8,436 research outputs found
TPAAD: twoâphase authentication system for denial of service attack detection and mitigation using machine learning in softwareâdefined network.
Software-defined networking (SDN) has received considerable attention and adoption owing to its inherent advantages, such as enhanced scalability, increased adaptability, and the ability to exercise centralized control. However, the control plane of the system is vulnerable to denial-of-service (DoS) attacks, which are a primary focus for attackers. These attacks have the potential to result in substantial delays and packet loss. In this study, we present a novel system called Two-Phase Authentication for Attack Detection that aims to enhance the security of SDN by mitigating DoS attacks. The methodology utilized in our study involves the implementation of packet filtration and machine learning classification techniques, which are subsequently followed by the targeted restriction of malevolent network traffic. Instead of completely deactivating the host, the emphasis lies on preventing harmful communication. Support vector machine and K-nearest neighbours algorithms were utilized for efficient detection on the CICDoS 2017 dataset. The deployed model was utilized within an environment designed for the identification of threats in SDN. Based on the observations of the banned queue, our system allows a host to reconnect when it is no longer contributing to malicious traffic. The experiments were run on a VMware Ubuntu, and an SDN environment was created using Mininet and the RYU controller. The results of the tests demonstrated enhanced performance in various aspects, including the reduction of false positives, the minimization of central processing unit utilization and control channel bandwidth consumption, the improvement of packet delivery ratio, and the decrease in the number of flow requests submitted to the controller. These results confirm that our Two-Phase Authentication for Attack Detection architecture identifies and mitigates SDN DoS attacks with low overhead
Distributed Ledger Technology (DLT) Applications in Payment, Clearing, and Settlement Systems:A Study of Blockchain-Based Payment Barriers and Potential Solutions, and DLT Application in Central Bank Payment System Functions
Payment, clearing, and settlement systems are essential components of the financial markets and exert considerable influence on the overall economy. While there have been considerable technological advancements in payment systems, the conventional systems still depend on centralized architecture, with inherent limitations and risks. The emergence of Distributed ledger technology (DLT) is being regarded as a potential solution to transform payment and settlement processes and address certain challenges posed by the centralized architecture of traditional payment systems (Bank for International Settlements, 2017). While proof-of-concept projects have demonstrated the technical feasibility of DLT, significant barriers still hinder its adoption and implementation. The overarching objective of this thesis is to contribute to the developing area of DLT application in payment, clearing and settlement systems, which is still in its initial stages of applications development and lacks a substantial body of scholarly literature and empirical research. This is achieved by identifying the socio-technical barriers to adoption and diffusion of blockchain-based payment systems and the solutions proposed to address them. Furthermore, the thesis examines and classifies various applications of DLT in central bank payment system functions, offering valuable insights into the motivations, DLT platforms used, and consensus algorithms for applicable use cases. To achieve these objectives, the methodology employed involved a systematic literature review (SLR) of academic literature on blockchain-based payment systems. Furthermore, we utilized a thematic analysis approach to examine data collected from various sources regarding the use of DLT applications in central bank payment system functions, such as central bank white papers, industry reports, and policy documents. The study's findings on blockchain-based payment systems barriers and proposed solutions; challenge the prevailing emphasis on technological and regulatory barriers in the literature and industry discourse regarding the adoption and implementation of blockchain-based payment systems. It highlights the importance of considering the broader socio-technical context and identifying barriers across all five dimensions of the social technical framework, including technological, infrastructural, user practices/market, regulatory, and cultural dimensions. Furthermore, the research identified seven DLT applications in central bank payment system functions. These are grouped into three overarching themes: central banks' operational responsibilities in payment and settlement systems, issuance of central bank digital money, and regulatory oversight/supervisory functions, along with other ancillary functions. Each of these applications has unique motivations or value proposition, which is the underlying reason for utilizing in that particular use case
UMSL Bulletin 2023-2024
The 2023-2024 Bulletin and Course Catalog for the University of Missouri St. Louis.https://irl.umsl.edu/bulletin/1088/thumbnail.jp
The Influence of Neuroendocrine and Genetic Markers of Stress on Cognitive Processing and Intrusive Symptoms
This body of research investigated the influence of neuroendocrine and genetic elements of arousal on cognitive processes in the development of intrusive memories and flash-forward intrusions as related to Post-Traumatic Stress Disorder. Specifically, this thesis investigated various mechanisms that may underlie intrusive symptoms as postulated by prevalent theories of PTSD. Study 1 examined the distinctive relationship between peritraumatic dissociation and subsequent re-experiencing symptoms. Network analyses revealed strong positive edges between peritraumatic dissociation and subsequent amnesia, as well as the re-experiencing symptoms of physical reactivity to reminders, flashbacks, intrusions, and dreams, and to a lesser extent emotional numbness and hypervigilance. The finding that peritraumatic dissociation is related to subsequent re-experiencing symptoms is consistent with cognitive models that emphasize the role of dissociative experiences during a traumatic event in the etiology of PTSD re-experiencing symptoms. Study 2 aimed to determine whether peri-traumatic stress, as measured via salivary cortisol and salivary alpha-amylase, as well as pre-existing genetic polymorphisms on the FKBP5 gene increased dissociation and data-driven processing, and subsequently impacted intrusive memories related to a trauma film. The findings revealed that greater noradrenergic arousal predicted less intrusive memory distress in individuals who scored higher on data-driven processing and trait dissociation, and in FKBP5 low-risk carriers. For individuals who reported less data-driven processing and trait dissociation, and in FKBP5 high-risk carriers, as noradrenergic arousal increased, intrusive memory distress increased. This study also showed no association between data-driven processing with memory fragmentation, and fragmentation with intrusive memories. Whilst these findings support some aspect of cognitive models of PTSD as they indicate a role for data-driven processing and dissociation in intrusive symptoms, they highlight a threshold at which these variables stop moderating the relationship between arousal and intrusive memories and suggest that memory fragmentation is not related to intrusive memories. Study 3 examined the role of cognitive control in flash-forward intrusions in the context of an enduring stressor, the COVID-19 pandemic. In line with expectations, results showed that as cognitive control worsened, FKBP5 high-risk carriers reported more flash-forward distress, and low-risk carriers reported less distress. These findings are considered in the context of hippocampal changes and are consistent with emerging theories of PTSD. Lastly, study 4 sought to investigate the role of two neurological processes, pattern separation and pattern completion in intrusive memories in individuals with PTSD compared to trauma exposed controls. Consistent with existing literature, the data indicate that individuals with PTSD reported more data-driven processing, more intrusive symptoms, and demonstrated better behavioural pattern completion than trauma-exposed controls. These findings are in line with current cognitive models of PTSD, as they again indicate a role for data-driven processing in PTSD. However, study 4 found no support for the postulate that deficient pattern separation is a feature of PTSD and found an opposite effect for the role of pattern completion. Whilst these findings are inconsistent with theory, they are in line with existing experimental studies. Overall, the findings from this thesis provide insight into cognitive and biological models of PTSD and shed light on the mechanisms underlying the nature and development of intrusive symptoms
Testing SOAR Tools in Use
Modern security operation centers (SOCs) rely on operators and a tapestry of
logging and alerting tools with large scale collection and query abilities. SOC
investigations are tedious as they rely on manual efforts to query diverse data
sources, overlay related logs, and correlate the data into information and then
document results in a ticketing system. Security orchestration, automation, and
response (SOAR) tools are a new technology that promise to collect, filter, and
display needed data; automate common tasks that require SOC analysts' time;
facilitate SOC collaboration; and, improve both efficiency and consistency of
SOCs. SOAR tools have never been tested in practice to evaluate their effect
and understand them in use. In this paper, we design and administer the first
hands-on user study of SOAR tools, involving 24 participants and 6 commercial
SOAR tools. Our contributions include the experimental design, itemizing six
characteristics of SOAR tools and a methodology for testing them. We describe
configuration of the test environment in a cyber range, including network,
user, and threat emulation; a full SOC tool suite; and creation of artifacts
allowing multiple representative investigation scenarios to permit testing. We
present the first research results on SOAR tools. We found that SOAR
configuration is critical, as it involves creative design for data display and
automation. We found that SOAR tools increased efficiency and reduced context
switching during investigations, although ticket accuracy and completeness
(indicating investigation quality) decreased with SOAR use. Our findings
indicated that user preferences are slightly negatively correlated with their
performance with the tool; overautomation was a concern of senior analysts, and
SOAR tools that balanced automation with assisting a user to make decisions
were preferred
Securing IoT Applications through Decentralised and Distributed IoT-Blockchain Architectures
The integration of blockchain into IoT can provide reliable control of the IoT network's
ability to distribute computation over a large number of devices. It also allows the AI
system to use trusted data for analysis and forecasts while utilising the available IoT
hardware to coordinate the execution of tasks in parallel, using a fully distributed
approach.
This thesis's ârst contribution is a practical implementation of a real world IoT-
blockchain application,
ood detection use case, is demonstrated using Ethereum proof
of authority (PoA). This includes performance measurements of the transaction con-
ârmation time, the system end-to-end latency, and the average power consumption.
The study showed that blockchain can be integrated into IoT applications, and that
Ethereum PoA can be used within IoT for permissioned implementation. This can be
achieved while the average energy consumption of running the
ood detection system
including the Ethereum Geth client is small (around 0.3J).
The second contribution is a novel IoT-centric consensus protocol called honesty-
based distributed proof of authority (HDPoA) via scalable work. HDPoA was analysed
and then deployed and tested. Performance measurements and evaluation along with
the security analyses of HDPoA were conducted using a total of 30 diâerent IoT de-
vices comprising Raspberry Pis, ESP32, and ESP8266 devices. These measurements
included energy consumption, the devices' hash power, and the transaction conârma-
tion time. The measured values of hash per joule (h/J) for mining were 13.8Kh/J,
54Kh/J, and 22.4Kh/J when using the Raspberry Pi, the ESP32 devices, and the
ESP8266 devices, respectively, this achieved while there is limited impact on each de-
vice's power. In HDPoA the transaction conârmation time was reduced to only one
block compared to up to six blocks in bitcoin.
The third contribution is a novel, secure, distributed and decentralised architecture
for supporting the implementation of distributed artiâcial intelligence (DAI) using
hardware platforms provided by IoT. A trained DAI system was implemented over the
IoT, where each IoT device hosts one or more neurons within the DAI layers. This
is accomplished through the utilisation of blockchain technology that allows trusted
interaction and information exchange between distributed neurons. Three diâerent
datasets were tested and the system achieved a similar accuracy as when testing on a
standalone system; both achieved accuracies of 92%-98%. The system accomplished
that while ensuring an overall latency of as low as two minutes. This showed the secure architecture capabilities of facilitating the implementation of DAI within IoT
while ensuring the accuracy of the system is preserved.
The fourth contribution is a novel and secure architecture that integrates the ad-
vantages oâered by edge computing, artiâcial intelligence (AI), IoT end-devices, and
blockchain. This new architecture has the ability to monitor the environment, collect
data, analyse it, process it using an AI-expert engine, provide predictions and action-
able outcomes, and ânally share it on a public blockchain platform. The pandemic
caused by the wide and rapid spread of the novel coronavirus COVID-19 was used as
a use-case implementation to test and evaluate the proposed system. While providing
the AI-engine trusted data, the system achieved an accuracy of 95%,. This is achieved
while the AI-engine only requires a 7% increase in power consumption. This demon-
strate the system's ability to protect the data and support the AI system, and improves
the IoT overall security with limited impact on the IoT devices.
The âfth and ânal contribution is enhancing the security of the HDPoA through
the integration of a hardware secure module (HSM) and a hardware wallet (HW). A
performance evaluation regarding the energy consumption of nodes that are equipped
with HSM and HW and a security analysis were conducted. In addition to enhancing
the nodes' security, the HSM can be used to sign more than 120 bytes/joule and
encrypt up to 100 bytes/joule, while the HW can be used to sign up to 90 bytes/joule
and encrypt up to 80 bytes/joule. The result and analyses demonstrated that the HSM
and HW enhance the security of HDPoA, and also can be utilised within IoT-blockchain
applications while providing much needed security in terms of conâdentiality, trust in
devices, and attack deterrence.
The above contributions showed that blockchain can be integrated into IoT systems.
It showed that blockchain can successfully support the integration of other technolo-
gies such as AI, IoT end devices, and edge computing into one system thus allowing
organisations and users to beneât greatly from a resilient, distributed, decentralised,
self-managed, robust, and secure systems
Loss of a sense of aliveness, bodily unhomeliness and radical estrangement: A phenomenological inquiry into service usersâ experiences of psychiatric medication use in the treatment of early psychosis
Quantitative research drawing on the disease-centred model of psychiatric drug action dominates research on psychiatric medication, while little is known about service usersâ subjective, embodied experiences of taking psychiatric medication. This research explored service usersâ felt, embodied and relational experiences of psychiatric medication use in the
treatment of early psychosis using a multimodal, longitudinal research design. A more in-depth understanding of what it is like and what it means to take psychiatric medication from
service usersâ idiographic perspectives is needed to improve the clinical care and support service users receive and better understand the treatment choices they make. Ten participants between the age of 18 and 30 years were recruited from London-based NHS Early Intervention in Psychosis services and participated in in-depth idiographic interviews. Eight participants took part in a follow-up interview between six and nine months later. Visual methods were used to explore the verbal as well as the pre-reflective, embodied aspects of participantsâ medication experiences. The data was analysed using a combination of interpretative phenomenological analysis and framework analysis. While taking psychiatric medication, participants reported the loss of a sense of aliveness, feelings of radical estrangement from themselves, the world and other people and a sense of being suspended in a liminal, time-locked dimension in which they felt unable to transition from past
experiences of psychosis to future recovery. The findings of this study highlight the highly distressing and adverse iatrogenic effects of psychiatric medication use, including medication-induced coporealisation, disembodiment, estrangement and a loss of belonging. More holistic, human rights-based, recovery-oriented and body-centred ways of treating psychosis are needed
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Sonic heritage: listening to the past
History is so often told through objects, images and photographs, but the potential of sounds to reveal place and space is often neglected. Our research project âSonic Palimpsestâ1 explores the potential of sound to evoke impressions and new understandings of the past, to embrace the sonic as a tool to understand what was, in a way that can complement and add to our predominant visual understandings. Our work includes the expansion of the Oral History archives held at Chatham Dockyard to include womenâs voices and experiences, and the creation of sonic works to engage the public with their heritage. Our research highlights the social and cultural value of oral history and field recordings in the transmission of knowledge to both researchers and the public. Together these recordings document how buildings and spaces within the dockyard were used and experienced by those who worked there. We can begin to understand the social and cultural roles of these buildings within the community, both past and present
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