<abstract xmlns="http://www.w3.org/1999/xhtml">

The Russia-Ukraine war has clearly shown that critical infrastructures are prime targets for cyber operations in addition to the physical domain. In practice, in many cases, these critical infrastructures are protected by civilian cybersecurity companies in the context of a managed security service, so their defense operations must necessarily be coordinated with military defense activities. This includes among others the sharing of information classified under different classification systems (national, EU, NATO) between different actors in national cyber defense, the inclusion of appropriate civilian experts in the armed forces, and the usage of cutting-edge cybersecurity technologies (e.g. AI-enabled solutions) that are first introduced for civilian use, with military organizations only having access to them later or possibly not encountering them at all due to procurement difficulties. The main goal of this paper is to introduce the existing opportunities and obstacles to civilians’ involvement in military cyber operations in the areas of legislation, technology, and human resources from the European perspective. Moreover, the paper deals with the actual questions of cybersecurity intelligence sharing between civilian and military entities and the European Union’s actions in order to improve the overall cybersecurity posture of the region.
</abstract>

The Role of Civilian Cybersecurity Companies in Military Cyber Operations

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The main purpose of writing this article was to show how disruptive technologies, including artificial intelligence and machine learning, can be used in military operations. We also covered how the UN and other international organisations have begun to regulate this rapidly exploding field from a policy perspective. We presented some of the technologies that use AI and made suggestions for their general military application and how these technologies can be used in peacetime operations. Artificial intelligence and intelligent devices can also bring enormous benefits in the areas of command and control systems, reconnaissance and intelligence activities. We also presented issues and dilemmas related to developments in this direction, such as ethical, liability, security and information protection problems and dilemmas.
</abstract>

Possibilities of Using Artificial Intelligence in EU and UN Peacekeeping Activities

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This paper examines the ongoing trend of digitization within educational institutions, analyzing the potential opportunities that lie ahead. As educational landscapes evolve, embracing digitization offers institutions a pathway to unlock a myriad of prospects. This research explores the current state of digitization in educational settings, highlighting the opportunities that arise from the integration of digital technologies. The driving forces behind significant changes in higher education include escalating operating costs, the emergence of micro and nano degrees, the surge in online learning, the influx of digitally-native students, and the overarching wave of digital transformation. Students are increasingly leveraging digital technologies to showcase a diverse array of tools, integrating structured learning environments into the fabric of higher education teaching. This research provides a comprehensive overview of digital transformation in higher education, evaluating the potential of digitalization and forecasting its prospects in the near future. Key concepts such as digital transformation, virtual reality (VR) technology, artificial intelligence (AI), and Technology, Entertainment, Design (TED) courses are examined as practical and indispensable elements shaping the future of education. Through a meticulous analysis, it becomes evident that digitalization marks only the initial phase in a broader process wherein institutions harness new technologies not merely to replicate old tasks but to redefine educational paradigms. Furthermore, the paper emphasizes that digital transformation necessitates the infusion of new management practices capable of harnessing the full potential of information and communication technologies (ICT). The journey towards the digital transformation of educational institutions involves a profound shift in mindset, encompassing innovative approaches to teaching, learning, and administration. As institutions embrace this transformative journey, they position themselves to create enhanced value for students and forge dynamic collaborations with partners in the evolving landscape of higher education.
</abstract>

Digital Renaissance in Education: Unveiling the Transformative Potential of Digitization in Educational Institutions

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It is important to fully comprehend the critical role of the healthcare and public health sector in safeguarding the economy from various threats, including terrorism, infectious diseases, and natural disasters. The private ownership of many healthcare assets underscores the need for enhanced collaboration and information sharing between the public and private sectors. The COVID-19 pandemic has accelerated the digitalization of this sector, leading to a heightened risk of cyber threats. The increasing reliance on emerging technologies such as blockchain, the metaverse, and virtual reality is further exacerbating the cybersecurity landscape, with the projected cost of cybercrime exceeding $10 trillion in 2023 and an anticipated surge to nearly $24 trillion in the next four years. Human error remains the primary cause of cybersecurity incidents, accounting for 95% of reported cases, with insider threats contributing significantly. Despite increased cyber training and risk mitigation efforts, vulnerabilities continue to be rapidly exploited. This paper provides an in-depth analysis of cybersecurity risks in the healthcare sector, drawing on existing literature and theoretical frameworks to highlight the complex challenges in this evolving landscape.
</abstract>

Understanding Healthcare Cybersecurity Risk Management Complexity

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The literature on college attrition rates has revealed that self-efficacy and locus of control play a critical role in academic performance and retention. However, despite the importance of students’ attitudes in academic performance, there have been few studies focused on how to develop students’ self-efficacy and internal locus of control. We examined the impact of motivational book reading on the promotion of self-efficacy and locus of control by leveraging a mixed method study, analyzing quantitative and qualitative data. One hundred diverse, business students participated in the research, where they read one motivational book and wrote essays to reflect their learning and took surveys that measured the quantitative variables before and after reading the book. The analysis revealed that motivational book reading significantly increased self-efficacy and locus of control of the participants. The qualitative analysis revealed that students expressed improvement in self-efficacy and internal locus of control after reading the book. The limitations, practical implications, and future research implications are discussed in this paper.
</abstract>

Inspirational Book Reading: The Changes in Self-Efficacy and Locus of Control in Minority Students: A Mixed Method Study

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The purpose of this study is to identify whether students’ academic performance is influenced by their learning style. The research addressed students in the field of educational sciences. To collect research data, a questionnaire was applied to a number of 143 students aged between 19 and 56 years. The research data were statistically analyzed using the Kruskal Wallis Test. The statistical results indicate significant differences between students with auditory, visual and practical learning styles depending on the academic performance and the year of study. Our results can be used in the teaching-learning process by the teacher.
</abstract>

Learning Styles and Academic Performance Among Students

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In recent years, there has been a noticeable increase in the production of counterfeit goods, ranging from luxury items to products that have serious repercussions on individuals’ well-being. This article presents the contributing factors to the rise of counterfeiting and its potential socio-economic impacts, including effects on innovation, business partnerships, environmental issues, employment rates and consumers. Research in the field of counterfeiting goods involves using a diverse set of methods to analyze and understand the phenomenon.Document research, such as legal documents, and analyses from international organizations, will give us information about the types of counterfeit goods, trade routes, and market trends.
</abstract>

General Aspects Related to Counterfeiting of Material Goods

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In the rapidly advancing digital age, the surge in malware complexity presents a formidable challenge to cybersecurity efforts, rendering traditional signature-based detection methods increasingly obsolete. These methods struggle to keep pace with the swift evolution of malware, particularly with the emergence of polymorphic and metamorphic variants designed to bypass conventional detection. This study introduces a groundbreaking approach to malware detection by utilizing GPT-2, a cutting-edge language model developed by OpenAI, specifically for the purpose of feature extraction. By applying GPT-2’s deep learning capabilities to the EMBER and Drebin datasets, this research explores the model’s effectiveness in identifying malware through the intricate patterns present in binary data. Contrary to its original design for natural language processing, GPT-2’s application in this context demonstrates a significant potential for enhancing malware detection strategies. The model’s proficiency in extracting complex features from binary sequences marks a notable advancement over traditional methods, providing a more adaptive and robust mechanism for identifying malicious software. However, the study also acknowledges the challenges associated with the interpretability of deep learning models and their susceptibility to adversarial attacks, underscoring the imperative for ongoing innovation in the field of cybersecurity. This exploration into the unconventional use of GPT-2 for feature extraction in malware detection not only showcases the model’s versatility beyond language tasks but also sets a new precedent for the application of unsupervised learning models in enhancing cybersecurity defenses.
</abstract>

Harnessing GPT-2 for Feature Extraction in Malware Detection: A Novel Approach to Cybersecurity

<abstract xmlns="http://www.w3.org/1999/xhtml">

The current study is focused on the analysis of methods and means for reducing marine engine exhaust and greenhouse gases (GHGs). The research method consists in identifying equipments that have been applied in the case of small four-stroke marine engines used as emergency generators on board large ships, specifically the Cummins Qsb6.7-G16 model. The results, which were demonstrated by practical experiences of the different possible configurations for the engine studied showed high potential for reducing emissions, but the most suitable alternative is the Selective Catalytic Reduction (SCR).
</abstract>

Pollution Reduction Methods for an Emergency Diesel Generator Fitted Onboard a Large Container Vessel

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The escalating complexity and sophistication of software vulnerabilities demand innovative approaches in cybersecurity. This study introduces a groundbreaking framework, named “CodeSentry”, employing a transformer-based model for vulnerability detection in software code. “CodeSentry” leverages a finely-tuned version of the Generative Pre-trained Transformer (GPT), optimized for pinpointing vulnerable code patterns across various benchmark datasets. This approach stands apart by its remarkable computational efficiency, making it suitable for real-time applications − a significant advancement over traditional, resource-intensive deep learning models like CNNs and LSTMs. Empirical results showcase “CodeSentry” achieving an impressive 92.65% accuracy in vulnerability detection, surpassing existing state-of-the-art methods such as SyseVR and VulDeBERT. This novel methodology marks a paradigm shift in vulnerability detection, blending advanced AI with practical application efficiency.
</abstract>

The University of Virginia, Virginia, USA & Capitol Technology University

Codesentry: Revolutionizing Real-Time Software Vulnerability Detection With Optimized GPT Framework

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Enhancing software quality and security hinges on the effective identification of vulnerabilities in source code. This paper presents a novel approach that combines pattern recognition training with cloze-style examination techniques in a semi-supervised learning framework. Our methodology involves training a language model using the SARD and Devign datasets, which contain numerous examples of vulnerable code. During training, specific code sections are deliberately obscured, challenging the model to predict the hidden tokens. Through rigorous empirical testing, we demonstrate the effectiveness of our approach in accurately identifying code vulnerabilities. Our results highlight the significant advantages of employing pattern recognition training alongside cloze-style questioning, leading to improved accuracy in detecting vulnerabilities in source code.
</abstract>

Codeguard: Utilizing Advanced Pattern Recognition in Language Models for Software Vulnerability Analysis

AHEAD OF PRINT

Volume 29 (2024): Issue 1 (March 2024)

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Land Forces Academy Review

This publication aims at disseminating the most outstanding results of scientific research obtained by the teaching staff and researchers belonging to higher education community. The Land Forces Academy Review is a double blind peer-review scientific publication. It disseminates scientific research activity outcomes obtained by members of the teaching staff and by researchers within national and international higher education institutions, in the following fields: Military Sciences, Social-Behavioural Sciences, Management and Economics and Technical Sciences.  The Land Forces Academy Review does not have article processing charges (APC`s) nor article submission charges.   The Land Forces Academy Review has became a landmark the Land Forces Academy. By proposing a diversified structure, the publication contributes to the development of cooperation with other military and civilian higher education institutions, from the country and abroad. The publication is issued quarterly: March, June, September and December.   Why subscribe and read:    source of high quality research from Romania as well as from other parts of the world;  designed to facilitate the exchange of ideas between researchers from different countries;  excellent articles authored by researchers from all over the world.    Why submit:    relatively fast, fair and constructive double blind peer-review provided by two international specialists;  as far as the speed of publication is concerned, The Land Forces Academy Review offers a fast publication schedule whilst maintaining rigorous review standards;  what makes The Land Forces Academy Review distinct from the vast majority of existing military journals is its focus on scientific innovation relevance.  Rejection Rate    44%  Plagiarism Policy  The editorial board is participating in a growing community of Similarity Check System's users in order to ensure that the content published is original and trustworthy. Similarity Check is a medium that allows for comprehensive manuscripts screening, aimed to eliminate plagiarism and provide a high standard and quality peer-review process.  Archiving  Sciendo archives the contents of this journal in Portico - digital long-term preservation service of scholarly books, journals and collections. 