A System Perspective to Privacy, Security and Resilience in Mobile Applications

Mobile applications have changed our life so much, but they also create problems related to privacy which is one of basic human rights. Protection (or security) of privacy is an important issue in mobile applications owing to the high likelihood of privacy violation nowadays. This thesis is devoted to a fundamental study on the privacy issue in mobile applications. The overall objective of the thesis is to advance our understanding of privacy and its relevant concepts in the context of mobile applications. There are three specific objectives with this thesis. Objective 1 is to have a more comprehensive understanding of the concepts of privacy, security and resilience (PSR for short) along with their relationship in the context of mobile applications. Objective 2 is to develop the principles of design of a mobile application system with a satisfactory PSR. Objective 3 is to develop a demonstration system (PSR demo for short) to illustrate how the principles of design can be applied. A salient approach was taken in this thesis, that is based on a general knowledge architecture called FCBPSS (F: function, C: context, B: behavior, P: principle. SS: state and structure). An analysis of literature was conducted first, resulting in a classification of various privacies against the FCPBSS architecture, followed by developing a theory of privacy, protection of privacy (security), and resilience of the system that performs protection of privacy, PSR theory for short. The principles of design of a mobile application system based on the PSR theory were then developed, which are expected to guide the practice of developing a mobile application for satisfactory privacy protection. Finally, a demonstration system, regarding the doctor booking for minimum waiting time and energy consumption, was developed to issue how the PSR theory and design principles work. The main contribution of this thesis is the development of the concept of PSR, especially the relationship among privacy (P), security (S), and resilience (R), and a set of design rules to develop a mobile application based on the PSR theory

An Approach to Guide Users Towards Less Revealing Internet Browsers

When browsing the Internet, HTTP headers enable both clients and servers send extra data in their requests or responses such as the User-Agent string. This string contains information related to the sender’s device, browser, and operating system. Previous research has shown that there are numerous privacy and security risks result from exposing sensitive information in the User-Agent string. For example, it enables device and browser fingerprinting and user tracking and identification. Our large analysis of thousands of User-Agent strings shows that browsers differ tremendously in the amount of information they include in their User-Agent strings. As such, our work aims at guiding users towards using less exposing browsers. In doing so, we propose to assign an exposure score to browsers based on the information they expose and vulnerability records. Thus, our contribution in this work is as follows: first, provide a full implementation that is ready to be deployed and used by users. Second, conduct a user study to identify the effectiveness and limitations of our proposed approach. Our implementation is based on using more than 52 thousand unique browsers. Our performance and validation analysis show that our solution is accurate and efficient. The source code and data set are publicly available and the solution has been deployed

Causal Reinforcement Learning: A Survey

Reinforcement learning is an essential paradigm for solving sequential decision problems under uncertainty. Despite many remarkable achievements in recent decades, applying reinforcement learning methods in the real world remains challenging. One of the main obstacles is that reinforcement learning agents lack a fundamental understanding of the world and must therefore learn from scratch through numerous trial-and-error interactions. They may also face challenges in providing explanations for their decisions and generalizing the acquired knowledge. Causality, however, offers a notable advantage as it can formalize knowledge in a systematic manner and leverage invariance for effective knowledge transfer. This has led to the emergence of causal reinforcement learning, a subfield of reinforcement learning that seeks to enhance existing algorithms by incorporating causal relationships into the learning process. In this survey, we comprehensively review the literature on causal reinforcement learning. We first introduce the basic concepts of causality and reinforcement learning, and then explain how causality can address core challenges in non-causal reinforcement learning. We categorize and systematically review existing causal reinforcement learning approaches based on their target problems and methodologies. Finally, we outline open issues and future directions in this emerging field.Comment: 48 pages, 10 figure

Parallel programming systems for scalable scientific computing

High-performance computing (HPC) systems are more powerful than ever before. However, this rise in performance brings with it greater complexity, presenting significant challenges for researchers who wish to use these systems for their scientific work. This dissertation explores the development of scalable programming solutions for scientific computing. These solutions aim to be effective across a diverse range of computing platforms, from personal desktops to advanced supercomputers.To better understand HPC systems, this dissertation begins with a literature review on exascale supercomputers, massive systems capable of performing 10¹⁸ floating-point operations per second. This review combines both manual and data-driven analyses, revealing that while traditional challenges of exascale computing have largely been addressed, issues like software complexity and data volume remain. Additionally, the dissertation introduces the open-source software tool (called LitStudy) developed for this research.Next, this dissertation introduces two novel programming systems. The first system (called Rocket) is designed to scale all-versus-all algorithms to massive datasets. It features a multi-level software-based cache, a divide-and-conquer approach, hierarchical work-stealing, and asynchronous processing to maximize data reuse, exploit data locality, dynamically balance workloads, and optimize resource utilization. The second system (called Lightning) aims to scale existing single-GPU kernel functions across multiple GPUs, even on different nodes, with minimal code adjustments. Results across eight benchmarks on up to 32 GPUs show excellent scalability.The dissertation concludes by proposing a set of design principles for developing parallel programming systems for scalable scientific computing. These principles, based on lessons from this PhD research, represent significant steps forward in enabling researchers to efficiently utilize HPC systems

Problems in Cloud Security, Access Control and Logic Locking

In this thesis, we study problems related to security in three different contexts: cloud scheduling, access control, and logic locking to protect digital ICs. The first set of problems relates to security in cloud computing. Prior work suggests that scheduling, with security as a consideration, can be effective in minimizing information leakage, via side-channels, that can exist when virtual machines (VMs) co-reside in clouds. We analyze the overhead that is incurred by such an approach. We first pose and answer a fundamental question: is the problem tractable? We show that the seemingly simpler sub-cases of initial placement and migration across only two equal-capacity servers are both intractable (NP-hard). However, a decision version of the general problem to which the optimization version is related polynomially is in NP. With these results as the basis, we make several other contributions. We revisit recent work that proposes a greedy algorithm for this problem, called Nomad. We establish that if P != NP, then there exist infinitely many classes of input, each with an infinite number of inputs, for which a decrease in information leakage is possible, but Nomad provides none, let alone minimize it. We establish also that a mapping to Integer Linear Programming (ILP) in prior work is deficient in that the mapping can be inefficient (exponential-time), and therefore does not accurately convey the overhead of such an approach that actually decreases information leakage. We present our efficient reductions to ILP and boolean satisfiability in conjunctive normal form (CNF-SAT). We have implemented these approaches and conducted an empirical assessment using the same ILP solver as prior work, and a SAT solver. Our analytical and empirical results more accurately convey the overhead that is incurred by an approach that actually provides security (decrease in information leakage). The second set of problems relates to access control. We pose and study forensic analysis in the context of access control systems. Forensics seeks to answer questions about past states of a system, and thereby provides important clues and evidence in the event of a security incident. Access control deals with who may perform what action on a resource and is an important security function. We argue that access control is an important context in which to consider forensic analysis, and observe that it is a natural complement of safety analysis, which has been considered extensively in the literature. We pose the forensic analysis problem for access control systems abstractly, and instantiate it for three schemes from the literature: a well-known access matrix scheme, a role-based scheme, and a discretionary scheme. In particular, we ask what the computational complexity of forensic analysis is, and compare it to the computational complexity of safety analysis for each of these schemes. We observe that in the worst-case, forensic analysis lies in the same complexity class as safety analysis. We consider also the notion of logs, i.e., data that can be collected over time to aid forensic analysis. We present results for sufficient and minimal logs that render forensic analysis for the three schemes efficient. This motivates discussions on goal-directed logging, with the explicit intent of aiding forensic analysis. We carry out a case-study in the realistic setting of a serverless cloud application, and observe that goal-directed logging can be highly effective. Our work makes contributions at the foundations of information security, and its practical implications. The third set of problems relates to logic locking to protect digital integrated circuits (ICs) against untrusted semiconductor foundries. We make two sets of complementary contributions, all rooted in foundations and bolstered by implementations and empirical results. Our first set of contributions regards observations about prior schemes and attacks, and our second is a new security notion. Towards the former, we make two contributions. (a) We revisit a prior approach called XOR-locking that has been demonstrated to be susceptible, in practice, to a particular attack called the SAT attack. We establish that (i) there exist circuits that are invulnerable to the SAT attack when XOR-locked with even a 1-bit key, and, (ii) there is a particular property that is inherent to benchmark circuits that explains why the SAT attack is successful against XOR-locked versions of those. Both (i) and (ii) are rooted in computing foundations: for (i), one-way functions; for (ii), average-case computational complexity, specifically, the class distP. (b) We revisit a state-of-art logic locking approach called TTLock whose generalization called SFLL-HD has been argued to be ``provably secure'' in prior work. We devise a new, probabilistic attack against TTLock. We explain, from foundations, why benchmark circuits that are locked using TTLock are susceptible to our new attack. Our observations (a) and (b), and prior work on attacks, informs our second contribution, which is a new security notion. Our notion is at least as strong as the property that underlies the SAT attack

Climate change in a mingling-state: sea level rise confronts social susceptibility and justice in the southwestern coastal region of Bangladesh

Shyamnagar Upazila, within the Southwestern part of Bangladesh encompassing the entire Sundarbans, is located in the deltas of the Ganges, Brahmaputra and Megna rivers in the Bay of Bengal and is an area extremely vulnerable to climate change, with serious consequences at the socioeconomic level. This doctoral research involved collecting data on physical, hydrological, geographical aspects, land cover change, rainfall changing patterns, water and soil trace elements, and tidal gauges. These data were complemented with the analysis of social and economic vulnerability dimensions through qualitative methods (interviews, focus groups and observation). Qualitative data collection techniques, including focus group discussions (FGDs), case studies, PRA (Participatory rural appraisal) questionnaires, workshops, in-depth interviews, key informant interviews and participant observation, was undertaken in the Shyamnagar Upazila from 2017 to 2019 (through Skype + messenger + over telephone 2020 to 2022). A survey with a close ended questionnaire was applied at the first stage in nine unions (series-based analysis), at the second stage in 12 unions (risk, hazards, vulnerability and adaptation analysis) and at a third stage in 3 unions (safe drinking water and health analysis) with a total of (320 +387 +1579) household samples (n = 2286). Sea level rise has negative impacts on agriculture, riverbank erosion, and salinity, loss of natural ecosystems, gender vulnerability, poverty, food security, fisheries, safe water resources, migration, and public health factors that affect the development of SWCRB populations and cause climate injustices. This thesis analyzed the implications of coastal risks and hazards to the vulnerability of the local populations, while also addressing their perceptions of justice and adaptation strategies.A subida acelerada do nível médio do mar (SLR) é o impacto mais importante das alterações climáticas nas zonas costeiras do Bangladesh. Esta investigação de doutoramento centrou-se na região costeira do sudoeste do Bangladesh (SWCRB), que enfrenta um perigo iminente com a subida do nível do mar, com consequências diretas nas desigualdades sociais e na justiça climática. Com enfoque nos temas-chave dos ODS, esta compilação de artigos contribui para a implementação da Agenda 2030 das Nações Unidas, nomeadamente para os ODS1 – “Erradicar a pobreza”, ODS2 –“Erradicar a fome”, ODS3 – “Saúde de qualidade, ODS5 – “Igualdade de género”, ODS6 – “Água potável e saneamento”, ODS10 – “Redução das desigualdades”, ODS13 – “Ação climática” e ODS16 – “Paz, justiça e instituições eficazes”. Para analisar a vulnerabilidade induzida pela subida do nível do mar, esta investigação considerou a atual e futura modelização da subida do nível do mar. A metodologia utilizada é interdisciplinar e foi baseada numa abordagem de métodos mistos. Esta investigação inclui quatro artigos publicados em revistas revistas revistas por pares, integrados no corpo da tese como capítulos de resultados (capítulos 4 a 7), tendo o autor submetido ainda durante o período do doutoramento dois outros artigos e dois capítulos de livros que foram aceites e que, por conseguinte, estão incluídos como material suplementar a esta tese (anexos). O primeiro artigo (capítulo 4) centrou-se na modelação da subida do nível médio do mar (NMM). As projeções locais do nível do mar indicam que o este pode aumentar em meio metro ou até mais de um metro até ao final do século XXI. A região da Baía de Bengala revela taxas superiores às médias globais, devido à fusão dos glaciares dos Himalaias. Contudo, devido à natureza não linear da subida do NMM, é de esperar que as projeções sejam ultrapassadas, o que representa uma ameaça para a vida de milhões de pessoas no Bangladesh. Além disso, as zonas costeiras do sudoeste do Bangladesh são altamente vulneráveis à intrusão de água salgada, sobretudo devido aos ciclones e à subida do NMM, especialmente a região de Shyamnagar Upazila, e espera-se que isto se agrave durante o próximo século devido às alterações climáticas. Por conseguinte, este estudo analisa a geoquímica da água salgada e compostos relacionados, a resposta à intrusão salina nos sistemas fluviais e as possíveis áreas afetadas pelos eventos climáticos extremos nas condições actuais e em 2100. Esta análise mostrou que os níveis de salinidade do solo e da água são já altamente inadequados para os padrões de fertilidade do solo e a qualidade da água na região. Além disso, analisaram-se os principais impactos das alterações climáticas na saúde pública, começando pelo global e passando pelo local, estudando as comunidades costeiras na área de influência das Sundarbans. Discutimos quais são os principais desafios enfrentados pelos diferentes atores a nível local, incluindo o agravamento de certos riscos para a saúde da comunidade com os impactos das alterações climáticas. Os países em desenvolvimento estão a enfrentar grandes desafios em termos de mitigação e adaptação, no entanto são os que têm contribuído menos para as causas das alterações climáticas. Verificou-se que a maioria dos inquiridos vive abaixo do limiar da pobreza, com níveis de desigualdade relativamente baixos baseados num coeficiente de Gini de 28,5 (capítulo 5). Algumas das questões mais graves que afetam a subsistência das populações locais são os ciclones e as inundações, bem como o aumento da salinidade do solo e da água doce. Os mais pobres estão muito mais expostos aos eventos extremos, têm reduzidos recursos económicos para prevenir e recuperar dos seus impactos, e as suas fontes diretas de rendimento, na sua maioria baseadas em recursos naturais, são também duramente afetadas. Os resultados mostraram que o impacto das alterações climáticas difere entre homens e mulheres nas comunidades examinadas (capítulo 6). Entre os principais fatores que influenciam a vulnerabilidade da comunidade estão os níveis de escolaridade, as normas culturais locais. Ainda assim, estas mulheres têm potencial para participar em planos de conservação ambiental, para liderar movimentos sociais e ambientais, e para promover estratégias de gestão sustentável dos recursos naturais, uma vez que são consideradas como as guardiãs do conhecimento local. Finalmente, esta investigação propõe que, a fim de reduzir a vulnerabilidade feminina, as mulheres devem ser capacitadas e integradas em medidas de mitigação e planos de adaptação, tanto como partes interessadas como como agentes de mudança. Ao analisar o impacto socioeconómico das alterações climáticas, esta investigação contribui para o debate sobre a justiça climática, que é uma problemática social, política e económica (capítulo 7). Os países industrializados que mais contribuíram para o problema através da emissão excessiva de gases com efeito de estufa (GEE) são os menos propensos a sofrer as consequências. Tanto a abordagem baseada nos direitos humanos como a abordagem baseada nas capacidades são aqui discutidas, mas concluímos que esta última é a mais adequada para compreender a realidade no Bangladesh. Esta área está a sofrer enormes mudanças devido aos efeitos devastadores das alterações climáticas e da subida do NMM. Com base em extensivos estudos locais, a tese conclui que as populações locais gostariam de estar mais envolvidas na conceção, planeamento e implementação de estratégias para reforçar a resiliência das suas comunidades. A população local destaca como as suas principais necessidades ter acesso a água doce a preços acessíveis, a segurança alimentar e as infraestruturas sustentáveis, tais como estradas, casas, escolas e unidades de saúde. Nestas áreas, muitas vezes as formas de assistência centram-se na ajuda de emergência após grandes catástrofes; contudo, isto não é suficiente. A intensidade da subida do nível do mar torna cada vez mais difícil a reconstrução após a ocorrência de cada catástrofe. Foram ainda efetuadas análises para avaliar o estado da água, da vegetação e do solo na região. O estudo analisa os dados pluviométricos recolhidos pelo BWDB entre 1968 e 2018, mostrando as mudanças no padrão de precipitação ao longo dos anos e a diminuição da produção agrícola no SWCRB e reforçando o diagnóstico de declínio das terras agrícolas durante o período 1989-2019. Como forma de diversificar as suas fontes de rendimento, alguns agricultores converteram as suas terras para a criação de camarão, o que aumenta ainda mais a salinidade do solo. Além disso, a Barragem Farakka afecta negativamente a população da SWCRB ao reduzir o fluxo do rio Ganges para o Bangladesh. As medidas adaptativas utilizadas pelos agricultores incluem a construção de aterros, a recolha das águas da chuva, a drenagem adequada para reduzir o alagamento, o controlo da expansão das explorações de camarão e a introdução de culturas de de alto rendimento mas que são mais tolerantes à salinidade, bem como o emprego de novas técnicas de irrigação. Além disso, as técnicas agrícolas Sorjan e o cultivo flutuante, a pecuária e a agricultura apoiadas pela comunidade, são vistas pelos agricultores das zonas costeiras como uma forma de mitigar os impactos climáticos. A análise de vulnerabilidade revela que a população local já implementou com sucesso oito estratégias de adaptação baseadas na comunidade para reduzir a vulnerabilidade causada pela subida do mar e pelas inundações. Tem sido testemunhado que as práticas de adaptação implementadas com a participação direta das comunidades tem contribuído para a redução das vulnerabilidades e o reforço da resiliência das populações locais. Após as catástrofes, a reabilitação dos aterros costeiros com o envolvimento da comunidade local é uma resposta favorecida nos processos de adaptação estrutural, bem como a reflorestação costeira e os abrigos polivalentes construídos pelo governo para os furacões. Concluiu-se também que o governo deveria ter em consideração as propostas da comunidade local para ajudar no processo de adaptação. Já há um vasto número de vítimas das alterações climáticas na SWCRB. Ao mesmo tempo, estas regiões tornaram-se um campo de ensaio para estratégias de adaptação que são particularmente adequadas para as comunidades de pequena escala. Considerando as contribuições empíricas de todos os artigos incluídos nesta tese, pode argumentar-se que as estratégias de adaptação e resiliência, até à data, não têm considerado plenamente indicadores sociais tais como pobreza, desigualdade de género, empoderamento ou desigualdades de rendimentos. A subida do nível do mar, agravada pelas alterações climáticas, tem impactos negativos na agricultura, na erosão das margens dos rios e no aumento da salinidade, levando à perda de ecossistemas naturais, a uma menor segurança alimentar das populações e a maiores fluxos de migração, contribuindo ainda para agravar problemas de saúde pública que afetam o desenvolvimento das populações da SWCRB e geram crescentes injustiças

Digital Biomarker Models for Prediction of Infectious Disease Susceptibility

Acute respiratory viral infection (ARVI) represents one of the most prevalent infectious diseases affecting mankind. With the threat of COVID-19 still looming over us, we have witnessed the substantial threat ARVI poses to world health and economy, extinguishing millions of lives and costing trillions of dollars. This sets the context for the research of this thesis: using digital biomarkers to distinguish between individuals who are susceptible to becoming severely infected and/or infectious before an infection is clinically detectable. The development of such biomarkers can have both clinical and epidemiological impact in terms of identifying individuals who are either vulnerable to severe infection or those who may become highly infectious. The digital biomarkers and associated analysis methods are developed and validated on longitudinal data collected by our clinical collaborators from two different ARVI challenge studies. The first study provides data on healthy human volunteers who were inoculated with the common cold and the second study provides data on volunteers inoculated with the flu. Digital biomarkers include molecular, physiological and cognitive data continuously collected from blood, wearable devices and cognitive testing of the study participants. The findings of our research on digitally measurable susceptibility factors are wide-ranging. We find that circadian rhythm at the molecular scale (biochronicity) plays an important role in mediating both the susceptibility and the response to severe infection, revealing groups of gene expression markers that differentiate the responses of low infected and high infected individuals. Using a high dimensional representation of physiological signals from a wearable device, we find that an infection response and its onset time can be reliably predicted at least 24 hours before peak infection time. We find that a certain measure of variability in pre-exposure cognitive function is highly associated with the post-exposure severity of infection.PHDBioinformaticsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/169966/1/yayazhai_1.pd