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Articles 1 - 3 of 3
Full-Text Articles in Systems Architecture
Enhancing Urban Life: A Policy-Based Autonomic Smart City Management System For Efficient, Sustainable, And Self-Adaptive Urban Environments, Elham Okhovat
Electronic Thesis and Dissertation Repository
This thesis proposes the concept of the Policy-based Autonomic Smart City Management System, an innovative framework designed to comprehensively manage diverse aspects of urban environments, ranging from environmental conditions such as temperature and air quality to the infrastructure which comprises multiple layers of infrastructure, from sensors and devices to advanced IoT platforms and applications. Efficient management requires continuous monitoring of devices and infrastructure, data analysis, and real-time resource assessment to ensure seamless city operations and improve residents' quality of life. Automating data monitoring is essential due to the vast array of hardware and data exchanges, and round-the-clock monitoring is critical. …
Developing A Uas-Deployable Methane Sensor Using Low-Cost Modular Open-Source Components, Gavin Demali
Developing A Uas-Deployable Methane Sensor Using Low-Cost Modular Open-Source Components, Gavin Demali
Williams Honors College, Honors Research Projects
This project aimed to develop a methane sensor for deployment on an unmanned aerial system (UAS), or drone, platform. This design is centered around low cost, commercially available modular hardware components and open source software libraries. Once successfully developed, this system was deployed at the Bath Nature Preserve in Bath Township, Summit County Ohio in order to detect any potential on site fugitive methane emissions in the vicinity of the oil and gas infrastructure present. The deliverables of this project (i.e. the data collected at BNP) will be given to the land managers there to better inform future management and …
A System For Detecting Malicious Insider Data Theft In Iaas Cloud Environments, Jason Nikolai, Yong Wang
A System For Detecting Malicious Insider Data Theft In Iaas Cloud Environments, Jason Nikolai, Yong Wang
Faculty Research & Publications
The Cloud Security Alliance lists data theft and insider attacks as critical threats to cloud security. Our work puts forth an approach using a train, monitor, detect pattern which leverages a stateful rule based k-nearest neighbors anomaly detection technique and system state data to detect inside attacker data theft on Infrastructure as a Service (IaaS) nodes. We posit, instantiate, and demonstrate our approach using the Eucalyptus cloud computing infrastructure where we observe a 100 percent detection rate for abnormal login events and data copies to outside systems.