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

Sustainable Retailing – Influencing Consumer Behaviour on Food Waste

The aim of this research was to examine the influence of a UK national retailer on its customers' food waste behaviour. Using six communication channels (in‐store magazine, e‐newsletter, Facebook site, product stickers and in‐store demonstrations), Asda presented standard food waste reduction messages to its customers during two time limited periods in 2014 and 2015. Six national surveys over 21 months tracked customers' self‐reported food waste. Our results showed that the combined communication channels and repeated messages over time had a significant effect on reducing food waste of customers. Surprisingly, customers who said they did not recall seeing the messages also reduced their food waste, showing the wider influence of interventions. Those who saw a food waste reduction message saved an estimated £81 annually from reducing food waste. The main conclusion of this paper is that retailers can influence the pro‐environmental behaviour of customers using conventional communication channels; however, repeat messages are needed in order to have a long‐term impact

Application of information theory and statistical learning to anomaly detection

In today\u27s highly networked world, computer intrusions and other attacks area constant threat. The detection of such attacks, especially attacks that are new or previously unknown, is important to secure networks and computers. A major focus of current research efforts in this area is on anomaly detection.;In this dissertation, we explore applications of information theory and statistical learning to anomaly detection. Specifically, we look at two difficult detection problems in network and system security, (1) detecting covert channels, and (2) determining if a user is a human or bot. We link both of these problems to entropy, a measure of randomness information content, or complexity, a concept that is central to information theory. The behavior of bots is low in entropy when tasks are rigidly repeated or high in entropy when behavior is pseudo-random. In contrast, human behavior is complex and medium in entropy. Similarly, covert channels either create regularity, resulting in low entropy, or encode extra information, resulting in high entropy. Meanwhile, legitimate traffic is characterized by complex interdependencies and moderate entropy. In addition, we utilize statistical learning algorithms, Bayesian learning, neural networks, and maximum likelihood estimation, in both modeling and detecting of covert channels and bots.;Our results using entropy and statistical learning techniques are excellent. By using entropy to detect covert channels, we detected three different covert timing channels that were not detected by previous detection methods. Then, using entropy and Bayesian learning to detect chat bots, we detected 100% of chat bots with a false positive rate of only 0.05% in over 1400 hours of chat traces. Lastly, using neural networks and the idea of human observational proofs to detect game bots, we detected 99.8% of game bots with no false positives in 95 hours of traces. Our work shows that a combination of entropy measures and statistical learning algorithms is a powerful and highly effective tool for anomaly detection

Workplace Engagement Around Stewardship and Recyling in a Healthcare Setting

The healthcare industry is second only to the food industry in overall waste production, and there are many opportunities to mitigate the environmental impacts of waste through waste reduction and recycling programs in healthcare. Beaumont Royal Oak is a 1,000-bed hospital in Southeast Michigan that is part of an eight-hospital, non-profit health system called Beaumont Health. Beaumont Royal Oak is unique in that it has a voluntary training program that educates employees on environmental stewardship in the work place. The Green Officer program is administered by a Green Team made up of leaders in the hospital. In addition to running the Green Officer training program, the Green Team also implements other environmental stewardship initiatives at the hospital. While the Green Team had been successful in recruiting 483 employees to undergo the Green Officer certification program at Royal Oak, as of January 2015, they lacked information about whether Green Officer’s attitudes, knowledge, and behaviors differed from non-trained employees. At the same time, data on the hospital’s waste management revealed that the hospital’s recycling rate was lower than other hospitals with dedicated stewardship programs. This master’s project attempted to answer two questions: (1) how do Beaumont Royal Oak staff perceive and engage in environmental stewardship in the work place, and (2) how can Beaumont Royal Oak increase its recycling rate? To help us answer the second question, we used the Community-Based Social Marketing (CBSM) framework to give us guidance on how to address recycling in particular. The framework helped us focus on identifying barriers and benefits to recycling and engagement in environmental stewardship. We employed a wide variety of methods, including site visits, a literature review, an online survey, and employee interviews to answer our two questions. Our survey formed the crux of our data collection process and the findings from it provided the foundation for our recommendations. We used Qualtrics software to design our 10-minute, online survey which we distributed to both Green Officers and non-Green officers within the hospital. The goals of this survey instrument were two-fold: one, to gather data about environmental stewardship among employees at Beaumont Royal Oak, and two, to identify reasons why employees were not recycling at Beaumont Royal Oak. The first half of our survey measured whether there were differences between the environmental behavior and attitudes reported by Green Officers and non-Green Officers, while the second half narrowed in on recycling and measured employee knowledge and awareness of recycling procedures, self-reported recycling behaviors, and employee perceptions of barriers to recycling. We conducted our analysis based on a sample of 294 responses, composed of 116 GOs and 178 non- GOs. Based on our analysis, we saw that attitudes towards the hospital’s work in environmental stewardship were positive across all employees suggesting ample support for future stewardship programming. Green Officers, however, reported practicing environmental stewardship behaviors in the work place more often than their colleagues who are not Green Officers. This finding suggested that Green Officers are a key group to include in developing and rolling out behavior change interventions. The second portion of the survey focused on recycling, and for all items that we asked about, we found that Green Officers recycle them more frequently than employees who have not been trained. Our survey findings demonstrated that Green Officers are also more knowledgeable about what is recyclable in the hospital. However, across both groups we found that there was a lower level of knowledge about how recycling worked in the hospital. When we asked about barriers to recycling, we found that non- Green Officers reported finding recycling more difficult than Green Officers. They consider it more inconvenient, they are more confused about labels, and they do not feel it is as worthwhile as their Green Officers counterparts do. They also reported feeling less encouragement from supervisors and colleagues to recycle. The barriers identified by respondents demonstrated a need for greater communication about how the recycling program works and how the hospital is performing over time. The physical infrastructure of the recycling bins could also use greater standardization, while still keeping unique needs for different types of workspaces in mind. Based on our site visits, survey, literature review, and interviews, we created six recommendations that fit into three themes: convenience, awareness and knowledge, and motivation. These six recommendations are to increase bin availability, standardize bin appearance, inform employees how and where to recycle, tap into effective communication channels, renew commitments regularly, and to recognize recycling leaders for their efforts. A summary table of recommendations is shown in Section 7.3. After describing our recommendations, we provide guidance to Beaumont for completing the final steps of the CBSM process. This includes piloting, evaluating, and adjusting strategies, then scaling them up across the hospital. In conclusion, this project helps the Beaumont RO Green Team understand the current state of attitudes, knowledge, and engagement regarding environmental stewardship and recycling. After investing heavily in training hundreds of GOs, a feat unique in healthcare organizations across the country, there is still much more to do to help GOs succeed in helping their peers be better stewards at work. This project contributes to the small body of knowledge surrounding healthcare professionals’ opinions on environmental issues. This is an important contribution because healthcare professionals are trusted members of the community and can be strong environmental leaders with the right support and direction.Master of ScienceNatural Resources and EnvironmentUniversity of Michiganhttp://deepblue.lib.umich.edu/bitstream/2027.42/117634/1/Masters Project Beaumont Sustainability Final Report.pd

The IceCube Realtime Alert System

Following the detection of high-energy astrophysical neutrinos in 2013, their origin is still unknown. Aiming for the identification of an electromagnetic counterpart of a rapidly fading source, we have implemented a realtime analysis framework for the IceCube neutrino observatory. Several analyses selecting neutrinos of astrophysical origin are now operating in realtime at the detector site in Antarctica and are producing alerts to the community to enable rapid follow-up observations. The goal of these observations is to locate the astrophysical objects responsible for these neutrino signals. This paper highlights the infrastructure in place both at the South Pole detector site and at IceCube facilities in the north that have enabled this fast follow-up program to be developed. Additionally, this paper presents the first realtime analyses to be activated within this framework, highlights their sensitivities to astrophysical neutrinos and background event rates, and presents an outlook for future discoveries.Comment: 33 pages, 9 figures, Published in Astroparticle Physic

Impact of communication appeals on recycling behaviors among undergraduate students

The present thesis aims to understand factors influencing student recycling behaviors, and to investigate effective communication approaches to increase such behaviors. An online survey was conducted to examine the relationships between student recycling frequency in different contexts, students’ attitudes toward the environment, barriers to their recycling, students’ perceptions of communication messages, and communication media they think to be effective. Descriptive statistics, ANOVAs, t-test, simple linear regressions, categorical multinomial logistic regression, and a chi-square test were conducted, and the data was collected from a large land-grant university in the Midwestern United States. A total of 537 questionnaires were answered. The main results of the present study are as follows: First, context as well as recycling barriers were factors that influenced student recycling behaviors. Most students who were likely to recycle at home would also recycle on campus, but students recycled more at home than on vacation. The main recycling barriers on campus were attitude barriers and knowledge barriers, while on vacation the main barriers were situational. Second, students thought positive messages were most effective in increasing recycling behavior, while students with less pro-environmental attitudes preferred neutral messages. “Clear, informative, and consistent bin infrastructure and bin labels” and “promotions such as recycling contests [and] competitions between departments or colleges” were found to be effective forms of communication. Additionally, when there were more significant factors such as the accessibility of recycling, student environmental attitudes did not play an important role in recycling behaviors on campus and on vacation. The study offers two practical recommendations. They are to increase recycling facilities and accessibility, and providing informative, clear recycling signs and labels with positive messages. Two suggestion are made for future research on the topic. They are to find factors that are more determinant than attitudes of environment about student recycling and to do more research on the usage of positive messages about student recycling behaviors

A Multifaceted Consideration of Motivation and Learning within ASSISTments

An approach to education gaining popularity in the modern classroom, adaptive tutoring systems offer interactive learning environments in which students can access immediate feedback and rich tutoring while teachers can achieve organized assessment for targeted interventions. Yet despite the benefits that these systems provide, a number of questions remain regarding the optimal inner workings of adaptive platforms. What is the recipe for optimal student performance within these platforms? What elements should be taken into consideration when designing these learning environments? Can facets of these platforms be harnessed to increase students’ motivation to learn and to improve both immediate and robust learning gains? This thesis combines work conducted over the past two years through versatile approaches toward the goal of enhancing student motivation and learning within the ASSISTments platform. Approaches considered include a) enhancing motivation and performance through altered feedback using hypermedia elements, b) instilling motivational messages alongside media enhanced content and feedback, c) allowing students to choose their feedback medium, thereby exerting control over their assignment, d) altering content delivery by interleaving skills to enhance solution strategy development, and e) establishing partial credit assessments to drive motivation and proper system usage while enhancing student modeling. After a brief introduction regarding the main tenants of this research, each chapter highlights a randomized controlled trial focused around one of these approaches. All studies presented have been conducted or are still running within ASSISTments. Much of this work has already been published at peer reviewed conference venues, some with stringent acceptance rates as low as 25% for full papers. Two of the studies presented here are second iterations of previously published work that are still in progress, and only preliminary analyses are available. A chapter on conclusions and future work is included to discuss the contributions that have been made to the Learning Sciences community thus far, and to briefly discuss potential directions for my continued research

Traffic analysis of Internet user behavior and content demand patterns

El estudio del trafico de internet es relevante para poder mejorar la calidad de servicio de los usuarios. Ser capaz de conocer cuales son los servicios más populares y las horas con más usuarios activos permite identificar la cantidad de tráfico producido y, por lo tanto, diseñar una red capaz de soportar la actividad esperada. La implementación de una red considerando este conocimiento puede reducir el tiempo de espera considerablemente, mejorando la experiencia de los usuarios en la web. Ya existen análisis del trafico de los usuarios y de sus patrones de demanda. Pero, los datos utilizados en estos estudios no han sido renovados, por lo tanto los resultados obtenidos pueden estar obsoletos y se han podido producir cambios importantes. En esta tesis, se estudia la cantidad de trafico entrante y saliente producido por diferentes aplicaciones y se ha hecho una evolución teniendo en cuenta datos presentes y pasados. Esto nos permitirá entender los cambios producidos desde 2007 hasta 2015 y observar las tendencias actuales. Además, se han analizado los patrones de demanda de usuarios del inicio de 2016 y se han comparado con resultados previos. La evolución del tráfico demuestra cambios en las preferencias de los usuarios, a pesar de que los patrones de demanda siguen siendo los mismos que en años anteriores. Los resultados obtenidos en esta tesis confirman las predicciones sobre un aumento del tráfico de 'Streaming Media'; se ha comprobado que el tráfico de 'Streaming Media' es el tráfico total dominante, con Netflix como el mayor contribuidor.L'estudi del trànsit d'Internet és rellevant per a poder millor la qualitat de servei dels usuaris. Ser capaç de conèixer quins són els serveis més popular i les hores amb més usuaris actius permet identificar la quantitat de trànsit produït i, per tant, dissenyar una xarxa capaç de soportar la activitat esperada. L'implementació d'una xarxa considerant aquest coneixement pot reduir el temps d'espera considerablement, millorant l'experiència dels usuaris a la web. Ja existeixen anàlisis del transit dels usuaris i els seus patrons de demanda. Però, les dades utilitzades en aquests estudis no han sigut renovades, per tant els resultats obtinguts poden estar obsolets i s'han produït canvis importants. En aquesta tesis, s'estudia la quantitat de transit entrant i sortint produit per diferents aplicacions i s'ha fet una evolució, tenint en compte dades presents i passades. Això ens permetrà entendre els canvis produïts des de 2007 fins 2015 i observar les tendències actuals. A més, s'han analitzat els patrons de demanda de usuaris de principis de 2016 i s'han comparat amb resultats previs. L'evolució del trànsit mostra canvis en las preferències dels usuaris, en canvi els patrons de demanda continuen sent els mateixos que en anys posteriors. Els resultats obtinguts en aquesta tesis confirmen les prediccions sobre un augment del trànsit de 'Streaming Media'; s'ha comprovat que el trànsit de 'Streaming Media' es el trànsit total dominant, amb Netflix com el major contribuïdor.The study of Internet traffic is relevant in order to improve the quality of service of users. Being able to know which are the most popular services and the hours with most active users can let us identify the amount of inbound and outbound traffic produced, and hence design a network able to support the activity expected. The implementation of a network considering that knowledge can reduce the waiting time of users considerably, improving the users’ experience in the web. Analysis of users’ traffic and user demand patterns already exist. However, the data used in these studies is not renewed, thus the results found can be obsolete and considerable changes would have happened. In this bachelor’s thesis, it is studied the amount of inbound and outbound traffic produced considering different applications and the evolution when regarding previous and actual data has been taken into account. This would let us understand the changes produced from 2007 to 2015 and observe the tendencies nowadays. In addition, it has been analyzed the user demand patterns in the beginning of 2016 and it has been contrasted with previous results. The evolution of traffic has shown changes in users’ preferences, although their demand patterns are still the same as previous years. The results found in this thesis confirmed the expectations about an increase of streaming media Internet traffic; it was proved that streaming media traffic is the dominant total traffic, with Netflix as the major contributor

Medium Moderates the Message. How Users Adjust Their Communication Trajectories to Different Media in Collaborative Task Solving.

Rapid development of information and communications technologies (ICT) has triggered profound changes in how people manage their social contacts in both informal and professional contexts. ICT mediated communication may seem limited in possibilities compared to face-to-face encounters, but research shows that puzzlingly often it can be just as effective and satisfactory. We posit that ICT users employ specific communication strategies adapted to particular communication channels, which results in a comparable effectiveness of communication. In order to maintain a satisfactory level of conversational intelligibility they calibrate the content of their messages to a given medium's richness and adjust the whole conversation trajectory so that every stage of the communication process runs fluently. In the current study, we compared complex task solving trajectories in chat, mobile phone and face-to-face dyadic conversations. Media conditions did not influence the quality of decision outcomes or users' perceptions of the interaction, but they had impact on the amount of time devoted to each of the identified phases of decision development. In face-to-face contacts the evaluation stage of the discussion dominated the conversation; in the texting condition the orientation-evaluation-control phases were evenly distributed; and the phone condition provided a midpoint between these two extremes. The results show that contemporary ICT users adjust their communication behavior to the limitations and opportunities of various media through the regulation of attention directed to each stage of the discussion so that as a whole the communication process remains effective

Multichannel Social Signatures and Persistent Features of Egocentric Networks

Mobile phones are perfect sensors for capturing the behavior of people. They are widespread personal devices that we carry around all day. Modern smartphones, equipped with an arsenal of various sensors, monitor their environments and also their owners. However, even the simplest mobile phone device, when used with a SIM card, can collect rich behavioral data. Call Detail Records (CDRs), collected by telecommunication companies for billing purposes, contain detailed information on communication behavior of the users which can not be collected by traditional data collection methods such as questionnaires. Scientists have used CDRs to study the structure and dynamics of societal-level communication networks as well as the properties of egocentric networks. The structure of weighted egocentric networks can be quantified with the so-called social signatures. It is known that call-based social signatures are distinct and persistent at the individual level. However, calling is just one of the several channels that people use to communicate. To get a more realistic picture of people's social behavior we should include more communication channels. However, because of their intrinsic differences, it is challenging to combine the usage frequencies on multiple channels into single combined weights. In this Thesis, we propose a method for determining link weights which enables us to compare the egocentric networks across different channels and also to construct multichannel egocentric networks and multichannel social signatures. Using two different datasets on calling and texting behavior of people, we observed that similarly to call signatures, text-message signatures and multichannel signatures (combining information on calls and texts) are also persistent in time. Moreover, we observed that even though people call and text different sets of people, their call and text signatures are similar in shape. In other words, the shapes of our social signatures--which are distinct from signatures of others--seem to be independent of the communication channel or the people whom we contact. Further research is needed to explain the mechanism behind these shapes and to investigate the roots of persistence and stability of social signatures