abstract: Peer-to-peer systems are known to be vulnerable to the Sybil attack. The lack of a central authority allows a malicious user to create many fake identities (called Sybil nodes) pretending to be independent honest nodes. The goal of the malicious user is to influence the system on his/her behalf. In order to detect the Sybil nodes and prevent the attack, a reputation system is used for the nodes, built through observing its interactions with its peers. The construction makes every node a part of a distributed authority that keeps records on the reputation and behavior of the nodes. Records of interactions between nodes are broadcast by the interacting nodes and honest reporting proves to be a Nash Equilibrium for correct (non-Sybil) nodes. In this research is argued that in realistic communication schedule scenarios, simple graph-theoretic queries such as the computation of Strongly Connected Components and Densest Subgraphs, help in exposing those nodes most likely to be Sybil, which are then proved to be Sybil or not through a direct test executed by some peers. / Dissertation/Thesis / Ph.D. Computer Science 2010

abstract: Microblogging services such as Twitter, Sina Weibo, and Tumblr have been emerging and deeply embedded into people's daily lives. Used by hundreds of millions of users to connect the people worldwide and share and access information in real-time, the microblogging service has also became the target of malicious attackers due to its massive user engagement and structural openness. Although existed, little is still known in the community about new types of vulnerabilities in current microblogging services which could be leveraged by the intelligence-evolving attackers, and more importantly, the corresponding defenses that could prevent both the users and the microblogging service providers from being attacked. This dissertation aims to uncover a number of challenging security and privacy issues in microblogging services and also propose corresponding defenses. This dissertation makes fivefold contributions. The first part presents the social botnet, a group of collaborative social bots under the control of a single botmaster, demonstrate the effectiveness and advantages of exploiting a social botnet for spam distribution and digital-influence manipulation, and propose the corresponding countermeasures and evaluate their effectiveness. Inspired by Pagerank, the second part describes TrueTop, the first sybil-resilient system to find the top-K influential users in microblogging services with very accurate results and strong resilience to sybil attacks. TrueTop has been implemented to handle millions of nodes and 100 times more edges on commodity computers. The third and fourth part demonstrate that microblogging systems' structural openness and users' carelessness could disclose the later's sensitive information such as home city and age. LocInfer, a novel and lightweight system, is presented to uncover the majority of the users in any metropolitan area; the dissertation also proposes MAIF, a novel machine learning framework that leverages public content and interaction information in microblogging services to infer users' hidden ages. Finally, the dissertation proposes the first privacy-preserving social media publishing framework to let the microblogging service providers publish their data to any third-party without disclosing users' privacy and meanwhile meeting the data's commercial utilities. This dissertation sheds the light on the state-of-the-art security and privacy issues in the microblogging services. / Dissertation/Thesis / Doctoral Dissertation Electrical Engineering 2016

Trådlösa nätverk är något som växer och breder ut sig mer och mer i det moderna samhället. Allt fler personer har bärbara enheter som kan ansluta till dessa nät. Därför måste de nätverk som inte skall vara publika skyddas från obehöriga. Viktig information kan annars hamna i fel händer. I denna rapport kommer olika trådlösa nätverk och säkerhetslösningar till dessa att undersökas. Genom att använda olika säkerhetslösningar så som kryptering med hjälp av t.ex . WPA och även tillämpar Pfleeger’s teorier om datasäkerhet så kan ett trådlöst nätverk vara förhållandevis säkert mot de flesta angripare.

The flexibility of Mobile Ad hoc networks (MANET) and its characteristics introduce new security risks. One possible attack is the Black Hole attack which received recent attention. In the Black Hole attack, a malicious node uses the routing protocol to declare itself as having the shortest path to the node whose packets it wants to intercept. It is needed to understand this risk with a view to extract preventive and corrective protections against it. We introduce an approach that could stop this attack from happening in such a network by using an algorithm which controls the communications between nodes and let each node becomes identified and authorized in a group of nodes. In this algorithm, stable nodes, which called leaders, are responsible for routing and forwarding packets from source to destination nodes. This research reviews the black hole attack, and, explains the algorithm that helps throughput to be increased as a consequence. / Graduate / manar.alnaghes@hotmail.com

Transient ischaemic attack (TIA) and minor stroke are associated with a high risk of recurrent stroke which can be predicted with a clinical rule and reduced with urgent treatment. Delay in accessing assessment and vascular risk factor modification should therefore be as short as possible, yet little is known in the UK about where patients seek care and the key influences of the time to contact healthcare services. However, using cohort studies to answer questions on healthcare access requires an assessment of how well such cohorts represent the wider population. Within the primary care consultation, the recognition of TIA is an important step in the care pathway as definitive treatment is initiated by specialists, yet TIA presentations are not common for individual GPs and difficulties in diagnosis may be due to low clinical exposure in routine practice or inadequacies in training. For patients where GPs suspect that TIA may be the cause of symptoms, inaccurate risk prediction and diagnosis of TIA can result in delay to definitive care and the existing tools for prognosis and diagnosis have been exclusively derived from clinical assessments in secondary care rather than primary care.

Recent advances in electronic and computer technologies lead to wide-spread deployment of wireless sensor networks (WSNs). WSNs have wide range applications, including military sensing and tracking, environment monitoring, smart environments, etc. Many WSNs have mission-critical tasks, such as military applications. Thus, the security issues in WSNs are kept in the foreground among research areas. Compared with other wireless networks, such as ad hoc, and cellular networks, security in WSNs is more complicated due to the constrained capabilities of sensor nodes and the properties of the deployment, such as large scale, hostile environment, etc. Security issues mainly come from attacks. In general, the attacks in WSNs can be classified as external attacks and internal attacks. In an external attack, the attacking node is not an authorized participant of the sensor network. Cryptography and other security methods can prevent some of external attacks. However, node compromise, the major and unique problem that leads to internal attacks, will eliminate all the efforts to prevent attacks. Knowing the probability of node compromise will help systems to detect and defend against it. Although there are some approaches that can be used to detect and defend against node compromise, few of them have the ability to estimate the probability of node compromise. Hence, we develop basic uniform, basic gradient, intelligent uniform and intelligent gradient models for node compromise distribution in order to adapt to different application environments by using probability theory. These models allow systems to estimate the probability of node compromise. Applying these models in system security designs can improve system security and decrease the overheads nearly in every security area. Moreover, based on these models, we design a novel secure routing algorithm to defend against the routing security issue that comes from the nodes that have already been compromised but have not been detected by the node compromise detecting mechanism. The routing paths in our algorithm detour those nodes which have already been detected as compromised nodes or have larger probabilities of being compromised. Simulation results show that our algorithm is effective to protect routing paths from node compromise whether detected or not.

Background: Myocardial infarction (MI), also known as heart attack, is the leading cause of morbidity and mortality among the heart diseases spectrum. It results from an insufficient supply of blood to the heart muscles. According to the United States (U.S.) Centers for Disease Control and Prevention (CDC), about 610 000 people die of heart disease in the U.S. every year. Myocardial infarction contributes 370 000 of these deaths annually. Every 40 seconds, someone in the U.S. experience heart attack. This burden is disproportionately distributed within the U.S. population. The rate of heart disease in Central Appalachia is 249 per 100 000, 42% higher than the national rate. Exploring further within the region, rural areas experience higher heart disease mortality rates; 27% higher than the region’s metro counties. According to 2018 America Health Ranking, the prevalence of heart attack in Tennessee is 5.9%, compared to the 4.9% nationwide, with the majority of the burden seen among adults aged ≥65 years and with a 1:1.8 female to male ratio. Patients with heart disease often have other comorbid conditions such as peripheral arterial disease (PAD), hypertension, diabetes, dyslipidemias, which contribute immensely to this chronic condition. Therefore, the aim of this study is to explore the association between cardiovascular comorbidities such as diabetes mellitus, hypertension and dyslipidemia, and the prevalence of heart attack among patients with PAD in rural Central Appalachia. Methods: We used a cross-sectional data of patients diagnosed with PAD in the Central Appalachian region. A total of 13455 patients with PAD were recruited using ICD 9 and 10 search terms for PAD from the electronic medical records (EMR) system between January 1, 2008, and April 30, 2018. Descriptive statistics of the variables were extracted. The association between the comorbidities, including hypertension, diabetes, dyslipidemia, body mass index(BMI) and the prevalence of MI was determined using a binomial logistic regression model. All analysis was done using IBM SPSS statistics 25. Results: Of the total 13455 patients with PAD, 3045 had MI (37.7% female and 62.3% male) with a mean age of 69±10.5years. While 93% had hypertension, 56% had diabetes. For the lipids, the mean of HDL, Cholesterol, and LDL among participants with a history of MI is 40.99mg/dl±13, 156.32mg/dl±45, 82.08mg/dl±36.35 respectively. The results of binomial logistic regression with stratification based on gender shows that female patients with diabetes had 86% increased odds of MI [OR: 1.858, C.I: 1.308-2.638, p-value=0.001), and for female hypertensives, 4.51 times increased odds of MI was found (C.I: 1.576-12.895, p-value=0.005). The male diabetics and hypertensives showed a similarly increased odds of MI with (OR 1.138, C.I: 0.870-1.489 p-value=0.345) and (OR 3.697C.I: 1.559-8.736, p-value=0.003) respectively. No significant association was found among the various lipid profiles examined. Conclusion: The results showed that female PAD patients with hypertension and diabetes have a significantly increased likelihood of having MI. In contrast, male with PAD also showed increased likelihood (although to a lesser degree) of MI in those with hypertension, but not those with diabetes. These findings underscore the importance of a proactive approach to preventive care and adequate control among PAD patients with diabetes and hypertension in a bid to curbing the morbidity and mortality associated with myocardial infarction among residents in Central Appalachia.

abstract: The advances of Deep Learning (DL) achieved recently have successfully demonstrated its great potential of surpassing or close to human-level performance across multiple domains. Consequently, there exists a rising demand to deploy state-of-the-art DL algorithms, e.g., Deep Neural Networks (DNN), in real-world applications to release labors from repetitive work. On the one hand, the impressive performance achieved by the DNN normally accompanies with the drawbacks of intensive memory and power usage due to enormous model size and high computation workload, which significantly hampers their deployment on the resource-limited cyber-physical systems or edge devices. Thus, the urgent demand for enhancing the inference efficiency of DNN has also great research interests across various communities. On the other hand, scientists and engineers still have insufficient knowledge about the principles of DNN which makes it mostly be treated as a black-box. Under such circumstance, DNN is like "the sword of Damocles" where its security or fault-tolerance capability is an essential concern which cannot be circumvented. Motivated by the aforementioned concerns, this dissertation comprehensively investigates the emerging efficiency and security issues of DNNs, from both software and hardware design perspectives. From the efficiency perspective, as the foundation technique for efficient inference of target DNN, the model compression via quantization is elaborated. In order to maximize the inference performance boost, the deployment of quantized DNN on the revolutionary Computing-in-Memory based neural accelerator is presented in a cross-layer (device/circuit/system) fashion. From the security perspective, the well known adversarial attack is investigated spanning from its original input attack form (aka. Adversarial example generation) to its parameter attack variant. / Dissertation/Thesis / Doctoral Dissertation Electrical Engineering 2020

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The master’s thesis deals with computer networks, which are currently the global communication infrastructure and play a very important role in today’s society. Most of us can be unaware of how often we interact with these networks. We almost constantly come into contact with them. They allow us to communicate through the Internet via services such as: email, skype, icq, facebook, etc... The work focuses on the design and implementation of a robot designed for exploration and mapping of computer network topology and protocols HTTP and ICMP. The theoretical part is dedicated to computer networks, seventh and third-layer ISO/OSI model, protocol HTTP and ICMP attacks against DNS, DoS attacks and detection systems and avoiding distortaions.