Quantifying the need for supervised machine learning in conducting live forensic analysis of emergent configurations (ECO) in IoT environments

© 2020 The Author(s) Machine learning has been shown as a promising approach to mine larger datasets, such as those that comprise data from a broad range of Internet of Things devices, across complex environment(s) to solve different problems. This paper surveys existing literature on the potential of using supervised classical machine learning techniques, such as K-Nearest Neigbour, Support Vector Machines, Naive Bayes and Random Forest algorithms, in performing live digital forensics for different IoT configurations. There are also a number of challenges associated with the use of machine learning techniques, as discussed in this paper

Smart Product Design Methodology

The noticeable emergence of new technological advances, such as Artificial Intelligence (AI) and Internet of Things (IoT), and their continuous developments in today’s market, have paved the way for an apparent transformation from conventional products to smart connected products. Smart products are Cyber-Physical Systems (CPS) that provide services to users through Internet and Communication capabilities. The use of smart products offers exceptional potential for the users to meet their expectations and needs intelligently and effectively. Hence, designers and manufacturers are encouraged to cope with constantly changing consumers’ requirements and help in satisfying their needs. It is necessary to achieve a high level of awareness when interacting with smart products, where in some cases, ambiguity and uncertainty may lead to an undesired outcome. Thus, the objective of this research thesis is to introduce a novel smart product design methodology that reveals a new design dimension that was found by conducting an extensive literature review. Smart product design methodology uses integration between existing Design Theory and Methodologies (DTM), both Systematic Design Approach (SDA) and Axiomatic Design Theory (ADT) which are integrated through the features and functions of smart products. The proposed design methodology concentrates on reducing the complexity of the product and raising its affordances for the users to perceive. This research includes a case study on smart speakers and voice-initiated virtual assistants specifically on Amazon’s Alexa, where the methodology proposed was applied. As a result, the complexity was reduced by achieving an uncoupled design, and affordances’ measures were discussed using the guidelines and recommendations concerning both visual and voice design perspectives for designers and developers of virtual assistants in order to maximize the affordances for the user to perceive with the least amount of ambiguity and doubtfulness

MORE THAN WORDS: A MULTI-DIMENSIONAL ANALYSIS OF ISLAMIC STATE LANGUAGE

ABSTRACT In this thesis I will provide an exploratory study applying Multi-Dimensional analysis to the realm of Islamic State language. Systematic, observable variables that constitute IS communications can be identified through a built model. The idea is to make more of the type of information that a human analyst relies on available in the automated pre-processing and parsing phases, the types of information that they are looking for is something that a system like Bag-of-Words is missing. The corpus studied was drawn from the Islamic State newsletter al-naba’. I collected five issues from January 2020 – February 2020. From those issues the editorial sections were focused on specifically. Two paragraphs were chosen from each editorial at random. Each paragraph was translated and coded for sixteen linguistic features, including the presence or absence of religious or political nouns and verbs. I ran a correlation matrix as well as a Factor Analysis and qualitatively analyzed each for the communicative functions. The statistical analysis revealed that overall, the Islamic State uses significantly more political speech than religious. However, in longer sentences, political and religious speech is more likely to occur. The qualitative analysis found that in longer sentences, religious and political speech are in service to each other. There is a political aim to the sentence punctuated with a religious admonition statement to reinforce the political goal. I hypothesize that MDA can determine, via a seeded exploration method, a distinct IS register among the newsletters. This thesis does not fully realize this goal; however, it does provide support for the concept by identifying patterns that may very well help to determine an IS register.Master of Art