Convergence Of Information Technology Research Articles

Comparative Analysis of Classification Methods and Suitable Datasets for Protocol Recognition in Operational Technologies

The interconnection of Operational Technology (OT) and Information Technology (IT) has created new opportunities for remote management, data storage in the cloud, real-time data transfer over long distances, or integration between different OT and IT networks. OT networks require increased attention due to the convergence of IT and OT, mainly due to the increased risk of cyber-attacks targeting these networks. This paper focuses on the analysis of different methods and data processing for protocol recognition and traffic classification in the context of OT specifics. Therefore, this paper summarizes the methods used to classify network traffic, analyzes the methods used to recognize and identify the protocol used in the industrial network, and describes machine learning methods to recognize industrial protocols. The output of this work is a comparative analysis of approaches specifically for protocol recognition and traffic classification in OT networks. In addition, publicly available datasets are compared in relation to their applicability for industrial protocol recognition. Research challenges are also identified, highlighting the lack of relevant datasets and defining directions for further research in the area of protocol recognition and classification in OT environments.

Energy 4.0: AI-enabled digital transformation for sustainable power networks

The exponential rise of green technology has changed several industries, including the energy business, especially the power sector. These advances have transformed power generation and distribution. AI, machine learning, computer vision, blockchain, and the internet-of-things (IoTs) have advanced significantly in recent years. These advances might transform the energy business, expanding its uses. This concise yet comprehensive analysis examines energy and power systems from an eco-friendly perspective, shedding light on emerging research trends. The increasing use of renewable energy sources necessitates infrastructure restructuring, opening up the potential for grid development and AI for intermittent and distributed generation. The integration of AI, IoT, and blockchain technology into energy and power systems offers potential opportunities to improve efficiency, sustainability, and dependability. This study conducts a comprehensive examination of application-specific research to investigate the present state-of-the-art and limits of various technologies, employing a thorough approach. Within this particular context, the article emphasizes the importance of implementing a complete policy and planning framework in order to support a significant and efficient shift towards advanced grid systems. The convergence of AI, information and communication technology (ICT), and energy systems offers unparalleled prospects for influencing the trajectory of energy generation, distribution, and consumption in the future. This work makes a valuable contribution to the wider academic discussion around the utilization of digital transformation in order to create sustainable and intelligent energy ecosystems. It achieves this by integrating insights from several fields.

Using Ensemble Learning for Anomaly Detection in Cyber–Physical Systems

The swift embrace of Industry 4.0 paradigms has led to the growing convergence of Information Technology (IT) networks and Operational Technology (OT) networks. Traditionally isolated on air-gapped and fully trusted networks, OT networks are now becoming more interconnected with IT networks due to the advancement and applications of IoT. This expanded attack surface has led to vulnerabilities in Cyber–Physical Systems (CPSs), resulting in increasingly frequent compromises with substantial economic and life safety repercussions. The existing methods for the anomaly detection of security threats typically use simple threshold-based strategies or apply Machine Learning (ML) algorithms to historical data for the prediction of future anomalies. However, due to the high levels of heterogeneity across different CPS environments, minimizing the opportunities for transfer learning, and the scarcity of real-world data for training, the existing ML-based anomaly detection techniques suffer from a poor predictive performance. This paper introduces a hybrid anomaly detection approach designed to identify threats to CPSs by combining the signature-based anomaly detection typically utilized in IT networks, the threshold-based anomaly detection typically utilized in OT networks, and behavioural-based anomaly detection using Ensemble Learning (EL), which leverages the strengths of multiple ML algorithms against the same dataset to increase the accuracy. Multiple public research datasets were used to validate the proposed approach, with the hybrid methodology employing a divide-and-conquer strategy to offload the detection of certain cyber threats to computationally inexpensive signature-based and threshold-based methods using domain knowledge to minimize the size of the behavioural-based data needed for ML model training, thus achieving a higher accuracy over a reduced timeframe. The experimental results showed accuracy improvements of 4–7% over those of the conventional ML classifiers in performing anomaly detection across multiple datasets, which is particularly important to the operators of CPS environments due to the high financial and life safety costs associated with interruptions to system availability.

How do technology convergence and expansibility affect information technology diffusion? Evidence from the internet of things technology in China

Information technology diffusion (ITD) is essential for promoting the sustainable development of technologies and helping technology owners gain a competitive advantage. The web-based development of technology and the digital transformation needs of multidisciplinary markets simultaneously drive the increasing convergence and expansibility of information technology (IT). However, whether these two technological characteristics can contribute to the diffusion of early-stage IT and how they influence the further diffusion of IT that has already diffused on a large scale are yet to be thoroughly investigated. We argue that the impact of technology convergence on ITD is heterogeneous when distinguishing between low- and high-ITD scenarios, as is technology expansibility. Our quantile regression estimates use a dataset about Internet of Things (IoT) patents authorized by the Chinese Patent Office from 2009 to 2019. The results show that increased technology convergence benefits ITD in high-ITD scenarios but does not affect ITD in low-ITD scenarios. Technology expansibility negatively impacts ITD in high-ITD scenarios and positively impacts ITD in low-ITD scenarios. This study broadens the theoretical paradigm of “technological characteristics and ITD” from the domain perspective. It inspires information technology owners to formulate sustainable strategies related to ITD according to technology convergence and expansibility.

Emerging Perspectives on the Application of Recommender Systems in Smart Cities

Smart cities represent the convergence of information and communication technologies (ICT) with urban management to improve the quality of life of city dwellers. In this context, recommender systems, tools that offer personalised suggestions to city dwellers, have emerged as key contributors to this convergence. Their successful application in various areas of city life and their ability to process massive amounts of data generated in urban environments has expedited their status as a crucial technology in the evolution of city planning. Our methodology included reviewing the Web of Science database, resulting in 130 articles that, filtered for relevancy, were reduced to 86. The first stage consisted of carrying out a bibliometric analysis with the objective of analysing structural aspects with the SciMAT tool. Secondly, a systematic literature review was undertaken using the PRISMA 2020 statement. The results illustrated the different processes by which recommendations are filtered in areas such as tourism, health, mobility, and transport. This research is seen as a significant breakthrough that can drive the evolution and efficiency of smart cities, establishing a solid framework for future research in this dynamic field.

ЭФФЕКТИВНОСТЬ АВТОМАТИЗИРОВАННОГО УПРАВЛЕНИЯ ТРАНСПОРТНЫМИ СРЕДСТВАМИ В ТРАМВАЙНЫХ СИСТЕМАХ

The intellectualization of water transport is accompanied by an expansion of the landscape of threats to transport security, caused by the characteristics and weaknesses of the technologies being introduced, which are the convergence of information and telecommunication technologies, automated and automatic control technologies and artificial intelligence. The peculiarity of these technologies is working with large volumes of information. Violation of the security of information processed in intelligent systems of water transport (illegal access, modification, deletion and similar unauthorized influence) causes a violation of transport security and, as a consequence, the security of critical information infrastructure and the country’s critical infrastructure, national security. Convergent technologies used in intelligent transport systems are characterized by multiple and poorly formalized manifestations of the consequences of threats. The article presents a model for assessing the risks of information security of intelligent water transport systems, based on the methods of the theory of fuzzy sets and fuzzy logic, the use of which makes it possible to take into account the above-mentioned features of the technologies being implemented. The hierarchical structure of the model and the use of fuzzy set theory and fuzzy logic methods make it possible to adapt the model to various risk criteria, types of input data and the level of detail of risk analysis. For the presented model, a methodology for assessing information security risks has been developed and an example of risk calculation is given. The developed model and methodology are intended to build an information security risk management system for autonomous shipping, implementing technologies of hybrid (augmented, extended) intelligence, providing for the use of artificial intelligence controlled by people.

НЕЧЕТКАЯ СИСТЕМА ОЦЕНКИ РИСКОВ ИНФОРМАЦИОННОЙ БЕЗОПАСНОСТИ ИНТЕЛЛЕКТУАЛЬНЫХ СИСТЕМ ВОДНОГО ТРАНСПОРТА

The intellectualization of water transport is accompanied by an expansion of the landscape of threats to transport security, caused by the characteristics and weaknesses of the technologies being introduced, which are the convergence of information and telecommunication technologies, automated and automatic control technologies and artificial intelligence. The peculiarity of these technologies is working with large volumes of information. Violation of the security of information processed in intelligent systems of water transport (illegal access, modification, deletion and similar unauthorized influence) causes a violation of transport security and, as a consequence, the security of critical information infrastructure and the country’s critical infrastructure, national security. Convergent technologies used in intelligent transport systems are characterized by multiple and poorly formalized manifestations of the consequences of threats. The article presents a model for assessing the risks of information security of intelligent water transport systems, based on the methods of the theory of fuzzy sets and fuzzy logic, the use of which makes it possible to take into account the above-mentioned features of the technologies being implemented. The hierarchical structure of the model and the use of fuzzy set theory and fuzzy logic methods make it possible to adapt the model to various risk criteria, types of input data and the level of detail of risk analysis. For the presented model, a methodology for assessing information security risks has been developed and an example of risk calculation is given. The developed model and methodology are intended to build an information security risk management system for autonomous shipping, implementing technologies of hybrid (augmented, extended) intelligence, providing for the use of artificial intelligence controlled by people.

Application of Structural Equation Modelling to Cybersecurity Risk Analysis in the Era of Industry 4.0

In the current digital transformation to Industry 4.0, the demands on the ability of countries to react responsibly and effectively to threats in the field of cyber security (CS) are increasing. Cyber safety is one of the pillars and concepts of Industry 4.0, as digitization brings convergence and integration of information technologies (IT) and operational technologies (OT), IT/OT systems, and data. Collecting and connecting a large amount of data in smart factories and cities poses risks, in a broader context for the entire state. The authors focus attention on the issue of CS, where, despite all digitization, the human factor plays a key role—an actor of risk as well as strengthening the sustainability and resilience of CS. It is obvious that in accordance with how the individuals (decision-makers) perceive the risk, thus they subsequently evaluate the situation and countermeasures. Perceiving cyber threats/risks in their complexity as a part of hybrid threats (HT) helps decision-makers prevent and manage them. Due to the growing trend of HT, the need for research focused on the perception of threats by individuals and companies is increasing. Moreover, the literature review points out a lack of methodology and evaluation strategy. This study presents the results of the research aimed at the mathematical modelling of risk perception of threats to the state and industry through the disruption of CS. The authors provide the developed factor model of cyber security (FMCS), i.e., the model of CS threat risk perception. When creating the FMCS, the researchers applied SEM (structural equation modelling) and confirmatory factor analysis to the data obtained by the implementation of the research tool (a questionnaire designed by the authors). The pillars and sub-pillars of CS defined within the questionnaire enable quantification in the perception of the level of risk of CS as well as differentiation and comparison between the analyzed groups of respondents (students of considered universities in SK and CZ). The convergent and discriminant validity of the research instrument is verified, and its reliability is confirmed (Cronbach’s alpha = 0.95047). The influence of the individual pillars is demonstrated as significant at the significance level of α = 5%. For the entire research set N = 964, the highest share of risk perception of CS threats is achieved by the DISRIT pillar (disruption or reduction of the resistance of IT infrastructure).

Cyberbiosecurity Workforce Preparation

Cyberbiosecurity is an emerging field at the convergence of life sciences and the digital world. As technological advances improve operational processes and expose them to vulnerabilities in agriculture and life sciences, cyberbiosecurity has become increasingly important for addressing contemporary concerns. Unfortunately, at this time, educational opportunities for cyberbiosecurity workforce preparation are limited. Stakeholders’ perceptions may help guide cyberbiosecurity workforce preparation efforts and bridge the gap from the classroom to the field. Toward this end, we identified stakeholders in education, private industry, and state agencies in Virginia and sought their input through both an online survey and focus groups. Findings suggest limited awareness and understanding of cyberbiosecurity. Results indicate that both formal and non-formal learning components—including short modules and comprehensive standalone courses—are important for cyberbiosecurity education programming. Stakeholders tied potential success of education programming to systems thinking and collaborative designs. Moreover, results reveal insights into concerns at the convergence of information technology (IT) and operational technology (OT), which is central to effective workforce preparation for today’s agriculture and life sciences professionals. Continuous interdisciplinary collaboration and academia-industry partnerships will be critical for developing robust cyberbiosecurity education and securing the future of agriculture.

Research on Sentiment Analysis of Tourism Review in The West Lake Scenic Area

With the advent of the digital tourism era, the convergence of information technology and tourism resources has become pervasive, with tourists relying on Internet-based tools as an essential part of their travel experience. In this study, we select the tourism reviews of The West Lake Natural Scenic Area as our research sample and conduct an in-depth analysis of its current situation through the sentiment analysis. A total of 3,376 data points related to reviews on Hangzhou’s West Lake Scenic Area was extractedtrip website using the “Octopus” web crawler software. After preprocessing, this study employed word frequency analysis, generation of word clouds, and other data visualization charts to analyze ROST EA and micro. Additionally, the LDA thematic clustering algorithm and SnowNLP sentiment analysis were utilized. The findings revealed that overall, tourists predominantly expressed positive emotions towards The West Lake Scenic Area compared to negative emotions. Positive sentiments primarily stemmed from factors such as the natural beauty of The West Lake, management practices, service quality, and charges. Furthermore, different tourists exhibited varying emotional tendencies.

Understanding the Landscape of Cyberbiosecurity for Integrative Educational Programming

Highlights Alignment of terminology and community building are crucial in cyberbiosecurity. Agriculture and life sciences in a digital age present unconventional challenges. Data and digital literacy are baseline skills for integrative cyberbiosecurity education programming. Cyberbiosecurity education framework offers a foundation for intentional, integrative programming efforts. Abstract. As an emerging and interdisciplinary field at the nexus of digital technologies and agriculture and life sciences (ALS), the integration of cyberbiosecurity education for professional training and skills development remains challenging. Educational practices and related workforce development efforts associated with cyberbiosecurity may be best generalized as pseudo-shadow education, occurring outside standardized practice and lacking known ‘best practice’ to mimic. The current state of cyberbiosecurity education reflects a lack of sequenced and developed knowledge, values, judgments, and ways of thinking, which serve as windows into the underlying cultures of a disciplinary field. Coupled with this gap, the continuous deployment and convergence of information technology (IT) and operational technology (OT) within ALS creates new vulnerabilities that are unfamiliar to the workforce. These vulnerabilities expose critical ALS infrastructures to cyber-attacks and terrorism and hold significant consequences for the bioeconomy. Securing the bioeconomy and preventing negative multiplier effects in other related sectors depend on adequate cyberbiosecurity education programming and workforce development. This exploratory report of current realities and future prospects provides insights into integrative cyberbiosecurity education programming for workforce development. The study explicates underlying concerns to be addressed in developing integrative cyberbiosecurity education for professionals in agriculture and life sciences and suggests an expandable framework to facilitate workforce development programming. Concerns to address regarding the creation of educational programming in cyberbiosecurity include alignment in definition, cross-boundary community building, the peculiar dynamics of the cyberbiosecurity threat landscape, and baseline requirements for cyberbiosecurity education and practice. Keywords: Agriculture and life sciences, Bioeconomy, Cyberbiosecurity, Education and workforce development, Threat landscape.

From Mathematical Theory of Communication to Network Society: a Sociological Transformation

An increasing pace of innovation in telecommunications, information technology has facilitated our society’s transition into what is called the “Information Age”. This work is intended to offer a means of understanding current directions in digital innovation. In 1948, the general theory for electronic communications (Shannon 1948), contributed to a substantial reorganization of our society; some fifty years later, Castells attempts to grasp the relationships between emerging technical, economic, political and cultural trends and helps us understand the processes of change triggered by the convergence of information and communication technologies (ICTs). In this work, starting from the interdisciplinary literature, the main theoretical and practical contributions leading to technological convergence are investigated in order to open a window on the contemporary landscape in semantic web, algorithmic reasoning and social intelligence (Esposito 2022). The resulting framework, although due to the dynamism of the phenomena under consideration, is not meant to be an exhaustive analysis of the relationship between digital tools and society, it rigorously summarizes many of the major technical and social issues open today and, in view of the future expansion of the ICT ecosystem, underscores the urgent need for conscious citizen participation in the information society.

Research on Financial Technology for High-Quality Economic Development

The convergence of information technology and the financial industry has led to the rapid development of financial technology. The main content of this paper is to introduce the importance of the background of financial technology to the economy, and to elaborate the significance of this research. Therefore, we put forward two main problems. The first problem is the problems faced by financial technology in the current development, among which there are three results. The results of our research are the imperfect application of science and technology in financial institutions, the homogenization of financial service functions, and the lack of application-oriented professionals, which are mainly problems faced in the current development. We first discussed what is financial economy, and then discussed the main issues. Around this issue, we gave three conclusions: 1) Promote the deep integration of finance and technology; 2) improve and build the regulatory system of financial technology; 3) deeply integrate the development of financial technology and give play to differentiated competitive advantages.

Wearable brain-computer interface technology and its application

Wearable Brain-Computer Interfaces (BCIs) signify a critical evolution in human-machine communication, driven by the convergence of neuroscience, engineering, and information technology. With applications that span across industrial, medical, and recreational domains, BCIs hold potential to redefine our interaction with the technological landscape. This manuscript elucidates this transformative juncture, bifurcating into passive and active BCIs. In passive BCIs, innovations leveraging Virtual Reality (VR) and Augmented Reality (AR) are delineated, progress has been demonstrated in the classification of passively induced emotional signals, highlighting the emergence of hands-free control systems like quadcopter control and industrial inspections. The discourse on active BCIs unveils advancements such as real-time handwriting and speech decoding, driver drowsiness detection, and emotion recognition, aided by machine learning techniques. Despite groundbreaking progress, challenges in algorithm optimization, adaptability, multimodal signal complexity, and ethics persist. Future directions emphasize the potential of deep learning and multimode input signals collaboration. The manuscript underscores the societal implications, particularly in rehabilitation, communication, and entertainment. The review, therefore, serves as both an appraisal and a roadmap for the burgeoning field of wearable BCIs, underlining its role as a pathway to enhance human capabilities and quality of life.

Revolutionizing Energy Harvesting: Solar Cell Integration with Radio Waves for AI, IT, and Business Applications

The dynamic convergence of solar cell technologies, radio waves, information technology (IT), artificial intelligence (AI), and business applications is examined in this study. The combination of these technological components has created a diverse array of innovative opportunities that provide cost-effective, environmentally friendly, and game-changing solutions for a range of businesses. We start by exploring the basic ideas behind solar cells, demonstrating their ability to transform light from the sun into electrical energy, and looking at the various kinds of solar cells and how they work together to gather energy. With uses ranging from off-grid, rural locations to space exploration and residential and commercial installations, solar cells have emerged as key players in the shift to clean, renewable energy sources. Next, we delve into the world of radio waves, which are essential to radar systems, wireless communication, remote sensing, and other fields. We clarify the various uses of radio waves and the difficulties they pose, paving the way for their cooperation with solar cell technology. The combination of radio waves with solar cells opens up new opportunities for business, IT, and artificial intelligence applications. With this connection, off-grid communication networks may be made more sustainable and wireless devices and sensors can be installed in remote or energy-constrained areas. There could be a huge impact on AI-driven applications such as Internet of Things (IoT), smart cities, precision agriculture, and remote data collection. Integration of solar-powered radio wave technology improves sustainability, resilience, and connectedness in the field of information technology. It enables companies to improve supply chain operations, lower energy costs, operate profitably in isolated or disaster-prone places, and support sustainable practices. Among the noteworthy trends influencing the IT sector are edge computing and digital inclusion. We also examine the significant effects of solar-powered radio wave technologies on the business sector. It increases supply chain optimization, energy efficiency, environmental monitoring, and remote monitoring and control. Key themes in this environment include resilience, scalability, and sustainability. Businesses are looking for creative ways to adapt to changing customer demands and legal obligations.

Designing next-generation cyber-physical systems: Why is it an issue?

Cyber-physical systems (CPSs) are seen as one of the tangible results of the convergence of advanced information technology, nanotechnology, biotechnology, cognitive science, and social science in addition to conventional systems science, engineering, and technologies. Designing next-generation cyber-physical systems (NG-CPSs) is a challenging matter for abundant reasons. It is not possible to consider all reasons and to address their interplays simultaneously in one paper. Therefore, this position paper elaborates only on a selected number of topical issues and influential factors. The author claims that the shift of the paradigm of CPSs and the uncertainty related to the paradigmatic systems features of NG-CPSs are among the primary reasons. Since the future of CPSs will be influenced strongly by their intellectualization, adaptation/evolution, and automation, these aspects are also addressed. It is argued that interaction and cooperation with NG-CPSs should be seen from a multi-dimensional perspective and that socialization of NG-CPSs needs more attention in research. The need for aggregation, management, and exploitation of the growing amount of synthetic systems knowledge produced by smart CPSs is seen by the author as an important emerging concern.

A hybrid cyber defense framework for reconnaissance attack in industrial control systems

The convergence of information technology (IT) and operation technology (OT) has made Industrial Control Systems (ICS) a popular target for cyberattacks in recent years. Unlike traditional networks, enhancing availability is the ICS network's top priority rather than confidentiality in the CIA scheme. We propose a bio-inspired adaptive defense framework based on dissimilar redundancy, diversity, and adaptive defense strategies to achieve this aim. The proposed mechanism mixed optimal network shuffling and cyber deception techniques to maximise the time attackers spend on the decoys. Besides, to provide an extra layer of protection for system availability, we introduce dual heterogeneous subnets in the proposed framework that could be regenerated once compromised. We evaluate the performance of the proposed defense framework in a typical industrial manufacturing network using an SDN-based platform and test the defense framework in various scenarios. Compared with previous research, the simulation shows a considerable improvement in defense performance in the adaptive defense mode.

La Encrucijada Ética de la Recopilación de Datos Personales

In the present day, we find ourselves immersed in an unprecedented technological revolution, driven by the convergence of artificial intelligence, information and communication technologies (ICT), big data analytics, cloud infrastructure, machine learning, and the Internet of Things (IoT). This transformation fundamentally redefines the interaction with information, services, and decision-making. Transparency emerges as a fundamental principle, demanding authenticity, genuine value, and integrity from brands and companies.We are witnessing a paradigm shift in the relationship between people and technology, from artificial intelligence to the Internet of Things IoT, reshaping the way we live, work, and communicate. Society is undergoing a complete digital transformation, reshaping entire sectors and shaping a new digital economy.Artificial intelligence and ICT are building an interconnected society, altering social dynamics, citizen participation, and the way information is consumed. This rapid introduction of technologies challenges traditional structures, demanding adaptability at both individual and organizational levels.In 2024, ethics in data management becomes a crucial pillar to cultivate trust. As privacy, equity in access to technology, and data security become hot topics, attention focuses on implementing ethical principles such as fairness, confidentiality, clarity, and responsibility.The focus on personalized adaptation, along with data privacy and security, stands out as a priority in 2024. While personalization is sought, transparency in data acquisition and usage becomes imperative for companies. The year is proclaimed as “the year of data,” where how brands use their data will make the difference between thriving and perishing.In terms of general figures and data, the amount of information produced and consumed globally is expected to double by 2025, reaching 97 zettabytes. The strategic relevance of data is highlighted, with 87 % of advertisers considering data their most underutilized asset.The percentage of valuable data with potential for analysis has grown from 22 % to 37 % between 2012 and 2020, consolidating the perception that data is the new gold mine in the digital business realm. The big data market is currently valued at $138,9 billion and is still growing.Industry 4,0 increasingly depends on the adoption of big data and artificial intelligence (AI) technologies, with 48,5 % of organizations currently using data as an engine to drive innovation.In 2024, the need for data and AI to go hand in hand to harness their power is emphasized. However, most organizational structures still face challenges in effectively addressing this paradigm shift. It is anticipated that artificial intelligence and algorithms will play a significant role in determining purchasing choices, political preferences, partner selections, family planning, health management, and medical recommendations soon.Trends for 2024 include the intensification of clean data structure usage, effective implementation of these structures, and an increase in “black box” AI solutions. This refers to AI systems and machine learning models that operate hidden from human understanding, driven by complex mathematical models and high-dimensional datasets. Major technology companies are accelerating their support for AI-driven marketing.

Impact of the Combination of Probiotics and Digital Poultry System on Behavior, Welfare Parameters, and Growth Performance in Broiler Chicken.

Recently, applied technology in the form of the combination of a probiotics and a digital poultry system, with the convergence of Information and Communications Technology and farm animals, has enabled a new strategy to overcome the livestock production crisis caused by climate change, while maintaining sustainable poultry farming in terms of care, feeding, and environmental management systems for poultry. The aim of this study was to investigate the biological mechanisms of animal behavioral welfare and production improvement using the combination of a probiotics and a digital poultry system in broiler chickens. A total of 400 one-day-old male broilers (ROSS 308) were randomly divided into four treatment groups, with five replicates each (20 birds/replicate pen) in a completely randomized design: control group with a conventional poultry system without probiotics (CON), conventional poultry system with 500 ppm of probiotics (CON500), digital poultry control system without probiotics (DPCS), and digital poultry system with 500 ppm of probiotics (DPS500). All experimental animals were reared for 35 days under the same standard environmental conditions. The experimental results indicated that the animal behavioral welfare, which includes drinking, eating, locomotion, grooming, and resting, in addition to foot pads, knee burns, plumage, and gait scores, as well as the growth performance of the broiler chickens, were improved by maintaining immune function and cecal microbiota balance via interaction between the combination of a probiotics and a digital poultry system. In conclusion, it was found that the combined system showed improved broiler growth performance and animal behavioral welfare. Thus, further studies of molecular biological mechanisms by the use of such a combined system to improve the nutritional composition and quality of chicken meats are recommended.

A flexible OT testbed for evaluating on-device implementations of IEC-61850 GOOSE

The growing convergence of Information Technology and Operational Technology has enhanced communication and visibility across power grids. This, coupled with the growing use of Distributed Energy Resources in power grids, has enhanced the grid capabilities while also creating a larger attack surface for malicious actors. A common protocol vulnerable to these attacks is the IEC-61850 GOOSE protocol due to its low-latency requirements, multicast packet delivery method, and lack of encryption. In this paper, we evaluate the security implications of different hardware implementations of this protocol by contrasting device response and recovery of two commercial off-the-shelf Intelligent Electronic Devices from separate manufacturers. The cyberattacks utilized in this paper are research-established GOOSE attacks with results measured in device latency and GOOSE endpoint response success.