896 research outputs found
Configuration Management of Distributed Systems over Unreliable and Hostile Networks
Economic incentives of large criminal profits and the threat of legal consequences have pushed criminals to continuously improve their malware, especially command and control channels. This thesis applied concepts from successful malware command and control to explore the survivability and resilience of benign configuration management systems.
This work expands on existing stage models of malware life cycle to contribute a new model for identifying malware concepts applicable to benign configuration management. The Hidden Master architecture is a contribution to master-agent network communication. In the Hidden Master architecture, communication between master and agent is asynchronous and can operate trough intermediate nodes. This protects the master secret key, which gives full control of all computers participating in configuration management. Multiple improvements to idempotent configuration were proposed, including the definition of the minimal base resource dependency model, simplified resource revalidation and the use of imperative general purpose language for defining idempotent configuration.
Following the constructive research approach, the improvements to configuration management were designed into two prototypes. This allowed validation in laboratory testing, in two case studies and in expert interviews. In laboratory testing, the Hidden Master prototype was more resilient than leading configuration management tools in high load and low memory conditions, and against packet loss and corruption. Only the research prototype was adaptable to a network without stable topology due to the asynchronous nature of the Hidden Master architecture.
The main case study used the research prototype in a complex environment to deploy a multi-room, authenticated audiovisual system for a client of an organization deploying the configuration. The case studies indicated that imperative general purpose language can be used for idempotent configuration in real life, for defining new configurations in unexpected situations using the base resources, and abstracting those using standard language features; and that such a system seems easy to learn.
Potential business benefits were identified and evaluated using individual semistructured expert interviews. Respondents agreed that the models and the Hidden Master architecture could reduce costs and risks, improve developer productivity and allow faster time-to-market. Protection of master secret keys and the reduced need for incident response were seen as key drivers for improved security. Low-cost geographic scaling and leveraging file serving capabilities of commodity servers were seen to improve scaling and resiliency. Respondents identified jurisdictional legal limitations to encryption and requirements for cloud operator auditing as factors potentially limiting the full use of some concepts
Multidisciplinary perspectives on Artificial Intelligence and the law
This open access book presents an interdisciplinary, multi-authored, edited collection of chapters on Artificial Intelligence (‘AI’) and the Law. AI technology has come to play a central role in the modern data economy. Through a combination of increased computing power, the growing availability of data and the advancement of algorithms, AI has now become an umbrella term for some of the most transformational technological breakthroughs of this age. The importance of AI stems from both the opportunities that it offers and the challenges that it entails. While AI applications hold the promise of economic growth and efficiency gains, they also create significant risks and uncertainty. The potential and perils of AI have thus come to dominate modern discussions of technology and ethics – and although AI was initially allowed to largely develop without guidelines or rules, few would deny that the law is set to play a fundamental role in shaping the future of AI. As the debate over AI is far from over, the need for rigorous analysis has never been greater. This book thus brings together contributors from different fields and backgrounds to explore how the law might provide answers to some of the most pressing questions raised by AI. An outcome of the Católica Research Centre for the Future of Law and its interdisciplinary working group on Law and Artificial Intelligence, it includes contributions by leading scholars in the fields of technology, ethics and the law.info:eu-repo/semantics/publishedVersio
LATEST ADVANCES ON SECURITY ARCHITECTURE FOR 5G TECHNOLOGY AND SERVICES
The roll out of the deployment of the 5G technology has been ongoing globally. The
deployment of the technologies associated with 5G has seen mixed reaction as regards its
prospects to improve communication services in all spares of life amid its security concerns. The
security concerns of 5G network lies in its architecture and other technologies that optimize the
performance of its architecture. There are many fractions of 5G security architecture in the
literature, a holistic security architectural structure will go a long way in tackling the security
challenges. In this paper, the review of the security challenges of the 5G technology based on its
architecture is presented along with their proposed solutions. This review was carried out with
some keywords relating to 5G securities and architecture; this was used to retrieve appropriate
literature for fitness of purpose. The 5G security architectures are mojorly centered around the
seven network security layers; thereby making each of the layers a source of security concern on
the 5G network. Many of the 5G security challenges are related to authentication and authorization
such as denial-of-service attacks, man in the middle attack and eavesdropping. Different methods
both hardware (Unmanned Aerial Vehicles, field programmable logic arrays) and software (Artificial
intelligence, Machine learning, Blockchain, Statistical Process Control) has been proposed for
mitigating the threats. Other technologies applicable to 5G security concerns includes: Multi-radio
access technology, smart-grid network and light fidelity. The implementation of these solutions
should be reviewed on a timely basis because of the dynamic nature of threats which will greatly
reduce the occurrence of security attacks on the 5G network
A lightweight and secure multilayer authentication scheme for wireless body area networks in healthcare system
Wireless body area networks (WBANs) have lately been combined with different healthcare equipment to monitor patients' health status and communicate information with their healthcare practitioners. Since healthcare data often contain personal and sensitive information, it is important that healthcare systems have a secure way for users to log in and access resources and services. The lack of security and presence of anonymous communication in WBANs can cause their operational failure. There are other systems in this area, but they are vulnerable to offline identity guessing attacks, impersonation attacks in sensor nodes, and spoofing attacks in hub node. Therefore, this study provides a secure approach that overcomes these issues while maintaining comparable efficiency in wireless sensor nodes and mobile phones. To conduct the proof of security, the proposed scheme uses the Scyther tool for formal analysis and the Canetti–Krawczyk (CK) model for informal analysis. Furthermore, the suggested technique outperforms the existing symmetric and asymmetric encryption-based schemes
Radio frequency communication and fault detection for railway signalling
The continuous and swift progression of both wireless and wired communication technologies in today's
world owes its success to the foundational systems established earlier. These systems serve as the building
blocks that enable the enhancement of services to cater to evolving requirements. Studying the
vulnerabilities of previously designed systems and their current usage leads to the development of new
communication technologies replacing the old ones such as GSM-R in the railway field. The current industrial
research has a specific focus on finding an appropriate telecommunication solution for railway
communications that will replace the GSM-R standard which will be switched off in the next years.
Various standardization organizations are currently exploring and designing a radiofrequency technology
based standard solution to serve railway communications in the form of FRMCS (Future Railway Mobile
Communication System) to substitute the current GSM-R. Bearing on this topic, the primary strategic
objective of the research is to assess the feasibility to leverage on the current public network technologies
such as LTE to cater to mission and safety critical communication for low density lines. The research aims
to identify the constraints, define a service level agreement with telecom operators, and establish the
necessary implementations to make the system as reliable as possible over an open and public network,
while considering safety and cybersecurity aspects.
The LTE infrastructure would be utilized to transmit the vital data for the communication of a railway system
and to gather and transmit all the field measurements to the control room for maintenance purposes. Given
the significance of maintenance activities in the railway sector, the ongoing research includes the
implementation of a machine learning algorithm to detect railway equipment faults, reducing time and
human analysis errors due to the large volume of measurements from the field
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  rst 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-
 rmation 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 di erent IoT de-
vices comprising Raspberry Pis, ESP32, and ESP8266 devices. These measurements
included energy consumption, the devices' hash power, and the transaction con rma-
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 con rmation 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 arti cial 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 di erent
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 o ered by edge computing, arti cial 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  nally 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  fth and  nal 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 con dentiality, 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 bene t greatly from a resilient, distributed, decentralised,
self-managed, robust, and secure systems
A Recent Connected Vehicle - IoT Automotive Application Based on Communication Technology
Realizing the full potential of vehicle communications depends in large part on the infrastructure of vehicular networks. As more cars are connected to the Internet and one another, new technological advancements are being driven by a multidisciplinary approach. As transportation networks become more complicated, academic, and automotive researchers collaborate to offer their thoughts and answers. They also imagine various applications to enhance mobility and the driving experience. Due to the requirement for low latency, faster throughput, and increased reliability, wireless access technologies and an appropriate (potentially dedicated) infrastructure present substantial hurdles to communication systems. This article provides a comprehensive overview of the wireless access technologies, deployment, and connected car infrastructures that enable vehicular connectivity. The challenges, issues, services, and maintenance of connected vehicles that rely on infrastructure-based vehicular communications are also identified in this paper
Advanced Characterization and On-Line Process Monitoring of Additively Manufactured Materials and Components
This reprint is concerned with the microstructural characterization and the defect analysis of metallic additively manufactured (AM) materials and parts. Special attention is paid to the determination of residual stress in such parts and to online monitoring techniques devised to predict the appearance of defects. Finally, several non-destructive testing techniques are employed to assess the quality of AM materials and parts
Machine Learning Algorithm for the Scansion of Old Saxon Poetry
Several scholars designed tools to perform the automatic scansion of poetry in many languages, but none of these tools
deal with Old Saxon or Old English. This project aims to be a first attempt to create a tool for these languages. We
implemented a Bidirectional Long Short-Term Memory (BiLSTM) model to perform the automatic scansion of Old Saxon
and Old English poems. Since this model uses supervised learning, we manually annotated the Heliand manuscript, and
we used the resulting corpus as labeled dataset to train the model. The evaluation of the performance of the algorithm
reached a 97% for the accuracy and a 99% of weighted average for precision, recall and F1 Score. In addition, we tested
the model with some verses from the Old Saxon Genesis and some from The Battle of Brunanburh, and we observed that
the model predicted almost all Old Saxon metrical patterns correctly misclassified the majority of the Old English input
verses
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