NIST Cybersecurity Framework and MITRE Cybersecurity Criteria
https://doi.org/10.1007/978-3-031-26845-8_5
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https://doi.org/10.1007/978-3-031-26845-8_5
Blockchain technology is defined as a decentralized system of distributed registers that are used to record data transactions on multiple computers. The reason this technology has gained popularity is that you can put any digital asset or t...
https://doi.org/10.1201/9780429324932
Undoubtedly, the evolution of Generative AI (GenAI) models has been the highlight of digital transformation in the year 2022. As the different GenAI models like ChatGPT and Google Bard continue to foster their complexity and capability, it’...
https://doi.org/10.1109/access.2023.3300381
This book provides the first comprehensive collection of papers that provide an integrative view on cybersecurity. This work is sorely needed in a world where cybersecurity has become indispensable to protect trust and confidence in the dig...
https://doi.org/10.1007/978-3-030-29053-5
Abstract With the extensive application of deep learning (DL) algorithms in recent years, e.g., for detecting Android malware or vulnerable source code, artificial intelligence (AI) and machine learning (ML) are increasingly becoming essent...
https://doi.org/10.1007/s12243-022-00926-7
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...
https://doi.org/10.1504/ijcis.2020.10029173
https://doi.org/10.1007/978-3-031-26845-8_1
The chapter thoroughly explores the multifaceted cybersecurity landscape's significance in safeguarding business intelligence amid rapid technological evolution. It starts with an overview of cybersecurity, defining its scope, exploring its...
https://doi.org/10.4018/979-8-3693-0839-4.ch001
Cybersecurity threats have grown exponentially, posing a heavy burden on organisations. Higher Education Institutions (HEIs) are particularly vulnerable, and their cybersecurity issues are receiving greater attention. However, existing rese...
https://doi.org/10.3390/info13040192
Advances in natural language processing (NLP) and educational technology, as well as the availability of unprecedented amounts of educationally-relevant text and speech data, have led to an increasing interest in using NLP to address the ne...
https://doi.org/10.1609/aaai.v30i1.9879
In this paper, we propose data statements as a design solution and professional practice for natural language processing technologists, in both research and development. Through the adoption and widespread use of data statements, the field ...
https://doi.org/10.1162/tacl_a_00041
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...
https://doi.org/10.1145/2883851.2883932
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 ...
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...
https://doi.org/10.48550/arxiv.1807.02383
https://doi.org/10.1017/9781139061773.020
Social researchers often apply qualitative research methods to study groups and their communications artifacts. The use of computer-mediated communications has dramatically increased the volume of text available, but coding such text requir...
https://doi.org/10.1080/13645579.2011.625764
We introduce a method to train Binarized Neural Networks (BNNs) - neural networks with binary weights and activations at run-time. At training-time the binary weights and activations are used for computing the parameters gradients. During t...
https://doi.org/10.48550/arxiv.1602.02830
This paper presents a margin-based multiclass generalization bound for neural networks that scales with their margin-normalized "spectral complexity": their Lipschitz constant, meaning the product of the spectral norms of the weight matrice...
https://doi.org/10.48550/arxiv.1706.08498
https://doi.org/10.1016/0098-1354(92)80051-a
In the past few years literature on computational civil engineering has concentrated primarily on artificial intelligence (Al) applications involving expert system technology. This article discusses a different Al approach involving neural ...
https://doi.org/10.1111/j.1467-8667.1990.tb00377.x