Intrusion detection attack patterns in cloud computing: trust and risk assessment

Dependence on cloud services has been steadily increasing in recent years, as cloud services are an attractive option to offer flexibility and cost effectiveness through economies of scale. Cloud services are also exposed to security incidents, such as data breaches and other malicious activities. To mitigate risks to the confidentiality, integrity, and availability of assets, but also minimise loss to cloud service providers and users, the attack trust and risk elements need to be identified, classified, and prioritised. The aim of the proposed conceptual framework is to combine trust and risk assessment sources with data of risk assessment related to each attack pattern. This novel approach is a new qualitative solution to examine and determine symptoms, indicators, and vulnerabilities to detect the impact and likelihood of distributed attacks directed at cloud computing environments. The proposed framework might help to reduce false positive alarms and improve performance in Intrusion Detection Systems

A predictive model for risk and trust assessment in cloud computing: taxonomy and analysis for attack pattern detection

Cloud computing environments consist of many entities that have different roles, such as provider and customer, and multiple interactions amongst them. Trust is an essential element to develop confidence-based relationships amongst the various components in such a diverse environment. The current chapter presents the taxonomy of trust models and classification of information sources for trust assessment. Furthermore, it presents the taxonomy of risk factors in cloud computing environment. It analyses further the existing approaches and portrays the potential of enhancing trust development by merging trust assessment and risk assessment methodologies. The aim of the proposed solution is to combine information sources collected from various trust and risk assessment systems deployed in cloud services, with data related to attack patterns. Specifically, the approach suggests a new qualitative solution that could analyse each symptom, indicator, and vulnerability in order to detect the impact and likelihood of attacks directed at cloud computing environments. Therefore, possible implementation of the proposed framework might help to minimise false positive alarms, as well as to improve performance and security, in the cloud computing environment

Mapping behavioural – related retention factors using a learning community lens: A mixed methods approach.

This study investigated the experiences of undergraduate learning communities in a UK Higher Education Institution and the causes that may lead to low retention rates amongst first year undergraduate computing students. Using learning communities as a lens, the author examined students’ perception of teamwork experiences, academic and social integration issues, and knowledge and characteristics that might help students to be successful. Four research questions guided the current study: (1) How do first year undergraduate computing students perceive their university experience? (2) To what depth and breadth does learning community participation affect social and/or academic integration? (3) What are the identified barriers/limitations to improve retention? (4) What learning characteristics or knowledge do students maintain and how are they accomplished? The study applied a mixture of quantitative and qualitative research methods using a concurrent triangulation. Firstly, a quantitative data analysis was performed including first year undergraduate students from various departments of the examined UK Higher Education Institution. Tinto’s model of student retention connects to behavioural patterns. Behavioural patterns were therefore identified using data collected from students in order to map factors as predictors for low student retention. The data collection was driven by the information collected when students enrol at the university, as well as Pascarella and Terenzini’s questionnaire (integration scales). The data was analysed using the Structural Equation Modelling (SEM) technique which offers the opportunity to test various theoretical models, such as Tinto’s, through understanding of how sets of variables characterise constructs, and in what ways these constructs are associated to one another. The quantitative data analysis results suggested that the theory of Tinto proved to be beneficial in analysing retention in first year undergraduate students. Not at its maximum potential, though, because the model variables accounted for only a modest amount of variance in retention. Nevertheless, the data analysis discovered important relationships amongst student’s initial and later academic goals and commitments. In particular, the results revealed that academic and social integration constructs can have a significant influence on student retention processes. It is recommended that when all or some of these relationships are operating towards students’ benefit, it may be necessary to promote them with appropriate services or programmes, such as student support systems. Secondly, after the quantitative approach was applied to the aforementioned large-scale comparative study within the institution, a qualitative approach was used to further explore student needs. Specifically, during the quantitative phase data from all first year students of the institution studied was collected in order to offer the opportunity for a comparison amongst students from different course divisions, and investigate any major similarities and/or differences regarding factors affecting retention. As this phase identified similar factors amongst all students, the qualitative phase was employed in order to narrow down the research focus. Therefore, the qualitative approach offered the opportunity for a thorough exploration of the first year computing students’ reasons for dropping out of university through the use of the ‘unfolding matrix’. The matrix was completed during group interviews, in which students were invited, and had the opportunity to read and comment on previous students’ experiences. The findings of the qualitative data analysis offered further insights, which were then mixed with the quantitative results and interpreted as one. The final results, which were an interpretation of both quantitative and qualitative findings, revealed that learning communities critically affect students’ academic and social integration. Specifically, the importance of student support and guidance from academic staff were considered important factors which could enhance students’ motivation to continue their education. Their relationships with fellow students and academic staff were reported as vital elements in order to become academically and socially integrated. In addition, developing a sense of personal awareness and the need to develop an effective academic skill-set in order to succeed was identified as critical

Analysis of Tinto’s student integration theory in first year undergraduate computing students of a UK Higher Education Institution

Purpose- Retention is one of the key performance indicators in university quality assurance processes. This study identifies causes leading to low retention rates for first year undergraduate computing students in a UK Higher Education Institution. Design/methodology/approach- The study applies Tinto’s Student Integration Theory, and connects it with be- havioural patterns of students. Data was collected from 901 students using Pascarella and Terenzini’s question- naire (integration scales). This data was combined with student enrolment information and analysed using the Structural Equation Modelling (SEM) technique. Findings- The study results indicate that Tinto’s Student Integration Theory is useful in analysing student reten- tion, but this accounts for only a modest amount of variance in retention. Nevertheless, important relationships amongst student’s initial and later academic goals and commitments have been identified through this new ap- proach to analysing retention. The largest direct effect on retention was accounted for by initial goals and institu- tional commitments, followed by later goals and institutional commitments. In addition, the results show that academic and social integration constructs can have an influence on the student retention processes. When all, or some, of these relationships are operating towards students’ benefit, appropriate services or programmes, such as student support systems, can have their maximum benefit. Originality/value- The authors mapped behavioural related retention factors using a learning community lens. The study explored students’ social and learning experiences within the context of a UK Higher Education insti- tution by employing Tinto’s model. This is the first time the model has been tested in this context

Retention of computing students in a London-based university during the Covid-19 pandemic using learned optimism as a lens: a statistical analysis in R

The aim of this research project is to investigate the low retention rate among the foundation and first year undergraduate students from the School of Computing and Digital Media in a London based university. Specifically, the research is conducted during the Covid-19 pandemic using learned optimism as a lens. The research will aid the university to improve retention rate as the overall dropout has been increasing in the last few years. The current study employed an exploratory investigation approach by using statistical modelling analysis in R to predict behavioural patterns. The quantitative data analysis conducted aims to support the efforts of the School of Computing and Digital Media of a London based university to re-evaluate its retention strategies in foundation and first year computing students. The main outcomes of the analysis is that students with a foreign qualification are optimistic, while students with other or not known qualification are mildly pessimistic. In addition, students with a BTECH, Higher Education diploma or A level qualification are generally more pessimistic especially if they are also black ethnicity, or are also not black ethnicity, aged under 34 and British

Breast ductal endoscopy: how many procedures qualify?

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