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Mohamed Amine Ferrag, Fatima Alwahedi, Ammar Ayman Battah, Bilel Cherif et al. • Internet of Things and Cyber-Physical Systems
(2025)
This paper provides a comprehensive review of the future of cybersecurity through Generative AI and Large Language Models (LLMs). We explore LLM applications across various domains, including hardware design security, intrusion detection, s...
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DOI: https://doi.org/10.1016/j.iotcps.2025.01.001
Duane C. Wilson • The MIT Press eBooks
(2021)
An accessible guide to cybersecurity for the everyday user, covering cryptography and public key infrastructure, malware, blockchain, and other topics. It seems that everything we touch is connected to the internet, from mobile phones and w...
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DOI: https://doi.org/10.7551/mitpress/11656.001.0001
Leonardo Ferreira, Daniel Castro Silva, Mikel Uriarte • Knowledge and Information Systems
(2023)
Abstract With the growth of CyberTerrorism, enterprises worldwide have been struggling to stop intruders from obtaining private data. Despite the efforts made by Cybersecurity experts, the shortage of skillful security teams and the usage o...
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DOI: https://doi.org/10.1007/s10115-023-01906-6
Leslie F. Sikos • Knowledge and Information Systems
(2023)
Abstract Cybersecurity knowledge graphs, which represent cyber-knowledge with a graph-based data model, provide holistic approaches for processing massive volumes of complex cybersecurity data derived from diverse sources. They can assist s...
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DOI: https://doi.org/10.1007/s10115-023-01860-3
Zareen Syed, Ankur Padia, Tim Finin, Mathews, Lisa et al. • Maryland Shared Open Access Repository (USMAI Consortium)
(2016)
In this paper we describe the Unified Cybersecurity Ontology (UCO) that is intended to support information integration and cyber situational awareness in cybersecurity systems. The ontology incorporates and integrates heterogeneous data and...
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Open Access
DOI: https://doi.org/10.13016/m2862bg1v
Vagelis Papakonstantinou • Computer law & security review
(2022)
The end of the second decade of the 21st century has been the best of times for EU's cybersecurity law and policy: Its NIS Directive has been transposed into all Member States’ national law, creating a new administrative structure at EU and...
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DOI: https://doi.org/10.1016/j.clsr.2022.105653
Saqib Saeed, Salha A. Altamimi, Norah A. Alkayyal, Ebtisam Alshehri et al. • Sensors
(2023)
This systematic literature review explores the digital transformation (DT) and cybersecurity implications for achieving business resilience. DT involves transitioning organizational processes to IT solutions, which can result in significant...
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DOI: https://doi.org/10.3390/s23156666
PMC: 10422504
Abdalmuttaleb M. A. Musleh Al-Sartawi • International Journal of Critical Infrastructures
(2020)
Security breaches are very costly in the USA, followed very closely by the Middle East. Shareholders and investors demand that their firms mitigate all kinds of risks, and it is the responsibility of the BOD to gain and maintain their confi...
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DOI: https://doi.org/10.1504/ijcis.2020.10029173
Portia Pusey, William Anthony Sadera • Journal of Digital Learning in Teacher Education
(2011)
In teacher education programs, preservice teachers learn about strategies to appropriately integrate computer-related and Internet-capable technologies into instructional settings to improve student learning. Many presume that preservice te...
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DOI: https://doi.org/10.1080/21532974.2011.10784684
Renáta Németh, Júlia Koltai • Intersections
(2023)
Natural language processing (NLP) methods are designed to automatically process and analyze large amounts of textual data. The integration of this new-generation toolbox into sociology faces many challenges. NLP was institutionalized outsid...
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DOI: https://doi.org/10.17356/ieejsp.v9i1.871
Carly D. Robinson, Michael Yeomans, Justin Reich, Chris S. Hulleman et al. • International Conference on Learning Analytics and Knowledge (LAK)
(2016)
Student intention and motivation are among the strongest predictors of persistence and completion in Massive Open Online Courses (MOOCs), but these factors are typically measured through fixed-response items that constrain student expressio...
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DOI: https://doi.org/10.1145/2883851.2883932
James D. Pustejovsky, Branimir Boguraev • Artificial Intelligence
(1993)
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DOI: https://doi.org/10.1016/0004-3702(93)90017-6
Santanu Pattanayak • Apress eBooks
(2022)
In the modern age of information and analytics, natural language processing (NLP) is one of the most important technologies out there. Making sense of complex structures in language and deriving insights and actions from it are crucial from...
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DOI: https://doi.org/10.1007/978-1-4842-8931-0_4
Fredrik Olsson • KTH Publication Database DiVA (KTH Royal Institute of Technology)
(2009)
Active learning is a supervised machine learning technique in which the learner is in control of the data used for learning. That control is utilized by the learner to ask an oracle, typically a human with extensive knowledge of the domain ...
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Sonit Singh • arXiv (Cornell University)
(2018)
With rise of digital age, there is an explosion of information in the form of news, articles, social media, and so on. Much of this data lies in unstructured form and manually managing and effectively making use of it is tedious, boring and...
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Open Access
DOI: https://doi.org/10.48550/arxiv.1807.02383
Jakob Gawlikowski, Cedrique Rovile Njieutcheu Tassi, Mohsin Ali, Jong‐Seok Lee et al. • Artificial Intelligence Review
(2023)
Abstract Over the last decade, neural networks have reached almost every field of science and become a crucial part of various real world applications. Due to the increasing spread, confidence in neural network predictions has become more a...
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DOI: https://doi.org/10.1007/s10462-023-10562-9
Abhijit S. Pandya, Robert B. Macy • CRC Press eBooks
(2021)
From the Publisher:
The addition of artificial neural network computing to traditionalpattern recognition has given rise to a new, different, and more powerful methodology that is presented in this interesting book. This is a practical gui...
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DOI: https://doi.org/10.1201/9780138744274
Igor I. Baskin, David Alan Winkler, Igor V. Tetko • Expert Opinion on Drug Discovery
(2016)
INTRODUCTION: Neural networks are becoming a very popular method for solving machine learning and artificial intelligence problems. The variety of neural network types and their application to drug discovery requires expert knowledge to cho...
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DOI: https://doi.org/10.1080/17460441.2016.1201262
Alison Carling • Sigma Press eBooks
(1992)
A background to the history of neural networks is provided in this book, in a way accessible to readers without a formal knowledge of computer science or advanced biology. It describes the major learning algorithms, the constraints of neuro...
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Chuxu Zhang, Dongjin Song, Chao Huang, Ananthram Swami et al. • ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)
(2019)
Representation learning in heterogeneous graphs aims to pursue a meaningful vector representation for each node so as to facilitate downstream applications such as link prediction, personalized recommendation, node classification, etc. This...
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Open Access
DOI: https://doi.org/10.1145/3292500.3330961