14 research outputs found
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An empirical study on object-oriented software dependencies: logical, structural and semantic
This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonThree of the most widely studied software dependency types are the structural, logical and semantic dependencies. Logical dependencies capture the degree of co-change between software artifacts. Semantic dependencies capture the degree to which artifacts, comments and names are related. Structural dependencies capture the dependencies in the source code of artifacts. Prior studies show that a combination of dependency analysis (e.g., semantic and logical analysis) improves accuracy when predicting which artifacts are likely to be impacted by ripple effects of software changes (though not to a large extent) compared to individual approaches. In addition, some dependencies could be hidden dependencies when an analysis of one dependency type (e.g., logical) does not reveal artifacts only linked by another dependency type (semantic). While previous studies have focused on combining dependency information with minimal benefits, this Thesis explores the consistency of these measurements, and whether hidden dependencies arise between artifacts, and in any of the axes studied. In this Thesis, 79 Java projects are empirically studied to investigate (i) the direct influence and the degree of overlap between dependency types on three axes (logical – structural (LSt); logical – semantic (LSe); structural – semantic (StSe)) (structural, logical and semantic), and (ii) the presence of hidden coupling on the axes. The results show that a high proportion of hidden dependencies can be detected on the LSt and StSe axes. Notwithstanding, the LSe axis shows a much smaller proportion of hidden dependencies. Practicable refactoring methods to mitigate hidden dependencies are proposed in the Thesis and discussed with examples
Trust-based Approaches Towards Enhancing IoT Security: A Systematic Literature Review
The continuous rise in the adoption of emerging technologies such as Internet
of Things (IoT) by businesses has brought unprecedented opportunities for
innovation and growth. However, due to the distinct characteristics of these
emerging IoT technologies like real-time data processing, Self-configuration,
interoperability, and scalability, they have also introduced some unique
cybersecurity challenges, such as malware attacks, advanced persistent threats
(APTs), DoS /DDoS (Denial of Service & Distributed Denial of Service attacks)
and insider threats. As a result of these challenges, there is an increased
need for improved cybersecurity approaches and efficient management solutions
to ensure the privacy and security of communication within IoT networks. One
proposed security approach is the utilization of trust-based systems and is the
focus of this study. This research paper presents a systematic literature
review on the Trust-based cybersecurity security approaches for IoT. A total of
23 articles were identified that satisfy the review criteria. We highlighted
the common trust-based mitigation techniques in existence for dealing with
these threats and grouped them into three major categories, namely:
Observation-Based, Knowledge-Based & Cluster-Based systems. Finally, several
open issues were highlighted, and future research directions presented.Comment: 20 Pages, Conferenc