Business Intelligence Applied to Sentiment Analysis in a Higher Education Institution

Social media allows institutions to not only publicize their work and get feedback from the community about it, but also to keep in touch with their alumni network and foster conversations between the academic community. While sentiment analysis allows a better understanding of what is being said about a brand and how to improve the use of this communication platform. The main goal of the current work is to build a Business Intelligence System for a Higher Education Institution (HEI) based on content extracted from social media. So, Posts, likes, dislikes, shares, comments and number of visits were extracted from Facebook, Google Maps Reviews, Instagram, LinkedIn, Student Forums, Twitter and YouTube. With this data and the ETL process a Data Warehouse (DW) in SQL Server and 17 Dashboards in Power BI were developed. Posts that had the most likes were about reporting a death of someone from the school, the school mascot, the pandemic or welcoming new students. Overall, the weekends were the days with more interactions. Students are concerned about accommodation, transport, and the school academic offer. This analysis allows a better understanding of what is being said about this HEI and how to improve the communication strateg

Practical Traffic Analysis Attacks on Secure Messaging Applications

Instant Messaging (IM) applications like Telegram, Signal, and WhatsApp have become extremely popular in recent years. Unfortunately, such IM services have been targets of continuous governmental surveillance and censorship, as these services are home to public and private communication channels on socially and politically sensitive topics. To protect their clients, popular IM services deploy state-of-the-art encryption mechanisms. In this paper, we show that despite the use of advanced encryption, popular IM applications leak sensitive information about their clients to adversaries who merely monitor their encrypted IM traffic, with no need for leveraging any software vulnerabilities of IM applications. Specifically, we devise traffic analysis attacks that enable an adversary to identify administrators as well as members of target IM channels (e.g., forums) with high accuracies. We believe that our study demonstrates a significant, real-world threat to the users of such services given the increasing attempts by oppressive governments at cracking down controversial IM channels. We demonstrate the practicality of our traffic analysis attacks through extensive experiments on real-world IM communications. We show that standard countermeasure techniques such as adding cover traffic can degrade the effectiveness of the attacks we introduce in this paper. We hope that our study will encourage IM providers to integrate effective traffic obfuscation countermeasures into their software. In the meantime, we have designed and deployed an open-source, publicly available countermeasure system, called IMProxy, that can be used by IM clients with no need for any support from IM providers. We have demonstrated the effectiveness of IMProxy through experiments

Sistema de Sugestões Sensível ao Contexto

Over the last few years, pervasive systems have experienced some interesting development. Nevertheless, human-human interaction can also take advantage of those systems by using their ability to perceive the surrounding environment. In this dissertation, we have developed a pervasive system - named ConversationaL Aware Suggestion SYstem (CLASSY) - which is aware of the conversational context and suggests the users potentially useful documents or that, somehow, save time executing a specific task. We have also proposed two different approaches - the Neighborhood one, that uses semantic similarity, based on proximity data in order to classify the relationship between tokens; and the Reinforcement Learning one, that uses implicit feedback associated with each suggestion as a source of knowledge that can be used to improve the system's performance over time. The conducted tests showed that these two approaches not only enhanced the pervasive behavior of the system, but also increased its global performance. A case study regarding the importance of feedback on context-limited environments was also carried out, whose results showed that it is still a useful source of knowledge regardless the conversational environment's characteristics.Ao longo dos últimos anos, os sistemas pervasivos têm sido fonte de um grande desenvolvimento. Contudo, as interações humano-humano também podem tirar vantagem deste tipo de sistemas recorrendo à sua capacidade para entender o ambiente que o rodeia. Nesta dissertação, foi desenvolvido um sistema pervasivo - chamado Sistema de Sugestões Sensível ao Contexto (CLASSY) - que está consciente dos vários contextos conversacionais e que sugere documentos considerados potencialmente úteis para os utilizadores ou que, de alguma forma, poupam tempo na execução de uma tarefa específica. Foram também propostas duas aproximações diferentes - a de vizinhança, que usa similaridade semântica, baseando-se em proximidades de forma a classificar relações entre palavras; e a de Aprendizagem por Reforço, que usa feedback implícito dos utilizadores associado a cada sugestão, como fonte de conhecimento que pode ser utilizado para melhorar a performance do sistema ao longo do tempo. Os testes realizados mostraram que as aproximações acima referidas melhoraram não só o comportamento pervasivo do sistema, mas também a sua performance global. Foi, ainda, analisado um caso de estudo referente à importância de feedback em ambientes com contexto limitado, onde os resultados mostraram que o mesmo continua a ser uma importante fonte de conhecimento, independentemente das características do ambiente conversacional.Mestrado em Engenharia de Computadores e Telemátic

Aspects of internet security: identity management and online child protection

This thesis examines four main subjects; consumer federated Internet Identity Management (IdM), text analysis to detect grooming in Internet chat, a system for using steganographed emoticons as ‘digital fingerprints’ in instant messaging and a systems analysis of online child protection. The Internet was never designed to support an identity framework. The current username / password model does not scale well and with an ever increasing number of sites and services users are suffering from password fatigue and using insecure practises such as using the same password across websites. In addition users are supplying personal information to vast number of sites and services with little, if any control over how that information is used. A new identity metasystem promises to bring federated identity, which has found success in the enterprise to the consumer, placing the user in control and limiting the disclosure of personal information. This thesis argues though technical feasible no business model exists to support consumer IdM and without a major change in Internet culture such as a breakdown in trust and security a new identity metasystem will not be realised. Is it possible to detect grooming or potential grooming from a statistical examination of Internet chat messages? Using techniques from speaker verification can grooming relationships be detected? Can this approach improve on the leading text analysis technique – Bayesian trigram analysis? Using a novel feature extraction technique and Gaussian Mixture Models (GMM) to detect potential grooming proved to be unreliable. Even with the benefit of extensive tuning the author doubts the technique would match or improve upon Bayesian analysis. Around 80% of child grooming is blatant with the groomer disguising neither their age nor sexual intent. Experiments conducted with Bayesian trigram analysis suggest this could be reliably detected, detecting the subtle, devious remaining 20% is considerably harder and reliable detection is questionable especially in systems using teenagers (the most at risk group). Observations of the MSN Messenger service and protocol lead the author to discover a method by which to leave digitally verifiable files on the computer of anyone who chats with a child by exploiting the custom emoticon feature. By employing techniques from steganography these custom emoticons can be made to appear innocuous. Finding and removing custom emoticons is a non-trivial matter and they cannot be easily spoofed. Identification is performed by examining the emoticon (file) hashes. If an emoticon is recovered e.g. in the course of an investigation it can be hashed and the hashed compared against a database of registered users and used to support non-repudiation and confirm if an individual has indeed been chatting with a child. Online child protection has been described as a classic systems problem. It covers a broad range of complex, and sometimes difficult to research issues including technology, sociology, psychology and law, and affects directly or indirectly the majority of the UK population. Yet despite this the problem and the challenges are poorly understood, thanks in no small part to mawkish attitudes and alarmist media coverage. Here the problem is examined holistically; how children use technology, what the risks are, and how they can best be protected – based not on idealism, but on the known behaviours of children. The overall protection message is often confused and unrealistic, leaving parents and children ill prepared to protect themselves. Technology does have a place in protecting children, but this is secondary to a strong and understanding parent/child relationship and education, both of the child and parent

XIP Dashboard: visual analytics from automated rhetorical parsing of scientific metadiscourse

A key competency that we seek to build in learners is a critical mind, i.e. ability to engage with the ideas in the literature, and to identify when significant claims are being made in articles. The ability to decode such moves in texts is essential, as is the ability to make such moves in one’s own writing. Computational techniques for extracting them are becoming available, using Natural Language Processing (NLP) tuned to recognize the rhetorical signals that authors use when making a significant scholarly move. After reviewing related NLP work, we introduce the Xerox Incremental Parser (XIP), note previous work to render its output, and then motivate the design of the XIP Dashboard, a set of visual analytics modules built on XIP output, using the LAK/EDM open dataset as a test corpus. We report preliminary user reactions to a paper prototype of such a novel dashboard, describe the visualizations implemented to date, and present user scenarios for learners, educators and researchers. We conclude with a summary of ongoing design refinements, potential platform integrations, and questions that need to be investigated through end-user evaluations

Targeted Attacks: Redefining Spear Phishing and Business Email Compromise

In today's digital world, cybercrime is responsible for significant damage to organizations, including financial losses, operational disruptions, or intellectual property theft. Cyberattacks often start with an email, the major means of corporate communication. Some rare, severely damaging email threats - known as spear phishing or Business Email Compromise - have emerged. However, the literature disagrees on their definition, impeding security vendors and researchers from mitigating targeted attacks. Therefore, we introduce targeted attacks. We describe targeted-attack-detection techniques as well as social-engineering methods used by fraudsters. Additionally, we present text-based attacks - with textual content as malicious payload - and compare non-targeted and targeted variants

Organization of Education Using Modern Distance Learning Technologies in the Context of the COVID-19 Pandemic (on the example of Russian law schools)

The purpose of the article was to find the key problems of transferring the educational process into a distance form, and options for their solution. The changes that have taken place in the world over the past year have posed new challenges for society to which it should have been able to react. The sphere of education found itself in a rather difficult situation. It had to be reorganized in a short time and began to function in a remote communication mode. The author's methodology was based on an empirical study (a survey of teachers and students) to determine the degree of their readiness for a global transition to distance learning. Moreover, sociological, systemic analysis and synthesis scientific methods were used. During the study, the authors have concluded that neither teachers nor trainees were ready for the transformation that took place in the field of education. The problems faced by the participants in the educational process are both technical and psychological. In the technical sphere, there was an acute shortage of equipment used by trainees in the educational process. In addition, the lack of Internet traffic provided made it difficult to exchange information between participants in the educational process.In the psychological sphere, the difficulties have boiled down to the fact that in the new environment the role and degree of responsibility of trainees have increased significantly, which was highly negatively assessed by them. Teachers of the older age group have turned out to be practically unprepared for mastering new methods using technical teaching means. The learning process was mainly reduced to self-preparation of students, during which they were offered to read lecture materials, self-test, independent problem solving and other tasks. At the same time, the interaction between a teacher and trainees was minimized. Some options for the implementation of techniques were proposed in the article. They will help in the future to grade a number of problems, increase the degree of interaction between the teacher and students, making remote learning more convenient and comfortable for many