishing productive routines, and meeting face-to-face. Organizational practices include demonstrating altruistic leadership, having clear roles, engaging user feedback, raising sustainable funding, growing organizational capacity, and maintaining personnel continuity. By asking a series of simple questions for reflection, science gateway teams can generate strategies to increase their likelihood of successful outcomes.

Human-Technology Centric In Cyber Security Maintenance For Digital Transformation Era

The development of the digital transformation in the organizations has become more expanding in these present and future years. This is because of the active demand to use the ICT services among all the organizations whether in the government agencies or private sectors. While digital transformation has led manufacturers to incorporate sensors and software analytics into their offerings, the same innovation has also brought pressure to offer clients more accommodating appliance deployment options. So, their needs a well plan to implement the cyber infrastructures and equipment. The cyber security play important role to ensure that the ICT components or infrastructures execute well along the organization’s business successful. This paper will present a study of security management models to guideline the security maintenance on existing cyber infrastructures. In order to perform security model for the currently existing cyber infrastructures, combination of the some security workforces and security process of extracting the security maintenance in cyber infrastructures. In the assessment, the focused on the cyber security maintenance within security models in cyber infrastructures and presented a way for the theoretical and practical analysis based on the selected security management models. Then, the proposed model does evaluation for the analysis which can be used to obtain insights into the configuration and to specify desired and undesired configurations. The implemented cyber security maintenance within security management model in a prototype and evaluated it for practical and theoretical scenarios. Furthermore, a framework model is presented which allows the evaluation of configuration changes in the agile and dynamic cyber infrastructure environments with regard to properties like vulnerabilities or expected availability. In case of a security perspective, this evaluation can be used to monitor the security levels of the configuration over its lifetime and to indicate degradations.

Cyberhubs: Virtual Research Environments for Astronomy

Abstract Collaborations in astronomy and astrophysics are faced with numerous cyber-infrastructure challenges, such as large data sets, the need to combine heterogeneous data sets, and the challenge to effectively collaborate on those large, heterogeneous data sets with significant processing requirements and complex science software tools. The cyberhubs system is an easy-to-deploy package for small- to medium-sized collaborations based on the Jupyter and Docker technology, which allows web-browser-enabled, remote, interactive analytic access to shared data. It offers an initial step to address these challenges. The features and deployment steps of the system are described, as well as the requirements collection through an account of the different approaches to data structuring, handling, and available analytic tools for the NuGrid and PPMstar collaborations. NuGrid is an international collaboration that creates stellar evolution and explosion physics and nucleosynthesis simulation data. The PPMstar collaboration performs large-scale 3D stellar hydrodynamics simulations of interior convection in the late phases of stellar evolution. Examples of science that is currently performed on cyberhubs, in the areas of 3D stellar hydrodynamic simulations, stellar evolution and nucleosynthesis, and Galactic chemical evolution, are presented.

On the Approach Considering Scientific IT-Service as a Base Unit for Cyberinfrastructure of Science

On the Approach Considering Scientific IT-Service as a Base Unit for Cyberinfrastructure of Science

Consideration of Cyber-Physical Interdependencies in Reliability Modeling of Smart Grids

A smart grid is a cyber-physical system designed to achieve sustainability by facilitating the use of renewable energy sources, without compromising the reliability of power distribution and transmission. The research presented in this paper seeks to facilitate analysis of the reliability achieved by smart grids. To this end, we present an analytical reliability model that captures the effect of impairments originating from both physical and cyber components, as well as the effect of cyber-physical interdependencies among these components. The model can be instantiated with failure data from field use or simulation. We categorize and quantify dependencies in the smart grid and analyze the impact on reliability of introducing additional interdependencies. Finally, we present a case study that investigates the effect of physical and cyber improvements on overall reliability of the smart grid, and demonstrate that flawed cyber infrastructure can result in reliability lower than that of a conventional power grid with less advanced control.

Towards an e-infrastructure for Open Science in Agriculture & Food

Towards an e-infrastructure for Open Science in Agriculture & Food

Evaluating spatial service and layout efficiency of municipal Wi-Fi facilities for SmartCity planning: A case study of Wuhan city, China

This paper explores an approach to evaluating spatial service and layout efficiency of municipal Wi-Fi facilities for cyber infrastructure planning in the construction of a smart city. Based on the equilibrium principle that Wi-Fi services supply should meet the spatial demand for recreation, urgency, and security, two evaluation models were built. In the first model, the spatial service efficiency of Wi-Fi facilities is measured by a mean ratio of three types of demand spaces covered by Wi-Fi service. In the other model, spatial layout efficiency of each Wi-Fi facility is calculated by a demand load indicator - the sum of the three types of demand space's ratios of served quantity to the average quantity it should carry, and then assessed by relationship with its adjacent facilities. Corresponding statistical methods and analysis processes were also designed using the function modules found in ArcGIS software. The approach was applied to Wuhan city in 2016. After overlaying influence areas of 688 Wi-Fi facilities with demand spaces of 137 access points for recreation, 1200.99 km roads for urgency, 121.54 km2 regions for security, the results show that there exists a spatial disequilibrium between supply and demand of Wi-Fi service in Wuhan due to lack of comprehensive planning. Specifically, there are 67 points, 700.76 km roads, and 42.59 km2 regions of demand spaces covered by Wi-Fi service, with service efficiencies of 48.91%, 58.35%, and 35.04% respectively and an overall spatial service efficiency of 47.43%. Among all the Wi-Fi facilities, there are 481 carrying saturated demand, 3 straying from the centre of demand space, and 204 redundant. The overall spatial layout efficiency of Wi-Fi facilities is 43.01%. The conclusion is that the dense and massive redundant Wi-Fi facilities should be optimized, especially in the centre areas along the confluence of Yangtze and Han rivers and new Wi-Fi facilities supplemented in other ill-equipped areas. Since many metropolitan cities experience the same problem, this novel approach will find wide application in the future and offer improved evaluation strategies for researchers and policymakers.