Third-party Providers Research Articles

ADAPT: Attack detection and prevention via deep learning techniques

Cloud computing is a new technology that provides services to customers anywhere, anytime, under varying conditions and managed by a third-party cloud provider. Even though cloud computing has progressed a lot, some attacks still happen. The recent anomalous and signature attacks use clever strategies such as low-rate attacks and attacking as an authenticated user. In this paper, a novel Attack Detection and Prevention (ADAPT) method is proposed to overcome this issue. The proposed system consists of three stages. An Intrusion Detection System is initially used to check whether there is an attack or not by comparing the IP address in the Blacklist IP Database. If an attack occurs, the IP address will be added to the Blacklist IP database and blocked. The second stage uses Bi-directional LSTM and Bi-directional GRU to check the anomalous and signature attack. In the third stage, classified output is sent to reinforcement learning, if any attack occurs the IP address is added to the blacklist IP database otherwise the packets are forwarded to the user. The proposed ADAPT technique achieves a higher accuracy range than existing techniques.

Harmonizing open banking in the European Union: an analysis of PSD2 compliance and interrelation with cybersecurity frameworks and standards

AbstractThis paper focuses on the security protocols enacted in banking transactions across the European Economic Area (EEA), as stipulated by the Second or Revised Payment Service Directive (commonly referred to as ‘PSD2’ or simply ‘the Directive’). The study aims to comprehensively analyse the implementation and efficacy of these security measures within the specified jurisdiction. The Directive incorporates fundamental rights and obligations that all stakeholders are compelled to adhere to and delineates specific security measures and standards that both traditional banking institutions and third-party providers (TPP) are mandated to implement. In particular, one of the cardinal mandates for banking and financial institutions under PSD2 is the obligation to facilitate third-party access to customer data via open application programming interfaces (API). While this open banking paradigm and the consequent proliferation of data sharing unquestionably bring about various advantages, such as enhanced consumer choice and market competition, they concurrently expose the financial ecosystem to a slew of potential security vulnerabilities and privacy risks. Upon conducting a comprehensive review of the security requirements and measures stipulated under PSD2 and a comparative analysis with essential cybersecurity frameworks and standards (NIS2, Cybersecurity Act, GDPR, ISO 27001:22 and PCI DSS), we have ascertained a discernible lack of harmonisation and clarity concerning the technical security specifications for its effective implementation. This lacuna substantiates the challenges banks face in fully grasping the extensive spectrum of compliance obligations mandated by PSD2. The aim of this research is to offer a valuable contribution to both the comprehension and the pragmatic deployment of security standards in the context of banking transactions, as regulated by the PSD2. The paper serves as a valuable resource for traditional banking institutions and relevant stakeholders by guiding them through the complexities of PSD2 implementation while also evaluating the effects of the security measures on transactional safeguards, data security, and the provision of payment services.

A model of digital rights management with user disutility

We develop a model in which software developers react to anticipated digital piracy either by undercutting piracy or by acquiring digital rights management (DRM) technology from a third-party DRM provider. DRM delays pirated copies to an uncertain future time, incentivizing impatient consumers to purchase a legitimate copy immediately. DRM, however, is a source of disutility for users. The somewhat counter-intuitive key results are that developers increase expected profit by credibly agreeing upon release to remove DRM from legitimate copies once DRM has been cracked, but it is not necessarily true that the eventual removal of DRM increases expected buyer welfare relative to indefinitely retained DRM.

Beaf:BD – A Blockchain Enabled Authentication Framework for Big Data

The widespread utilization of Internet-based applications in our daily routines has resulted in enormous amounts of data being generated every minute. This data is not only produced by humans but also by various machines such as sensors, satellites, CCTV, etc. For many organizations, Apache Hadoop is the solution for handling big data. Big data refers to the extensive set of dissimilar data that can be processed to derive meaningful insights. For its security needs, Hadoop relies on trusted third-party security providers such as Kerberos. Kerberos has several security vulnerabilities. The focus of this paper is to eliminate security issues, particularly dictionary attacks and single points of failure, by proposing a model based on blockchain technology and threshold cryptography.In comparison to other existing schemes, the proposed approach offers superior computational overhead and storage requirements while maintaining the system's security level.

“I Feel Like a Sex Ed Wizard Now”

The discourse around sex education is ambivalent and normatively loaded, stretching roughly between conservatism, liberalism, and neo-emancipation. In Germany, teachers receive no specific training and have little access to education, besides short and optional training from third-party providers. As a result, they feel left alone, overburdened, and politically at risk while simultaneously reporting a personal desire to make a positive change. Teach Love is a psychological knowledge transfer project applying critical community psychology to teachers’ continuing education on sex education. The participants receive emotion-, value-based, and pluralistic digital training based on empirically assessed needs and in collaboration with scientists (psychology, pedagogy, sociology) and practitioners (therapists, teachers, midwives) focusing on comprehensive competence. In this contribution, I present the empirically assessed teacher's needs on sex education and the resultant didactic. Second, I present the empirical post-measure evaluations to discuss the potential of applied critical community psychology in teachers' professionalisation. This contribution serves in three ways. Firstly, the paper presents a practically tested approach to how to deal constructively with polarizing topics in pedagogy. Secondly, the results show how to support teachers by applying critical community psychology in the teacher's professional development. Finally, insights into digital education formats, their applicability, effectiveness, and acceptability are gained.

Achieving a Decentralized and Secure Cab Sharing System Using Blockchain Technology

The cab-sharing system provides a platform for drivers and riders with shared trip services, providing significant benefits, such as decreasing traffic congestion, reducing travel costs, and limiting energy consumption, which improve the business of transportation. However, existing cab-sharing systems mainly depend on the centralized authority to provide many services, increasing privacy concerns and facing the single point of failure issue. Also, these systems expose drivers’ or riders’ locations and personal information that increase security issues, and charge high fees for services due to the involvement of third-party providers. Therefore, this paper proposes a decentralized and secure cab-sharing system to provide ride-sharing services using blockchain technology without any trusted third party. The proposed system uses the blockchain structure to preserve the driver’s or rider’s information, such as personal details, travel price, pickup or drop-off locations, departure or arrival date, and time. Furthermore, it implements the reputation feature to rate drivers and riders based on their travel history or behaviors without any centralized authority that allows users to select them based on their past experiences on the system. The proposed architecture is deployed using the Ethereum platform and functionality is designed using smart contracts. The performance evaluation and experimental results show that the proposed system requires low computational overheads and provides an efficient cab-sharing platform.

Between the Lines: An Exploration of Online Academic Help-Seeking and Outsourced Support in Higher Education: Who Seeks Help and Why?

The growth in online higher education has seen the ‘unbundling’ of some services as universities have partnered with private companies in an effort to enhance their services. This paper explores university students’ use and perceptions of the third-party online learning support platform, Studiosity, at Dublin City University. Studiosity was engaged to support undergraduate and postgraduate distance students, by offering support beyond existing campus-based services. This research employs a primarily inductive research design drawing on data collected through the third-party provider (2018–2020), supplemented by an in-house online survey (2019). Students were overwhelmingly positive about Studiosity. Postgraduate students, arguably students with good academic skills, used the service more than first-year undergraduate students. However, first-year undergraduates, a group the literature suggests are reluctant users of institutional support, were also strong users. Questions emanating from postgraduate students demonstrated expedient help-seeking. First-year undergraduate students were more concerned with explanations to help their understanding in order to persist with their studies. This paper posits that all other things being equal, those who already have strong academic capital will be the greatest users of academic support services. Proactive, less formal academic support strategies to encourage use by those who need help most, remain critical.

Survey on Decentralized Democracy: Blockchain Voting System

Voting is a fundamental pillar of democracy, but traditional voting systems face numerous challenges, including concerns related to security, transparency, and accessibility. In recent years, blockchain technology has emerged as a promising solution to revolutionize the voting process. By leveraging the inherent characteristics of blockchain technology, a blockchain-based voting system can enhance the integrity and trustworthiness of the voting process. Blockchain-based voting systems offer several key features and benefits. One of the main advantages is the security and immutability of voter data, which makes it virtually impossible to tamper with or manipulate. Each vote is recorded as a transaction on the blockchain, creating a transparent and auditable ledger that can be accessed by all stakeholders. This eliminates the need for intermediaries such as government agencies or third-party voting providers, reducing the risk of interference and tampering. Another advantage of blockchain-based voting systems is increased accessibility. Remote and mobile voting can help improve voter turnout and participation, especially for individuals who may have difficulty accessing traditional polling stations. Moreover, blockchain technology can maintain the anonymity of voters while ensuring the verifiability of their choices, which guarantees the privacy of their decisions. Despite these benefits, challenges persist, including concerns about identity verification and cybersecurity. Addressing these issues is crucial for the widespread adoption of blockchain-based voting systems. In conclusion, a blockchain-based voting system has the potential to transform the way elections are conducted by providing a secure, efficient, and transparent platform that empowers citizens and strengthens the democratic process. As the technology continues to evolve, it is essential to address its limitations while harnessing its advantages to build a more robust and inclusive electoral system. Keywords: Blockchain, voting, election, decentralized, secure, transparency, immutability, privacy.

Childcare Assistance Not a Major Draw for Most Employees

Employer-provided childcare accommodations by either in-house facilities or subsidies paid to third-party providers can be an expensive employee benefit and may not be considered the most desired accommodation an employer can offer. Changes in employee attitudes toward family and work balance may be a factor. Providing the benefit can cause related financial exposure and lead to resentment from employees who don’t need or want it. Alternative family accommodation of paid leave and flexible scheduling appear more popular. Employers should carefully survey employee attitudes toward the benefit, assess employee composition to determine need and consider alternative accommodations that may be a better fit.

Управление природно-социально-производственными системами на основе концепции интернета вещей: геопортальный подход

The authors describe the research in development of problem-oriented geoportal systems based on the concept of the Internet of things which enable solving the tasks of managing natural-social-production systems. The main purpose of the implemented automation solutions is to provide the decision maker with a tool for monitoring and remote control of IoT agents operating within the territorial framework. The solution to the problem of visualization and dissemination of spatial data on regional metageosystems can be achieved through the introduction and effective use of geoportal ones developed on the basis of web technologies and providing access to the spatial data infrastructure of organizations and regions through interactive digital maps. We propose the developed structure of a metageosystem management scheme based on the technology of the Internet of things and geoportal systems, based on the use of the LoRaWAN long-range wireless communication standard. The basis of such a network is represented by IoT devices consolidated around the head ones (gateways) and developed on the basis of a modular principle to achieve high rates of modifiability and extensibility. Gathering telemetric indicators and transferring control commands within the LoRaWAN network are carried out without involvement of third-party communication providers, which greatly reduces the expense of operating economic management systems, bringing the cost of data exchange to the lowest possible rate. It is proved that in the case of the use of geoinformation web systems in conjunction with the technology of the Internet of things, geoportals would play the role of dispatching centers along with their classic function of interactive visualization of spatial data

The politics of government intervention in the HE market: Andrew McGettigan talks to Kirsten Forkert

The last twenty to thirty years have seen a big push to create a market in higher education, but there have been frequent interventions by governments both to sustain the 'market' and to alter its operation for policy reasons. The sector has massively expanded since the 1990s because of a cross-party consensus that the country needed more skills - though this view is now less popular; however, there still seems to be consensus that higher education should be substantially funded by (capped) domestic student fees (the price of a degree for international students is largely unregulated). A big subprime market has developed in Higher Education; and there has also been an increase in third-party private providers: much recent regulation is necessitated by adapting the system to these providers. The market is frequently set aside when it comes up against the establishment privilege of Oxbridge and the Russell Group. And tweaks to the market made since 2010 have largely been designed to steer more resources to already privileged institutions. For example the recent announcements about capping foundation year fees, and limiting dependant visas for international students, will have a greater adverse effect on non-elite institutions because of the kind of recruitment they're involved in, and the kind of offer they make to students. The same logic applies to removing the cap on recruitment to elite universities, and the reduction of funding for Foundation Years. The 2023 announcement that the government wished the regulator, OfS, to make more use of its powers to restrict funding for 'low-value' courses was accompanied by culture wars rhetoric, but should be understood as an attempt to limit university autonomy, even while it also addresses concerns around the 'new providers' that have been allowed to access government-backed loans since 2010.

DB-COVIDNet: A Defense Method against Backdoor Attacks

With the emergence of COVID-19 disease in 2019, machine learning (ML) techniques, specifically deep learning networks (DNNs), played a key role in diagnosing the disease in the medical industry due to their superior performance. However, the computational cost of deep learning networks (DNNs) can be quite high, making it necessary to often outsource the training process to third-party providers, such as machine learning as a service (MLaaS). Therefore, careful consideration is required to achieve robustness in DNN-based systems against cyber-security attacks. In this paper, we propose a method called the dropout-bagging (DB-COVIDNet) algorithm, which works as a robust defense mechanism against poisoning backdoor attacks. In this model, the trigger-related features will be removed by the modified dropout algorithm, and then we will use the new voting method in the bagging algorithm to achieve the final results. We considered AC-COVIDNet as the main inducer of the bagging algorithm, which is an attention-guided contrastive convolutional neural network (CNN), and evaluated the performance of the proposed method with the malicious COVIDx dataset. The results demonstrated that DB-COVIDNet has strong robustness and can significantly reduce the effect of the backdoor attack. The proposed DB-COVIDNet nullifies backdoors before the attack has been activated, resulting in a tremendous reduction in the attack success rate from 99.5% to 3% with high accuracy on the clean data.

Trickle-Down Burdens: The Effect of Provider Burdens on Clients’ Experience

Abstract Administrative burden research disproportionately examines micro-level burdens on clients claiming benefits from public agencies. Yet we know little about meso-level burdens on third-party providers making up the submerged state—private actors working on behalf of a public purpose—and what effect these burdens have on services. We draw on interviews, participant observation, and focus groups with substance-use disorder service providers to map provider burdens and how they affect services that third parties offer. We supplement the provider perspective with data from clients and their families about their experience with services. We find that providers face significant administrative burdens resulting from federal and state policy; that these burdens affect the quality of the services they are able to offer; and, ultimately, that burdens on providers can trickle down to become burdens on clients. Our research has implications for how we understand administrative burdens, the solutions best suited to reducing them, and the role of burdens as a form of hidden politics in the submerged state.

THEORETICAL AND METHODOLOGICAL APPROACHES TO IT INFRASTRUCTURE MANAGEMENT IN CONDITIONS OF DIGITALIZATION

The article proves that the formation and support of IT infrastructure developing is a key strategic factor in the effective functioning of enterprises and organizations. There are the interpretations of the concepts ‘IT infrastructure’, ‘information infrastructure’, ‘technological infrastructure’ and ‘supporting infrastructure’. It has been found that the IT infrastructure needs constant support and updating to ensure the safety and reliability of data, devices, IT services, tools, technological processes, information, and communication technologies. The components of the organization’s IT infrastructure that meet the needs and business development plan are given. It has been established that IT infrastructure components can be deployed, organized and implemented in various ways. The main tasks of the IT infrastructure and its purpose are also given. The article provides the information that the modern version of the organization’s IT infrastructure is cloud infrastructure, which is quite effective for small and medium-sized businesses with a limited budget. It was found out the virtualization of the IT infrastructure of the enterprise is provided by the virtualization of servers, applications, workstations, the use of cloud computing, optimization of the information network, interaction on demand. The areas of management that have developed from the need to maximize the value created by IT assets are characterized: ITOM, ITSM and ITAM. Important to know the role of the IT infrastructure management system because it is manifested in the proactive administration and management of technological tools, in particular: monitoring of errors and problems; patch tracking; tracing all errors back to their original sources. Moreover, it has been established that the role of IT infrastructure security is becoming more complicated as business entities move to cloud models, hybrid models, multi-cloud technologies, etc. Finally, the model of providing cloud services, with the help of which IT organizations can purchase virtualized computing resources from a third-party provider and access them via the Internet, is called infrastructure services (IaaS).

Machine Learning Helps Customize Spacing for Maximum Acreage Value

_ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper URTeC 3723023, “Using Machine Learning To Customize Development Unit Spacing for Maximum Acreage Value,” by M. Maguire, SPE, Diamondback Energy; A. Cui, Novi Labs; and T.E. Witham, Diamondback Energy, et al. The paper has not been peer reviewed. _ In the complete paper, machine-learning (ML) models were trained using geologic, completion, and spacing parameters to predict production across the primary developed formations in the Midland Basin. The approach of using ML to test several different combinations of spacing and completion designs can be repeated across a basin to find an economical, customized solution for each development unit. Introduction In contrast to conventional methods, ML offers a data-driven approach that can leverage the large amount of data generated by operators within unconventional plays. Several characteristics of ML models make them well-suited for spacing optimization, including the following: - ML models rely on statistical methods to establish relationships between the input variables and the output variables. - ML handles nonlinear relationships well. - Complex variable interactions can be difficult to understand with traditional methods. The downside is the time required to assemble the input data used for training an ML model. However, once a model is built that has an acceptable level of error along with data examples covering the range of cases to be evaluated, many alternative development scenarios can be quickly evaluated. In addition, with the right variables (features) included, a model could be applicable to an area much larger than that of pilot wells. ML Methods Each ML model used production data (monthly or daily format), directional survey data (to locate the wells and allow for spacing calculations), a header table with a variety of information on all the wells (i.e., completion information, formation, and completed lateral length), and grid data (typically geology data, such as effective porosity). For all models, private data, such as daily production data and detailed completion data, had precedence over data acquired from public sources or a third-party data provider. For a well to be included in the ML model, it generally had to have all data values populated; wells with missing data were excluded. Once the data were gathered, the derivative variables were calculated, along with several spacing parameters. For ML studies of unconventional developments, practitioners face two main subsurface questions: how to subdivide the formations to represent the drainage heights and which rock properties to pass to the model. Drainage heights defined by the operator are based on the geochemical typing data. These heights generally extended further than traditionally defined formations (Fig. 1). Because these drainage boundaries are defined by the true vertical depth (TVD) positions of specific formational tops, the total vertical extent of these drainage heights mirrors the geospatial variation in the TVD positions of their boundary tops. To generate the grids, geologic attributes were calculated from well logs. Log processing began after drainage heights were determined across the Midland Basin. Attributes with high correlation were selectively removed from the model inputs.

ENRICHING LARGE DOCUMENT STORES WITH INTELLIGENT METADATA: A FRAMEWORK FOR EFFECTIVE KNOWLEDGE MANAGEMENT AND APPLIED ANALYTICS

The current paper focuses on a framework for structuring large document stores with the help of intelligent metadata. The described landscape includes a proprietary knowledge graph which ingests millions of concepts from external, third-party data providers and accommodates internal class taxonomies; an NLP service for automated annotation of textual data; an annotations quality control mechanism; tools for knowledge graph ontology and concept management; and an extensive API layer. The authors present an approach they have tested and proved successful in one of the leading media companies in the world, whose media content is a core data asset. The proposed solutions enable content analytics in their proper context and allow explicit and implicit connections between the content and other company data – i.e., user (media content consumer) data. The latter empowers the efficient application of advanced analytical models for searches and recommendations and the implementation of accurate data-driven virtual assistants. The paper advises addressing the metadata quality concerns, which the authors’ extensive practice identifies as an essential prerequisite for applied analytics delivering significant business value.

Technical Restrictions for Third-Party Providers in Aftermarkets Under the Lens of Competition Law

RICOH Toner Cartridge II

3C Resource Sharing for Personalized Content Delivery in B5G Networks: A Contract Approach

With the emergence of numerous new applications and the explosive growth of Internet-of-Things (IoT) devices in beyond 5G (B5G) networks, the massive yet delay-sensitive personalized content delivery has imposed a crucial challenge to mobile network operators (MNOs). Cooperation among MNOs for sharing the communication, caching, and computing (3C) three-dimensional resources in an economic yet real-time manner has provided a promising solution to address this challenge. In this paper, we investigate the 3C resource sharing among multiple MNOs to realize efficiently and economically personalized content delivery, where a third-party 3C resource provider (CRP) is introduced to manage the sharing 3C resource pool. By leveraging the multi-dimensional contract theory, we propose an optimal 3C resource contract scheme for the CRP in a realistic asymmetric information scenario, and the appointed 3C resources in one contract will be allocated to the MNO who signs it. For each MNO, we establish a partial transcoding model to achieve the optimal orchestration on the 3C resources, where the closed-form solution of caching placement and transcoding strategy is obtained. Then, MNOs can choose the most suitable contracts to sign based on the service requirements from end users. In particular, we analyze the global incentive compatibility and feasibility of the proposed multi-dimensional contract approach, which is theoretically proven to achieve the optimal solution. Extensive simulation results demonstrate the efficiency of the proposed 3C resource sharing mechanism compared with other benchmark schemes. Specifically, the proposed 3C resource sharing scheme can reduce 35% delivery delay compared with the non-sharing scheme.

Quality assuring an outsourced ambulatory electrocardiogram pathway

Abstract Funding Acknowledgements Type of funding sources: None. Introduction The rising demand for arrhythmia care has led to the use of outsourced ambulatory electrocardiogram (ECG) pathways to maintain timely service delivery and meet diagnostic targets. Since COVID-19, our ambulatory ECG service operates primarily through external third-party providers, using the remote (postal) model, where monitors are dispatched to patients for self-application. This pathway was activated to comply with social distancing restrictions and has now been integrated into our diagnostic model of care. A quality assurance (QA) process was introduced to ensure compliance with our internal ECG reporting practice and escalation protocols. Purpose To quality assure our outsourced ambulatory ECG reports and pathways against internal practices and protocols. Methods We audited our QA records on outsourced services from 1st January 2022 - 31st December 2022. During this period, a total of 4317 patients were provided with an ambulatory ECG monitor via the remote service. We conducted regular (~every 2-3 months) retrospective random sampling of ambulatory ECG reports (~10%) for inclusion in QA. Our QA framework consists of a series of quality and consistency checks related to clinical information, report content, and adherence to escalation protocols (table 1). QA reports are fed back to our providers at quarterly meetings to ensure improved service quality. To obtain the requisite data, a variety of sources were cross-referenced. These included our QA reports, outsourced databases, third-party provider platforms, and our patient information system. Results Over a 12-month period, a total of 459 reports were quality assured. Ambulatory ECG reports were checked for clinical information, report content, supporting ECG evidence and amendment requests (table 1). A compliance rate of 99% was achieved. There were few cases (1%) where a request was made to the provider to amend the report or include additional information, namely ECG strips to clarify the findings. We also quality checked compliance to our escalation protocols: appropriate RAG (red, amber, green) rating and action, timely notification to clinicians, and adequate documentation. The reviewed ambulatory ECG reports were RAG rated as: Red 23 (5%), Amber 189 (40%), Green-Amber 142 (30%), Green 117 (25%). These were carried out with 99% accuracy. Activation of the appropriate escalation protocols and timely clinician notification achieved 100% compliance, including 23 red-flagged reports requiring immediate action. Conclusion The outsourced ambulatory ECG pathway had a very high rate of compliance with internal ECG reporting practice and escalation protocols. Our QA framework ensures we work in collaboration with our external partners to continually provide high-quality ECG diagnostics. We believe undertaking internal quality checks is a vital part of using outsourced service providers.

Understanding domestic consumer attitude and behaviour towards energy: A study on the Island of Ireland

Attitudes towards renewable technologies and knowledge about energy consumption influences the adoption of sustainable energy systems across power, heat and transport. Research suggests that behavioural change strategies could accelerate the transition towards net-zero by reducing household energy consumption, increasing the uptake of energy efficient technologies and optimising consumption patterns. In tandem, emerging markets and business models facilitated by energy decentralisation and digitalisation give consumers more control over their home energy management and adopt more energy efficient behaviours. This empirical study seeks to determine the level of awareness of domestic consumers on the island of Ireland, which makes for an interesting case study due to the existence of a single electricity market with a dichotomic regulatory regime. This survey is critical to engineers, industry and other stakeholders in understanding the implications of climate policy aspirations and targets as society transitions towards carbon neutrality. A questionnaire was issued to a sample of 1,373 respondents in March 2022, facilitated by a third-party survey provider. The questionnaire had 40 questions composed of multiple-choice and single-answer format; questions covered participants’ sociodemographic attributes, their willingness to adopt new technologies and services and their eco-credentials. The results identify the strengths, weaknesses and opportunities for householders to adopt more efficient household energy behaviours and attitudes towards smart energy technology and their carbon footprint. This study explores the emerging, yet significant role of domestic consumers in an equitable transition to a sustainable future.