The Impact of Adaptive Learning in Principles of Microeconomics

Abstract The spread of Covid-19, which forced almost all learning to move to online in March, 2020, abruptly increased the number of undergraduates taking at least one online course by approximately 177% between the fall of 2019 and the spring of 2020 (Koksal, 2020; Carey, 2020; National Center for Education Statistics, 2020). Even without the Covid-19 disruption, online education has become increasing prevalent due to the decreasing allocation of resources to higher education and the pressure on college administrators to make a college education effective, affordable, and accessible for more students. Originally online instruction differed from in-class instruction only be the method of delivery of the material, viewing a lecture online versus being present in a live classroom lecture. Although there have been many studies on the effectiveness of traditional online instruction over the last several decades, there have been fewer studies on the efficacy of the relatively new adaptive learning courseware. This initial study found that adaptive learning had a consistently positive and statistically significant impact on all principle of microeconomics students in the study, regardless of aptitude, ethnicity, and gender. However, students with high aptitudes appeared to benefit more from adaptive learning than their peers

Location Privacy in VANETs: Provably Secure Anonymous Key Exchange Protocol Based on Self-Blindable Signatures

open access articleSecurity and privacy in vehicular ad hoc networks (VANETs) are challenging in terms of Intelligent Transportation Systems (ITS) features. The distribution and decentralisation of vehicles could threaten location privacy and confidentiality in the absence of trusted third parties (TTP)s or if they are otherwise compromised. If the same digital signatures (or the same certificates) are used for different communications, then adversaries could easily apply linking attacks. Unfortunately, most of the existing schemes for VANETs in the literature do not satisfy the required levels of security, location privacy, and efficiency simultaneously. This paper presents a new and efficient end-to-end anonymous key exchange protocol based on Yang et al. 's self-blindable signatures. In our protocol, vehicles first privately blind their own private certificates for each communication outside the mix-zone and then compute an anonymous shared key based on zero-knowledge proof of knowledge (PoK). The efficiency comes from the fact that once the signatures are verified, the ephemeral values in PoK are also used to compute a shared key through an authenticated Diffie-Hellman key exchange protocol. Therefore, the protocol does not require any further external information to generate a shared key. Our protocol also does not require an interference with the Roadside Units or Certificate Authorities, and hence can be securely run outside the mixed-zones. We demonstrate the security of our protocol in an ideal/real simulation paradigm. Hence, our protocol achieves secure authentication, forward unlinkability, and accountability. Furthermore, the performance analysis shows that our protocol is more efficient in terms of computational and communication overheads compared to existing schemes

Formal model and policy specification of usage control

The recent usage control model (UCON) is a foundation for next-generation access control models with distinguishing properties of decision continuity and attribute mutability. A usage control decision is determined by combining authorizations, obligations, and conditions, presented as UCON ABC core models by Park and Sandhu. Based on these core aspects, we develop a formal model and logical specification of UCON with an extension of Lamport's temporal logic of actions (TLA). The building blocks of this model include: (1) a set of sequences of system states based on the attributes of subjects, objects, and the system, (2) authorization predicates based on subject and object attributes, (3) usage control actions to update attributes and accessing status of a usage process, (4) obligation actions, and (5) condition predicates based on system attributes. A usage control policy is defined as a set of temporal logic formulas that are satisfied as the system state changes. A fixed set of scheme rules is defined to specify general UCON policies with the properties of soundness and completeness. We show the flexibility and expressive capability of this formal model by specifying the core models of UCON and some applications. © 2005 ACM

IaaS-cloud security enhancement: an intelligent attribute-based access control model and implementation

The cloud computing paradigm introduces an efficient utilisation of huge computing resources by multiple users with minimal expense and deployment effort compared to traditional computing facilities. Although cloud computing has incredible benefits, some governments and enterprises remain hesitant to transfer their computing technology to the cloud as a consequence of the associated security challenges. Security is, therefore, a significant factor in cloud computing adoption. Cloud services consist of three layers: Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS). Cloud computing services are accessed through network connections and utilised by multi-users who can share the resources through virtualisation technology. Accordingly, an efficient access control system is crucial to prevent unauthorised access. This thesis mainly investigates the IaaS security enhancement from an access control point of view. [Continues.

Network slice allocation for 5G V2X networks: A case study from framework to implementation and performance assessment

Empowered by the capabilities provided by fifth generation (5G) mobile communication systems, vehicle-to-everything (V2X) communication is heading from concept to reality. Given the nature of high-mobility and high-density for vehicle transportation, how to satisfy the stringent and divergent requirements for V2X communications such as ultra-low latency and ultra-high reliable connectivity appears as an unprecedented challenging task for network operators. As an enabler to tackle this problem, network slicing provides a power tool for supporting V2X communications over 5G networks. In this paper, we propose a network resource allocation framework which deals with slice allocation considering the coexistence of V2X communications with multiple other types of services. The framework is implemented in Python and we evaluate the performance of our framework based on real-life network deployment datasets from a 5G operator. Through extensive simulations, we explore the benefits brought by network slicing in terms of achieved data rates for V2X, blocking probability, and handover ratio through different combinations of traffic types. We also reveal the importance of proper resource splitting for slicing among V2X and other types of services when network traffic load in an area of interest and quality of service of end users are taken into account.publishedVersionPaid open acces

Semantic-Based Access Control Mechanisms in Dynamic Environments

The appearance of dynamic distributed networks in early eighties of the last century has evoked technologies like pervasive systems, ubiquitous computing, ambient intelligence, and more recently, Internet of Things (IoT) to be developed. Moreover, sensing capabil- ities embedded in computing devices offer users the ability to share, retrieve, and update resources on anytime and anywhere basis. These resources (or data) constitute what is widely known as contextual information. In these systems, there is an association between a system and its environment and the system should always adapt to its ever-changing environment. This situation makes the Context-Based Access Control (CBAC) the method of choice for such environments. However, most traditional policy models do not address the issue of dynamic nature of dynamic distributed systems and are limited in addressing issues like adaptability, extensibility, and reasoning over security policies. We propose a security framework for dynamic distributed network domain that is based on semantic technologies. This framework presents a flexible and adaptable context-based access control authoriza- tion model for protecting dynamic distributed networks’ resources. We extend our secu- rity model to incorporate context delegation in context-based access control environments. We show that security mechanisms provided by the framework are sound and adhere to the least-privilege principle. We develop a prototype implementation of our framework and present the results to show that our framework correctly derives Context-Based au- thorization decision. Furthermore, we provide complexity analysis for the authorization framework in its response to the requests and contrast the complexity against possible op- timization that can be applied on the framework. Finally, we incorporate semantic-based obligation into our security framework. In phase I of our research, we design two lightweight Web Ontology Language (OWL) ontologies CTX-Lite and CBAC. CTX-Lite ontology serves as a core ontology for context handling, while CBAC ontology is used for modeling access control policy requirements. Based on the two OWL ontologies, we develop access authorization approach in which access decision is solely made based on the context of the request. We separate context operations from access authorization operations to reduce processing time for distributed networks’ devices. In phase II, we present two novel ontology-based context delegation ap- proaches. Monotonic context delegation, which adopts GRANT version of delegation, and non-monotonic for TRANSFER version of delegation. Our goal is to present context del- egation mechanisms that can be adopted by existing CBAC systems which do not provide delegation services. Phase III has two sub-phases, the first is to provide complexity anal- ysis of the authorization framework. The second sub-phase is dedicated to incorporating semantic-based obligation

The Abstract Accountability Language: its Syntax, Semantics and Tools

Accountability is the driving principle for several of regulatory frameworks such as the European Union's General Data Protection Regulation (EU GDPR), the Health Insurance Portability and Accountability Act (HIPAA) and the Corporate and Auditing Accountability and Responsibility Act, thus influencing how organizations run their business processes. It is a central concept for enabling trust and assurance in cloud computing and future internet-based services that may emerge. Nevertheless, accountability can have different interpretations according to the level abstraction. This leads to uncertainty concerning handling and responsibility for data in computer systems with outsourcing supply-chains, as in cloud computing. When defining policies to govern organizations, we need tools to model accountability in rich contexts, including concepts like multiple agents, obligations, remediation actions and temporal aspects. The Abstract Accountability Language (AAL) is built on logical foundations allowing to describe real-world scenarios involving accountability concerns. Its semantic principles provide us means to answer whether the conditions to reach accountability in a given context are met. Moreover, we created a tool support to verify and monitor accountability policies

Foundations of secure computation

Issued as Workshop proceedings and Final report, Project no. G-36-61

Agile gravitational search algorithm for cyber-physical path-loss modelling in 5G connected autonomous vehicular network

Based on the characteristics of the 5 G standard defined in Release 17 by 3GPP and that of the emerging Beyond 5 G (or the so-called 6 G) network, cyber-physical systems (CPSs) used in smart transport network infrastructures, such as connected autonomous vehicles (CAV), will significantly depend on the cellular networks. The 5 G and Beyond 5 G (or 6 G) will operate over millimetre-wave (mmWave) bands. These network standards require suitable path loss (PL) models to guarantee effective communication over the network standards of CAV. The existing PL models suffer heavy signal losses and interferences at mmWave bands and may not be suitable for cyber-physical (CP) signal propagation. This paper develops an Agile Gravitational Search Algorithm (AGSA) that mitigates the PL and signal interference problems in the 5G–NR network for CAV. On top of that, a modified Okumura-Hata model (OHM) suitable for deployment in CP terrestrial mobile networks is derived for the CAV-CPS application. These models are tested on the real-world 5 G infrastructure. Results from the simulated models are compared with measured data for the modified, enhanced model and four other existing models. The comparative evaluation shows that the modified OHM and AGSA performed better than existing OHM, COST, and ECC-33 models by 90%. Also, the modified OHM demonstrated reduced signal interference compared to the existing models. In terms of optimisation validation, the AGSA scheme outperforms the Genetic algorithm, Particle Swarm Optimisation, and OHM models by at least 57.43%. On top of that, the enhanced AGSA outperformed existing PL (i.e., Okumura, Egli, Ericson 999, and ECC-33 models) by at least 67%, thus presenting the potential for efficient service provisioning in 5G-NR driverless car applications