2 results
Search Results
Now showing 1 - 2 of 2
Conference Object Citation - Scopus: 2Big Data on Cloud for Government Agencies: Benefits, Challenges, and Solutions(Assoc Computing Machinery, 2018) Rashed, Alaa Hussain; Karakaya, Ziya; Yazici, AliBig Data and Cloud computing are the most important technologies that give the opportunity for government agencies to gain a competitive advantage and improve their organizations. On one hand, Big Data implementation requires investing a significant amount of money in hardware, software, and workforce. On the other hand, Cloud Computing offers an unlimited, scalable and on-demand pool of resources which provide the ability to adopt Big Data technology without wasting on the financial resources of the organization and make the implementation of Big Data faster and easier. The aim of this study is to conduct a systematic literature review in order to collect data to identify the benefits and challenges of Big Data on Cloud for government agencies and to make a clear understanding of how combining Big Data and Cloud Computing help to overcome some of these challenges. The last objective of this study is to identify the solutions for related challenges of Big Data. Four research questions were designed to determine the information that is related to the objectives of this study. Data is collected using literature review method and the results are deduced from there.Conference Object An Overview of Challenges To Long-Term Sustainability and Scalability of Radio Frequency Fingerprinting(IEEE, 2024) Demiroglu, Harun Senol; Awan, Maaz Ali; Kara, AliInternet of Things (IoT) technology has become ubiquitous with a broad spectrum of applications. This vast penetration entails formidable cyber-security for the stable operation of the associated systems. Most inexpensive IoT devices employ rudimentary cryptographic security mechanisms due to their resource-limited architecture. Radio frequency fingerprinting (RFF) is a physical layer security mechanism that leverages hardware impairments for authentication and device classification. To this end, its scope has been limited to academia owing to daunting challenges. In this work, an abridged overview of the state-of-the-art is provided, along with a summary of the challenges that hinder progress toward practical applications. The article culminates with a discussion on the intricacies of performance metrics in RFF and the direction for future research.
