Information dissemination in mobile networks

This thesis proposes some solutions to relieve, using Wi-Fi wireless networks, the data consumption of cellular networks using cooperation between nodes, studies how to make a good deployment of access points to optimize the dissemination of contents, analyzes some mechanisms to reduce the nodes' power consumption during data dissemination in opportunistic networks, as well as explores some of the risks that arise in these networks. Among the applications that are being discussed for data off-loading from cellular networks, we can find Information Dissemination in Mobile Networks. In particular, for this thesis, the Mobile Networks will consist of Vehicular Ad-hoc Networks and Pedestrian Ad-Hoc Networks. In both scenarios we will find applications with the purpose of vehicle-to-vehicle or pedestrian-to-pedestrian Information dissemination, as well as vehicle-to-infrastructure or pedestrian-to-infrastructure Information dissemination. We will see how both scenarios (vehicular and pedestrian) share many characteristics, while on the other hand some differences make them unique, and therefore requiring of specific solutions. For example, large car batteries relegate power saving techniques to a second place, while power-saving techniques and its effects to network performance is a really relevant issue in Pedestrian networks. While Cellular Networks offer geographically full-coverage, in opportunistic Wi-Fi wireless solutions the short-range non-fullcoverage paradigm as well as the high mobility of the nodes requires different network abstractions like opportunistic networking, Disruptive/Delay Tolerant Networks (DTN) and Network Coding to analyze them. And as a particular application of Dissemination in Mobile Networks, we will study the malware spread in Mobile Networks. Even though it relies on similar spreading mechanisms, we will see how it entails a different perspective on Dissemination

Topology-Aware Vulnerability Mitigation Worms

In very dynamic Information and Communication Technology (ICT) infrastructures, with rapidly growing applications, malicious intrusions have become very sophisticated, effective, and fast. Industries have suffered billions of US dollars losses due only to malicious worm outbreaks. Several calls have been issued by governments and industries to the research community to propose innovative solutions that would help prevent malicious breaches, especially with enterprise networks becoming more complex, large, and volatile. In this thesis we approach self-replicating, self-propagating, and self-contained network programs (i.e. worms) as vulnerability mitigation mechanisms to eliminate threats to networks. These programs provide distinctive features, including: Short distance communication with network nodes, intermittent network node vulnerability probing, and network topology discovery. Such features become necessary, especially for networks with frequent node association and disassociation, dynamically connected links, and where hosts concurrently run multiple operating systems. We propose -- to the best of our knowledge -- the first computer worm that utilize the second layer of the OSI model (Data Link Layer) as its main propagation medium. We name our defensive worm Seawave, a controlled interactive, self-replicating, self-propagating, and self-contained vulnerability mitigation mechanism. We develop, experiment, and evaluate Seawave under different simulation environments that mimic to a large extent enterprise networks. We also propose a threat analysis model to help identify weaknesses, strengths, and threats within and towards our vulnerability mitigation mechanism, followed by a mathematical propagation model to observe Seawave's performance under large scale enterprise networks. We also preliminary propose another vulnerability mitigation worm that utilizes the Link Layer Discovery Protocol (LLDP) for its propagation, along with an evaluation of its performance. In addition, we describe a preliminary taxonomy that rediscovers the relationship between different types of self-replicating programs (i.e. viruses, worms, and botnets) and redefines these programs based on their properties. The taxonomy provides a classification that can be easily applied within the industry and the research community and paves the way for a promising research direction that would consider the defensive side of self-replicating programs

Dictionary of privacy, data protection and information security

The Dictionary of Privacy, Data Protection and Information Security explains the complex technical terms, legal concepts, privacy management techniques, conceptual matters and vocabulary that inform public debate about privacy. The revolutionary and pervasive influence of digital technology affects numerous disciplines and sectors of society, and concerns about its potential threats to privacy are growing. With over a thousand terms meticulously set out, described and cross-referenced, this Dictionary enables productive discussion by covering the full range of fields accessibly and comprehensively. In the ever-evolving debate surrounding privacy, this Dictionary takes a longer view, transcending the details of today''s problems, technology, and the law to examine the wider principles that underlie privacy discourse. Interdisciplinary in scope, this Dictionary is invaluable to students, scholars and researchers in law, technology and computing, cybersecurity, sociology, public policy and administration, and regulation. It is also a vital reference for diverse practitioners including data scientists, lawyers, policymakers and regulators

Notes on pre-Nightingale nursing: what it was and what it was not

Tanya Langtree studied the evolution of nursing praxis between the sixteenth and mid-nineteenth centuries. Tanya found pre-professionalised nursing practice was scientifically informed and aimed to restore health, promote comfort and prevent complications. These findings disrupt assumptions about early nursing and encourages the profession to reframe its understanding of the past

Cyber defensive capacity and capability::A perspective from the financial sector of a small state

This thesis explores ways in which the financial sectors of small states are able todefend themselves against ever-growing cyber threats, as well as ways these states can improve their cyber defense capability in order to withstand current andfuture attacks. To date, the context of small states in general is understudied. This study presents the challenges faced by financial sectors in small states with regard to withstanding cyberattacks. This study applies a mixed method approach through the use of various surveys, brainstorming sessions with financial sector focus groups, interviews with critical infrastructure stakeholders, a literature review, a comparative analysis of secondary data and a theoretical narrative review. The findings suggest that, for the Aruban financial sector, compliance is important, as with minimal drivers, precautionary behavior is significant. Countermeasures of formal, informal, and technical controls need to be in place. This study indicates the view that defending a small state such as Aruba is challenging, yet enough economic indicators indicate it not being outside the realm of possibility. On a theoretical level, this thesis proposes a conceptual “whole-of-cyber” model inspired by military science and the VSM (Viable Systems Model). The concept of fighting power components and governance S4 function form cyber defensive capacity’s shield and capability. The “whole-of-cyber” approach may be a good way to compensate for the lack of resources of small states. Collaboration may be an only out, as the fastest-growing need will be for advanced IT skillsets

Enhancing Free-text Interactions in a Communication Skills Learning Environment

Learning environments frequently use gamification to enhance user interactions.Virtual characters with whom players engage in simulated conversations often employ prescripted dialogues; however, free user inputs enable deeper immersion and higher-order cognition. In our learning environment, experts developed a scripted scenario as a sequence of potential actions, and we explore possibilities for enhancing interactions by enabling users to type free inputs that are matched to the pre-scripted statements using Natural Language Processing techniques. In this paper, we introduce a clustering mechanism that provides recommendations for fine-tuning the pre-scripted answers in order to better match user inputs