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AI Enabled IoT Network Traffic Fingerprinting With Locality Sensitive Hashing
Get PDFThe ubiquity of IoT devices in both public and private networks has increased dramatically in the last few years with billions of network-connected devices appearing in every sector. In many cases these devices provide low-power and low-cost solutions to multiple problems, but this convenience comes with a price. Low- powered devices often lack the computational capacity to support encryption or other means of protection. In addition, devices are often optimized for easy connection out-of-the-box, potentially leaving them vulnerable due to unchanged default configurations. It has been shown that device IP and MAC addresses can be easily spoofed, making accounting for IoT devices within a network problematic. These vulnerabilities have led to devices being compromised by malware such as the Mirai botnet, allowing for their unintentional use as access points to protected networks, as well as participants in large scale distributed denial of service (DDoS) attacks. With their increasing popularity leading to rapid growth, the development of new methods for identification and monitoring is critical. Much work has been done in recent times to address the problem of identification by fingerprinting network traffic using various techniques, allowing network administrators to track device membership and detect anomalous behavior. While a high degree of accuracy has been achieved, effective feature extraction and acceptable computational overhead continue to be an issue. In addition, machine learning models often require frequent modification and retraining to remain effective. We apply a combination of locality sensitive hashing and machine learning techniques to identify specific devices based on their network traffic, eliminating the need for complex feature engineering and model retraining. This approach achieves an accuracy identifying known devices as high as 98% using only a single packet sniffed from the network allowing for real-time device identification, providing a significant improvement over previous approaches. We aim to leverage this method to assist in the real-time identification of IoT devices based on their network traffic fingerprint. This will allow for the tracking of specific devices, detection of normal vs. anomalous behavior, and monitoring to alert administrative personnel when new or unauthorized devices appear on the network, providing improved security and network device accounting
Exploring the Mental Health Concerns of Advocates Working With Sexually Exploited Youth
Get PDFJob stress and fatigue can lead to employees burning out, especially for those working with children as youth advocates and case managers. This then causes disruptions in vital services being provided to clients (He et al., 2018; Orsi-Hunt et al., 2023). Unfortunately, 64% of child welfare workers have reported burnout symptoms across multiple studies (Baugerud et al., 2018; Leake et al., 2017). Research on burnout suggests advocates and case managers working with child exploitation investigators (Brady, 2017), and those working with sex-trafficking victims (Schwartz, 2021), may be at a higher risk for developing burnout. However, little research has explored individual burnout symptoms in advocates and case workers working with sexually exploited youth. This exploratory study will aim to answer the following questions: (a) What are some signs of burnout that youth advocates and case managers experience? (b) What coping strategies do youth advocates and case managers use to manage everyday stressors in their work environments? (c) What resources or advice do youth advocates and case managers perceive as being most useful for addressing burnout? Convenience and snowball sampling were used to collect data from advocates and case managers working with sexually exploited youth. This study found burnout to be a common theme experienced by individuals working with this unique population. Advocates and case managers express coping strategies that help them tackle burnout, along with resources that will benefit themselves and co-workers from burnout
Verification and Development of a Steady Thermal CFD Model for High Density Staging of Radiological Materials Packages
No full textThis thesis overviews the work that took place to exercise and verify results of a computational fluid dynamics model with a densely-packed array of staged heat generating packages in a theoretical ventilated room for the purposes of developing an application that estimates the surface temperatures of the packages with configurable loading conditions. A generic staging building was modelled in Solidworks with lights, a ventilation system, and 640 packages containing radiological materials placed on pallets located on four racks. The geometry was then used in Ansys Workbench where fluid and solid regions were assigned and then meshed with four different grid sizes. In Ansys Fluent, these regions were assigned boundary conditions and material properties that replicate a realistic loading condition for the theoretical staging room. Package temperature results from each mesh were compared with one another to determine the number of iterations and grid size necessary to approach the results achieved by the finest grid for 10,000 iterations. The results of the finest grid sizing are used to present the expected flow pattern in the staging building, the distribution of package temperatures, and the location of the packages of interest. From this work, the grid sizing and number of iterations needed for the simulation for the application were found to be 64 million elements run for 7,000 iterations. Package temperatures from the finest grid result indicate that the maximum package surface temperatures do not exceed 43oC which is 6.4oC colder than the maximum allowable surface temperature of the 9975 package
miR-10a-5p and miR-10b-5p Regulate Gastrointestinal Dysmotility in Aged Mice
No full textWe previously identified miR-10a-5p and miR-10b-5p (miR-10a/b-5p), as key regulators in gastrointestinal (GI) motility and diabetes. Healthy pacemaker cells, known as intestinal cells of Cajal (ICC), in the GI tract abundantly express miR-10a/b-5p, which in turn promote the growth and differentiation of these cells and therefore regulate GI motility. However, the role of miR-10a/b-5p in regulating GI dysmotility in aged mice has not been explored. In this study, we found miR-10a/b-5p were highly expressed in late embryonic and early postnatal stages but gradually decreased in aged mice. Similarly, ICC in the colon progressively deteriorated in the old age group compared to the young age group. Body weight gradually increased with age. Fasting blood glucose levels remained normal in the young, middle, and old age groups. However, GI motility showed an age-dependent impairment as total GI transit time (TGITT) was significantly delayed in the old age group. In addition, colon transit time (CTT) was also significantly delayed in the middle age group and further delayed in the old age group, which showed similar patterns in fecal pellet output (FPO). To confirm whether GI motility was regulated via miR-10a/b-5p, we generated mir-10a and/or mir-10b knockout (KO) mice. GI motility (TGITT, CTT, and FPO) was impaired in mir-10a KO mice and mir-10b KO mice. We finally demonstrated delayed GI motility was improved in the old age mice by injection of a miR-10a-5p mimic, confirming the key role of miR-10a-5p in the restoration of GI motility. This study suggests that GI motility is regulated by miR-10a/b-5p-mediated ICC phenotype in aged mice
A VUI Foundation and Performance Validation for Voice-to-Motion Control of Snake-like Robots
Get PDFSnakes are unique animals whose locomotion method has been the subject of analytical research since Sir James Gray first began investigating the undulatory movement of eels in the 1930s. The locomotion of snakes is unique as it allows snakes to efficiently navigate complex and uneven terrains without articulated limbs. This movement pattern is attractive in the field of robotics exactly for its hyper redundancy and lack of requirements of limbs. These two aspects of snake like locomotion translate well into the field of robotics. A hyper redundant locomotion mode means a more robust ability to move through inhospitable terrain and a lack of limbs means a relatively uncomplex movement system. These advantages allow snake like robots to be used effectively in extreme environments like disaster relief scenarios or even space exploration. Controlling a snake like robot in an environment like this requires lots of training if traditional methods of robotic control are used but if vocal command system with a high level of intuitive intelligence is created much of the effort, on the part of the operator, involved in training and use in an extreme environment can be relieved. This thesis details the design and implementation of a voice-command based control system for a robotic snake. The snake robot used in this thesis was designed and constructed in the lab with many capabilities and locomotion modes. This complexity of the snake robot used necessitated a similarly complex remote controller to operate the robot. The voice-command based control system shown in this thesis will enable the control of the snake robot to a similar or same degree as the remote control system from previous work and serve as a foundation for further projects involving the control of the robot. The theoretical and practical considerations surrounding the construction of the system are discussed in the following paragraphs. The advantages and disadvantages of the Automatic Speech Recognition software and Natural Language Processing methods considered for this project are explored and analyzed. A Comparison between the control method demonstrated in this thesis and the control method from previous projects is drawn exploring the advantages and disadvantages of the two systems and whether they are comparable
Development and Application of Krypton Spectroscopy for Spatially Resolved Analysis of Hot Implosion Cores
Get PDFA novel diagnostic technique utilizing krypton spectroscopy has been developed to obtain spatially resolved plasma conditions in hot implosion cores. Traditional diagnostic methods based on argon K-shell emission (3-5 keV) are limited to relatively low electron temperatures, below 2000 eV; however, this new technique enables the analysis of plasmas at significantly higher temperatures. To extract plasma conditions in these hot implosion cores, the atomic kinetics, Stark broadening and radiation transport effects were modeled for the Kr L-shell (2-4 keV) [1] and K-shell (12-16 keV) [2] spectral regions. As a result, spectral databases for these regions were developed, which showed sensitivity to electron temperature (Te) and density (ne). New Kr Multi-Monochromatic X-ray Imagers (MMI) were developed for both L-shell and K-shell regions to record the spatially resolved spectra needed to extract Te and ne distributions. The L-shell design involved a minor modification of the previous Ar MMI design, while the Kr K-shell required a major redesign of the instrument. For the Kr L-shell case, it was observed that the experimental setup using glass shell capsules did not allow for the detection of useful data. However, the Kr K-shell MMI achieved unprecedented 2D spatially resolved and time-gated Kr spectral measurements [4]. Analysis of these spectra, informed by the modeled Kr database, has produced the first 2D spatial distributions of core Te and ne at Te > 2000 eV. These measurements enable the calculation of spatial distributions of various plasma parameters, including pressure, radiation losses, and electron thermal transport. Furthermore, the results will be used to benchmark ion stopping power models in hot plasmas and to investigate differences between hydrodynamic and kinetic implosion regimes. This advancement provides a new approach to the study of High Energy Density plasmas
Investigating Reversible Zinc Electrodeposition Dynamic Windows
No full textThe current energy crisis is a growing and unrelenting problem that affects all of humanity. A problem that only seems to grow with the increasing world population leading to greater and greater energy demand from unrenewable and environmentally harmful sources. As such, energy sustainability is an expanding field attracting great interest. Dynamic windows have emerged as a potential solution in recent years as a technology that allows for a large decrease in energy consumption. Dynamic windows allow for controllable transparency through the application of a voltage, which in turn allows for greater control of the amount of light and heat in a building. This control leads to a reduction in the heating and cooling needed in a building to provide a comfortable environment and thus energy savings. However, current methods of creating dynamic windows have encountered hurdles that prevent the technology from being adopted widely. Dynamic windows that employ reversible metal electrodeposition (RME) allow for the construction of devices with high contrast, multiple optical states between 80% and <1% transmission, and high reversibility for a long cycle life. RME possesses several advantages over other forms of dynamic window, however, many of these benefits depend on the metal used in the electrolyte of the RME window. Electrolytes that enable the coelectrodeposition of Bi and Cu are leading candidates for use in RME windows due to their ability to support high contrast, fast, color-neutral, and reversible windows. In this dissertation, I detail progress made to address the low pH environment necessitated by the low solubility of Bi in water under neutral or alkaline conditions. I use chelating agents to bind to Bi, which allow for greater solubility at higher pH. This change leads to less etching of the transparent conducting working electrode and extends shelf life and viability of the Bi-Cu window. Zn electrolytes are another promising metal candidate for use in RME dynamic window electrolytes. The majority of this dissertation focuses on the use of Zn to create highly reversible electrolytes, some with Coulombic efficiencies as high as 99%. I examine the effect that anions such as halides and sulfate have on the spectroelectrochemical performance of different electrolytes. I further build a connection between the morphology of the Zn electrodeposits and window performance. I utilize techniques such as X-ray diffraction and scanning electron microscopy to study the Zn surface layer after electrodeposition, I analyze how dendritic and uneven morphology hinder long term cyclability. Using this knowledge, I employed methods such as the use of polymers in the electrode to create a three-electrode device that can cycle over 1,000 times as well as a practical two-electrode device that cycles over 100 times. I also designed a novel method of construction of dynamic windows through the employment of water-in-salt electrolytes (WISe). As opposed to traditional salt-in-water electrolytes, WISe facilitated Zn electrodeposition that does not generate side products such as ZnO or Zn(OH)2. This discovery as well as others written about in this dissertation illustrate the viability and promise of Zn for RME dynamic windows and serves as the basis for further modification and improvements
Material Recovery from Energy Production & Storage Technologies and Water Contaminant Monitoring
No full textGlobal electrification and global warming have greatly influenced the investigation of alternative power generation options. Several of these are intermittent and/or require some form of energy storage. Solar technologies are one of the leading renewable energy generation options, with silicon photovoltaics (Si PVs) having the largest market share. PVs heavily rely on energy storage as they are dependent on the time of day and general weather conditions, and lithium-ion battery (LIB) technologies are amongst the frontrunner energy storage options. Several considerations have arisen around PVs and LIBs, notably, raw materials for manufacture and waste management at their end-of-life (EoL). These two concerns can be simultaneously addressed through the recycling of materials from waste PV modules and spent LIBs. Apart from treating solid waste, wastewater generation during operations is a major aspect of consideration. It is therefore essential to develop means for rapid water testing to monitor contaminant discharge levels. The main goals of this dissertation are to highlight the work carried out in investigating methods of recovering materials from spent LIBs and waste PV modules. This was achieved through the application of organic and inorganic agents that have never been applied for the treatment and recovery of materials in these domains. A systematic approach for LIB pretreatment followed by leaching studies was developed, thereby contributing to LIB material recovery. A key characteristic is the ability to utilize the highlighted inorganic acids, the hydrohalic acids in the absence of a reducing agent and achieve high metal (Co, Li, Mn and Ni) recoveries of ~90%. Furthermore, based on conducted investigations, the inherent nature of the halide species presents aids in preventing toxic gas evolution. Recovery tests were carried out in which Si PV cells were recovered with minimal damage with the application of hexane as a solvent, presenting an eco-friendly and benign approach to pursue towards a strategic pathway for extending the life of recycled PV modules. Apart from material recovery, work on development of a sensor for water contaminant monitoring was explored, with cyanide as the working industrial contaminant monitored. Titanium dioxide (TiO2) nanotubes were used as the sensor substrate, with suitable and relatively inexpensive additives, achieving sensitive and selective electrochemical detection of cyanide in water. The current-time measurements indicated that i) increasing cyanide concentration could perturb the current proportionally, ii) the differential in the current could be used as a calibration for quantitative detection of cyanide, and iii) the developed sensor was highly selective even in the presence of interfering species. The work presented in this dissertation is expected to impact the materials recycling & recovery market by contributing towards providing more options for materials recovery, particularly regarding EoL LIBs and Si PV modules while also presenting a potential means for water contaminant monitoring during processing and recycling
Improving Safety of Rebar Cages using Innovative Connectors
No full textPrefabricated rebar cages are widely used in reinforced concrete constructions. These temporary structures are built by connecting longitudinal and transverse reinforcing bars (rebars), typically using tie-wires. Previous studies have identified tie-wire connections as the "weak links" in the rebar cage system, mainly responsible for failures in rebar cages at construction sites, resulting in injuries, fatalities, project delays, and increased construction costs. Consequently, this research explores the application of mechanical connectors for connecting rebars in a rebar cage. The research includes a comprehensive experimental and numerical investigation of the structural behavior of rebar cages, specifically those reinforced with mechanical connectors such as U-bolts and Cage Clamps. The overarching goal of the research is to promote the adoption of mechanical connectors as a viable solution to enhance the overall safety of rebar cages during different phases of construction.Through a series of experimental tests, the force-deformation response of mechanical connectors has been explored for crossbar connection in different degrees of freedom. The findings indicate that mechanical connectors offer significantly higher strength and stiffness compared to tie-wire connections. Subsequently, thirty-one experimental tests are performed on six full-scale underground pile-shaft rebar cages with tie-wires and mechanical connectors. The data obtained from the experiments are used to develop and calibrate detailed finite element models, demonstrating the effectiveness of mechanical connectors in enhancing the strength and stability of rebar cages. Building upon these experimental and numerical works, and through parametric studies and dimensional analysis, analytical models are developed to characterize the stiffness properties of a rebar cage as a function of its physical parameters. The derived stiffness properties are then used to create a simplified beam model for rebar cage analysis. The simplified model enables practitioners to analyze the deflection of rebar cages under on-site loading conditions without relying on complex and expensive finite element numerical models. Finally, in collaboration with rebar cage practitioners, a technical guideline and a best practice manual have been developed for the systematic analysis, design, fabrication, and handling of rebar cages using mechanical connectors. These documents provide a streamlined approach to decide about connector layouts, lifting process, and other rebar cage configurations, allowing for a practical process to design and fabricate rebar cages and ensure their stability and safety under common jobsite loading conditions
Digital Echoes of a Movement: Analyzing the Evolution of the WomanLifeFreedom Movement through Hashtag Analysis
No full textThis research investigates the digital activism surrounding the WomanLifeFreedom (WLF) movement on X (formerly Twitter), a significant socio-political uprising in Iran following the death of Mahsa Amini in September 2022. The study analyzes the use of the hashtag #MahsaAmini and co-occurrence hashtags along with it to understand the movement's dynamics, geographical spread, and evolving discourse. Observing in nine months of the movement, I tracked 270,000 tweets, to map engagement and identify key co-occurring hashtags. Findings reveal five primary frames within the movement: Tactics and Mobilization, Regime Change, Global Solidarity & Support, Activism, and Women's Rights. The analysis underscores the pivotal role of hashtags in Iranian protests, demonstrating how protesters strategically organized collective actions before the regime's repressive actions. Despite the central slogan 'WomanLifeFreedom' and the movement's origins in the death of a 22-year-old girl, my findings show that the movement not only focused on women's rights but mainly advocated for broader political transformation. This study highlights how social media has unified and mobilized diverse groups against systemic oppression in Iran. It illustrates the Iranian populace's strong desire for change and emphasizes the critical role of digital platforms in contemporary movements for democracy and human rights, particularly in authoritarian contexts