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Articles 1 - 6 of 6
Full-Text Articles in Databases and Information Systems
Integration Of Blockchain Technology Into Automobiles To Prevent And Study The Causes Of Accidents, John Kim
Integration Of Blockchain Technology Into Automobiles To Prevent And Study The Causes Of Accidents, John Kim
Electronic Theses, Projects, and Dissertations
Automobile collisions occur daily. We now live in an information-driven world, one where technology is quickly evolving. Blockchain technology can change the automotive industry, the safety of the motoring public and its surrounding environment by incorporating this vast array of information. It can place safety and efficiency at the forefront to pedestrians, public establishments, and provide public agencies with pertinent information securely and efficiently. Other industries where Blockchain technology has been effective in are as follows: supply chain management, logistics, and banking. This paper reviews some statistical information regarding automobile collisions, Blockchain technology, Smart Contracts, Smart Cities; assesses the feasibility …
Achieving Differential Privacy And Fairness In Machine Learning, Depeng Xu
Achieving Differential Privacy And Fairness In Machine Learning, Depeng Xu
Graduate Theses and Dissertations
Machine learning algorithms are used to make decisions in various applications, such as recruiting, lending and policing. These algorithms rely on large amounts of sensitive individual information to work properly. Hence, there are sociological concerns about machine learning algorithms on matters like privacy and fairness. Currently, many studies only focus on protecting individual privacy or ensuring fairness of algorithms separately without taking consideration of their connection. However, there are new challenges arising in privacy preserving and fairness-aware machine learning. On one hand, there is fairness within the private model, i.e., how to meet both privacy and fairness requirements simultaneously in …
A Framework To Detect The Susceptibility Of Employees To Social Engineering Attacks, Hashim H. Alneami
A Framework To Detect The Susceptibility Of Employees To Social Engineering Attacks, Hashim H. Alneami
Doctoral Dissertations and Master's Theses
Social engineering attacks (SE-attacks) in enterprises are hastily growing and are becoming increasingly sophisticated. Generally, SE-attacks involve the psychological manipulation of employees into revealing confidential and valuable company data to cybercriminals. The ramifications could bring devastating financial and irreparable reputation loss to the companies. Because SE-attacks involve a human element, preventing these attacks can be tricky and challenging and has become a topic of interest for many researchers and security experts. While methods exist for detecting SE-attacks, our literature review of existing methods identified many crucial factors such as the national cultural, organizational, and personality traits of employees that enable …
Network Function Virtualization Technology Adoption Strategies, Abdlrazaq Ayodeji Adeyi Shittu
Network Function Virtualization Technology Adoption Strategies, Abdlrazaq Ayodeji Adeyi Shittu
Walden Dissertations and Doctoral Studies
Network function virtualization (NFV) is a novel system adopted by service providers and organizations, which has become a critical organizational success factor. Chief information officers (CIOs) aim to adopt NFV to consolidate and optimize network processes unavailable in conventional methods. Grounded in the diffusion of innovation theory (DOI), the purpose of this multiple case research study was to explore strategies chief information officers utilized to adopt NFV technology. Participants include two CIOs, one chief security information officer (CSIO), one chief technical officer (CTO), and two senior information technology (IT) executives. Data were collected through semi-structured telephone interviews and eight organizational …
Cloud And Edge Computation Offloading For Latency Limited Services, Ivana Kovacevic, Erkki Harjula, Savo Glisic, Beatriz Lorenzo, Mika Ylianttila
Cloud And Edge Computation Offloading For Latency Limited Services, Ivana Kovacevic, Erkki Harjula, Savo Glisic, Beatriz Lorenzo, Mika Ylianttila
Electrical and Computer Engineering Faculty Publication Series
Multi-access Edge Computing (MEC) is recognised as a solution in future networks to offload computation and data storage from mobile and IoT devices to the servers at the edge of mobile networks. It reduces the network traffic and service latency compared to passing all data to cloud data centers while offering greater processing power than handling tasks locally at terminals. Since MEC servers are scattered throughout the radio access network, their computation capacities are modest in comparison to large cloud data centers. Therefore, offloading decision between MEC and cloud server should minimize the usage of the resources while maximizing the …
See-Trend: Secure Traffic-Related Event Detection In Smart Communities, Stephan Olariu, Dimitrie C. Popescu
See-Trend: Secure Traffic-Related Event Detection In Smart Communities, Stephan Olariu, Dimitrie C. Popescu
Computer Science Faculty Publications
It has been widely recognized that one of the critical services provided by Smart Cities and Smart Communities is Smart Mobility. This paper lays the theoretical foundations of SEE-TREND, a system for Secure Early Traffic-Related EveNt Detection in Smart Cities and Smart Communities. SEE-TREND promotes Smart Mobility by implementing an anonymous, probabilistic collection of traffic-related data from passing vehicles. The collected data are then aggregated and used by its inference engine to build beliefs about the state of the traffic, to detect traffic trends, and to disseminate relevant traffic-related information along the roadway to help the driving public make informed …