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The purpose of this paper is to present the educational computer emergency response team (EduCERT) framework, an integrated response mechanism to bolster national cybersecurity through collaborative efforts in the higher education sector. The EduCERT framework addresses this gap by enhancing cyber security and mitigating cybercrime through collaborative incident management, knowledge sharing and university awareness campaigns.

The authors propose an EduCERT framework following the design science methodology. The framework is developed based on literature and input from focus group experts. Moreover, it is grounded in the principles of the technology-organization-environment framework, organizational learning and diffusion of innovations theory.

The EduCERT has eight components: infrastructure, governance, knowledge development, awareness, incident management, evaluation and continuous improvement. The framework reinforces national cybersecurity through cooperation between universities and the National Computer Emergency Response Team. The framework has been implemented in Jordan to generate a cybersecurity foundation for higher education. Evaluating the EduCERT framework’s influence on national cybersecurity highlights the importance of adopting comprehensive cyber-security policies and controls. The framework application shows its relevance, effectiveness, adaptability and alignment with best practices.

Despite the impact of applying the framework in the Jordanian context, it is essential to acknowledge that the proposed EduCERT framework’s practical implementation may encounter challenges specific to diverse international educational environment sectors. However, framework customization for global applicability could address varied educational institutions in other countries.

Furthermore, the proposed EduCERT framework is designed with universal applicability that extends beyond the specific country’s context. The principles and components presented in the framework can serve as valuable design advice for establishing collaborative and resilient cybersecurity frameworks in educational settings worldwide. Therefore, the research enhances the proposed framework’s practical utility and positions it as an invaluable contribution to the broader discourse on global cybersecurity in academia.

This paper enhances national cybersecurity in the higher education sector, addressing the need for a more integrated response mechanism. The EduCERT framework demonstrates its effectiveness, adaptability and alignment with best practices, offering valuable guidance for global educational institutions.

The purpose of this paper is to propose a holistic cyber security implementation framework (HCS-IF) that lays out the ground for a conceptual, coherent, systematic, overarching and consolidated approach to implement cyber security strategies (CSSs).

The HCS-IF is conceptually proposed to address the actual needs that are extracted from literature review. The HCS-IF uses and integrates a set of high-level conceptual security controls, solutions, processes, entities, tools, techniques or mechanisms that are already known in the domains of information security management, software engineering and project management to address the identified needs.

The HCS-IF components and controls collectively interact and cooperate to implement CSSs. The proposed framework is compared with other related frameworks, and the results show that the HCS-IF outperforms other frameworks on most of the suggested comparison criteria.

From a practical standpoint, governments and practitioners alike stand to gain from the findings of this research. Governments who want to implement CSSs on a national level will find the proposed framework useful in overseeing cyber security implementation. Practitioners will be prepared to address the anticipated cyber security implementation challenges and the required controls needed to facilitate cyber-security implementation in a holistic overarching manner.

The authorship authentication (AA) problem is concerned with correctly attributing a text document to its corresponding author. Historically, this problem has been the focus of various studies focusing on the intuitive idea that each author has a unique style that can be captured using stylometric features (SF). Another approach to this problem, known as the bag-of-words (BOW) approach, uses keywords occurrences/frequencies in each document to identify its author. Unlike the first one, this approach is more language-independent. This paper aims to study and compare both approaches focusing on the Arabic language which is still largely understudied despite its importance.

Being a supervised learning problem, the authors start by collecting a very large data set of Arabic documents to be used for training and testing purposes. For the SF approach, they compute hundreds of SF, whereas, for the BOW approach, the popular term frequency-inverse document frequency technique is used. Both approaches are compared under various settings.

The results show that the SF approach, which is much cheaper to train, can generate more accurate results under most settings.

Numerous advantages of efficiently solving the AA problem are obtained in different fields of academia as well as the industry including literature, security, forensics, electronic markets and trading, etc. Another practical implication of this work is the public release of its sources. Specifically, some of the SF can be very useful for other problems such as sentiment analysis.

This is the first study of its kind to compare the SF and BOW approaches for authorship analysis of Arabic articles. Moreover, many of the computed SF are novel, while other features are inspired by the literature. As SF are language-dependent and most existing papers focus on English, extra effort must be invested to adapt such features to Arabic text.

In the context of information retrieval, text genre is as important as its content, and knowledge of the text genre enhances the search engine features by providing customized retrieval. The purpose of this study is to explore and evaluate the use of stylometric analysis, a quantitative analysis for the linguistics features of text, to support the task of automated text genre detection for Classical Arabic text.

Unsupervised clustering and supervised classification were applied on the King Saud University Corpus of Classical Arabic texts (KSUCCA) using the most frequent words in the corpus (MFWs) as stylometric features. Four popular distance measures established in stylometric research are evaluated for the genre detection task.

The results of the experiments show that stylometry-based genre clustering and classification align well with human-defined genre. The evidence suggests that genre style signals exist for Classical Arabic and can be used to support the task of automated genre detection.

This work targets the task of genre detection in Classical Arabic text using stylometric features, an approach that has only been previously applied to Arabic authorship attribution. The study also provides a comparison of four distance measures used in stylomtreic analysis on the KSUCCA, a corpus with over 50 million words of Classical Arabic using clustering and classification.