The explosion of data volume in the digital age has completely changed the corporate and industrial environments. In-depth analysis of large datasets to support strategic decision-making and innovation is the main focus of this paper’s exploration of big data management engineering. A thorough examination of the basic elements and approaches necessary for efficient big data use—data collecting, storage, processing, analysis, and visualization—is given in this paper. With real-life case studies from several sectors to complement our exploration of cutting-edge methods in big data management, we present useful applications and results. This document lists the difficulties in handling big data, such as guaranteeing scalability, governance, and data quality. It also describes possible future study paths to deal with these issues and promote ongoing creativity. The results stress the need to combine cutting-edge technology with industry standards to improve decision-making based on data. Through an analysis of approaches such as machine learning, real-time data processing, and predictive analytics, this paper offers insightful information to companies hoping to use big data as a strategic advantage. Lastly, this paper presents real-life use cases in different sectors and discusses future trends such as the utilization of big data by emerging technologies.

In this paper, we present approaches to generating random numbers, along with potential applications. Rather than trying to provide extensive coverage of several techniques or algorithms that have appeared in the scientific literature, we focus on some representative approaches, presenting their workings and properties in detail. Our goal is to delineate their strengths and weaknesses, as well as their potential application domains, so that the reader can judge what would be the best approach for the application at hand, possibly a combination of the available approaches. For instance, a physical source of randomness can be used for the initial seed; then, suitable preprocessing can enhance its randomness; then, the output of preprocessing can feed different types of generators, e.g., a linear congruential generator, a cryptographically secure one and one based on the combination of one-way hash functions and shared key cryptoalgorithms in various modes of operation. Then, if desired, the outputs of the different generators can be combined, giving the final random sequence. Moreover, we present a set of practical randomness tests that can be applied to the outputs of random number generators in order to assess their randomness characteristics. In order to demonstrate the importance of unpredictable random sequences, we present an application of cryptographically secure generators in domains where unpredictability is one of the major requirements, i.e., eLotteries and cryptographic key generation.

Background: Blockchain technology can transform military operations, increasing security and transparency and gaining efficiency. It addresses many problems related to data security, privacy, communication, and supply chain management. The most researched aspects are its integration with emerging technologies, such as artificial intelligence, the IoT, application in uncrewed aerial vehicles, and secure communications. Methods: A systematic review of 43 peer-reviewed articles was performed to discover the applications of blockchain in defense. Key areas analyzed include the role of blockchain in securing communications, fostering transparency, promoting real-time data sharing, and using smart contracts for maintenance management. Challenges were assessed, including scalability, interoperability, and integration with the legacy system, alongside possible solutions, such as sharding and optimized consensus mechanisms. Results: In the case of blockchain, great potential benefits were shown in enhancing military operations, including secure communication, immutable record keeping, and real-time integration of data with the IoT and AI. Smart contracts optimized resource allocation and reduced maintenance procedures. However, challenges remain, such as scalability, interoperability, and high energy requirements. Proposed solutions, like sharding and hybrid architecture, show promise to address these issues. Conclusions: Blockchain is set to revolutionize the efficiency and security of the military. Its potential is enormous, but it must overcome scalability, interoperability, and integration issues. Further research and strategic adoption will thus allow blockchain to become one of the cornerstones of future military operations.

This research examines the cognitive and psychological mechanisms underlying young adults’ reactions to ESG-labeled online advertisements, specifically resistance to persuasion and purchase intention. Based on dual-process theories of persuasion and digital literacy theory, we develop and test a structural equation model (SEM) of perceived greenwashing, online advertising literacy, source credibility, persuasion knowledge, and advertising skepticism as predictors of behavioral intention. Data were gathered from 690 Greek consumers between the ages of 18–35 years through an online survey. All the direct effects hypothesized were statistically significant, while advertising skepticism was the strongest direct predictor of purchase intention. Mediation tests indicated that persuasion knowledge and skepticism partially mediated perceptions of greenwashing, literacy, and credibility effects, in favor of a complementary dual-route process of ESG message evaluation. Multi-group comparisons revealed significant moderation effects across gender, age, education, ESG familiarity, influencer trust, and ad-avoidance behavior. Most strikingly, women evidenced stronger resistance effects via persuasion knowledge, whereas younger users and those with lower familiarity with ESG topics were more susceptible to skepticism and greenwashing. Education supported the processing of source credibility and digital literacy cues, underlining the contribution of informational capital to persuasion resilience. The results provide theoretical contributions to digital persuasion and resistance with practical implications for marketers, educators, and policymakers seeking to develop ethical ESG communication. Future research is invited to broaden cross-cultural understanding, investigate emotional mediators, and incorporate experimental approaches to foster consumer skepticism and trust knowledge in digital sustainability messages.

SCADA systems monitor critical industrial, energy and other physical infrastructures in order to detect malfunctions, issue alerts and, in many cases, propose or even take remedial actions. However, due to their attachment to the Internet, SCADA systems are, today, vulnerable to attacks such as, among several others, interception of data traffic, malicious modifications of settings and control operations data, malicious modification of measurements and infrastructure data and Denial-of-Service attacks. Our research focuses on strengthening SCADA systems with cryptographic methods and protection mechanisms with emphasis on data and messaging encryption and device identification and authentication. The limited availability of computing power and memory in sensors and embedded devices deployed in SCADA systems make render cryptographic methods with higher resource requirements, such as the use of conventional public key cryptography such as RSA, unsuitable. We, thus, propose Elliptic Curve Cryptography as an alternative cryptographic mechanism, where smaller key sizes are required, with lower resource requirements for cryptographic operations. Accordingly, our approach integrates Modbus, a commonly used SCADA communication protocol, with Elliptic Curve Cryptography. We have, also, developed an experimental set-up in order to demonstrate the performance of our approach and draw conclusions regarding its effectiveness in real SCADA installations.