On the evolution of hyperlinking

Across time, the hyperlink object has supported different applications and studies. This is one perspective on the evolution of the hyperlinking concept, its context and related behaviors. Through a spectrum of hyperlinking applications and practices, the article contrasts the status quo with its related, broader, conceptual roots; it also bridges to some theorized and prototyped hyperlink variations, namely "stigmergic hyperlinks", to make the case that the ubiquitousness of some objects and certain usage patterns can obfuscate opportunities to (re)think them. In trying to contribute an answer to "what has the common hyperlink (such an apparently simple object) done to society, and what has society done to it?", the article identifies situations that have become so embedded in the daily routine, that it is now hard to think of hyperlinking alternatives.info:eu-repo/semantics/publishedVersio

Application Oriented Analysis of Large Scale Datasets

Diverse application areas, such as social network, epidemiology, and software engineering consist of systems of objects and their relationships. Such systems are generally modeled as graphs. Graphs consist of vertices that represent the objects, and edges that represent the relationships between them. These systems are data intensive and it is important to correctly analyze the data to obtain meaningful information. Combinatorial metrics can provide useful insights for analyzing these systems. In this thesis, we use the graph based metrics such as betweenness centrality, clustering coefficient, articulation points, etc. for analyzing instances of large change in evolving networks (Software Engineering), and identifying points of similarity (Gene Expression Data). Computations of combinatorial properties are expensive and most real world networks are not static. As the network evolves these properties have to be recomputed. In the last part of thesis, we develop a fast algorithm that avoids redundant recomputations of communities in dynamic networks

Command & Control: Understanding, Denying and Detecting - A review of malware C2 techniques, detection and defences

In this survey, we first briefly review the current state of cyber attacks, highlighting significant recent changes in how and why such attacks are performed. We then investigate the mechanics of malware command and control (C2) establishment: we provide a comprehensive review of the techniques used by attackers to set up such a channel and to hide its presence from the attacked parties and the security tools they use. We then switch to the defensive side of the problem, and review approaches that have been proposed for the detection and disruption of C2 channels. We also map such techniques to widely-adopted security controls, emphasizing gaps or limitations (and success stories) in current best practices.Comment: Work commissioned by CPNI, available at c2report.org. 38 pages. Listing abstract compressed from version appearing in repor

Exploring the Impact of Socio-Technical Core-Periphery Structures in Open Source Software Development

In this paper we apply the social network concept of core-periphery structure to the sociotechnical structure of a software development team. We propose a socio-technical pattern that can be used to locate emerging coordination problems in Open Source projects. With the help of our tool and method called TESNA, we demonstrate a method to monitor the socio-technical core-periphery movement in Open Source projects. We then study the impact of different core-periphery movements on Open Source projects. We conclude that a steady core-periphery shift towards the core is beneficial to the project, whereas shifts away from the core are clearly not good. Furthermore, oscillatory shifts towards and away from the core can be considered as an indication of the instability of the project. Such an analysis can provide developers with a good insight into the health of an Open Source project. Researchers can gain from the pattern theory, and from the method we use to study the core-periphery movements

Solution and quality robust project scheduling: a methodological framework.

The vast majority of the research efforts in project scheduling over the past several years has concentrated on the development of exact and suboptimal procedures for the generation of a baseline schedule assuming complete information and a deterministic environment. During execution, however, projects may be the subject of considerable uncertainty, which may lead to numerous schedule disruptions. Predictive-reactive scheduling refers to the process where a baseline schedule is developed prior to the start of the project and updated if necessary during project execution. It is the objective of this paper to review possible procedures for the generation of proactive (robust) schedules, which are as well as possible protected against schedule disruptions, and for the deployment of reactive scheduling procedures that may be used to revise or re-optimize the baseline schedule when unexpected events occur. We also offer a methodological framework that should allow project management to identify the proper scheduling methodology for different project scheduling environments. Finally, we survey the basics of Critical Chain scheduling and indicate in which environments it is useful.Framework; Information; Management; Processes; Project management; Project scheduling; Project scheduling under uncertainty; Stability; Robust scheduling; Quality; Scheduling; Stability; Uncertainty;

Measuring and Disrupting Malware Distribution Networks: An Interdisciplinary Approach

Malware Delivery Networks (MDNs) are networks of webpages, servers, computers, and computer files that are used by cybercriminals to proliferate malicious software (or malware) onto victim machines. The business of malware delivery is a complex and multifaceted one that has become increasingly profitable over the last few years. Due to the ongoing arms race between cybercriminals and the security community, cybercriminals are constantly evolving and streamlining their techniques to beat security countermeasures and avoid disruption to their operations, such as by security researchers infiltrating their botnet operations, or law enforcement taking down their infrastructures and arresting those involved. So far, the research community has conducted insightful but isolated studies into the different facets of malicious file distribution. Hence, only a limited picture of the malicious file delivery ecosystem has been provided thus far, leaving many questions unanswered. Using a data-driven and interdisciplinary approach, the purpose of this research is twofold. One, to study and measure the malicious file delivery ecosystem, bringing prior research into context, and to understand precisely how these malware operations respond to security and law enforcement intervention. And two, taking into account the overlapping research efforts of the information security and crime science communities towards preventing cybercrime, this research aims to identify mitigation strategies and intervention points to disrupt this criminal economy more effectively

Airline Catering Supply Chain Performance during Pandemic Disruption: A Bayesian Network Modelling Approach

The supply chain (SC) encompasses all actions related to meeting customer requests and transferring materials upstream to meet those demands. Organisations must operate towards increasing SC efficiency and effectiveness to meet SC objectives. Although most businesses expected the COVID-19 pandemic to severely negatively impact their SCs, they did not know how to model disruptions or their effects on performance in the event of a pandemic, leading to delayed responses, an incomplete understanding of the pandemic’s effects and late deployment of recovery measures. This paper presents a method for modelling and quantifying SC performance assessment for airline catering. In the COVID-19 context, the researchers proposed a Bayesian network (BN) model to measure SC performance and risk events and quantify the consequences of pandemic disruptions. The research simulates and measures the impact of different triggers on SC performance and business continuity using forward and backward propagation analysis, among other BN features, enabling us to combine various SC perspectives and explicitly account for pandemic scenarios. This study’s findings offer a fresh theoretical perspective on the use of BNs in pandemic SC disruption modelling. The findings can be used as a decision-making tool to predict and better understand how pandemics affect SC performance.Airline Catering Supply Chain Performance during Pandemic Disruption: A Bayesian Network Modelling ApproachacceptedVersio