Security Tasks Research Articles

Peningkatan Pemahaman terhadap Peran TNI dalam Pemberdayaan Masyarakat di Daerah Perbatasan Nusa Tenggara Timur

The implementation of this community service activity is to conduct discussions aimed at increasing understanding of the duties of the TNI to assist local governments in community empowerment programs at the border of Nusa Tenggara Timur (NTT) Province. The method of writing this paper is to use a qualitative approach by reviewing various literature and discussions conducted with Korem 161/Wirasakti Kupang and Kodim 1605 Belu NTT. At the NTT border, the Border Security Task Force (Satgas Pamtas) 742/SWY TNI performs the main task of Border Security and explores the community's potential, and empowers this potential. There are many creations of this unit in "fighting poverty," namely through the five programs of the Wira Yudha House. Rumah Wira Yudha has programs in Education, Health, Love Pancasila, Entrepreneurship, and Wira Yudha Sharing to answer the needs and limitations in border villages. All these activities are full of activities based on Pancasila values.

The Impact of COVID-19 Lockdown on Security, Environment and Social Vices: Global Perspectives

The Pandemic caused by the novel coronavirus 2019 has made the governments of both developed and developing countries introduce various restrictive mechanisms in an attempt to lessen the menace and its rapid spread, Nigeria is not an exception. In Nigeria, the Federal Government restricts interstate travel, locked all offices, closed all commercial markets, and imposed a dusk to dawn curfew on the people. Security task forces were deployed across the country to enforce the restriction. Hence, this resulted in an increase in the rate of extortion and corruption among the security operatives, the volume of waste unrecycled was on the high side, ecotourism was affected as well as an increase in the occurrence of sexual assault, cyber fraud, abduction and other related vices in Nigeria. This article intends to review the security issues and social vices on the increase in Nigeria owing to the COVID 19 lockdown as well as provide possible solutions and prevent future occurrences.

Multi-objective secure task scheduling based on SLA in multi-cloud environment

The appliances that are received at a cloud data centre are a compilation of jobs (task) that might be independent or dependent on one another. These tasks are then allocated to diverse virtual machine (VM) in a scheduled way. For this task allocation, various scheduling policies are deployed with the intention of reducing energy utilization and makespan, and increasing cloud resource exploitation as well. A variety of research and studies were done to attain an optimal solution in a single cloud setting, however the similar schemes might not operate on multi-cloud environments. Here, this paper aims to introduce a secured task scheduling model in multi-cloud environment. The developed approach mainly concerns on optimal allocation of tasks via a hybrid optimization theory. Consequently, the developed optimal task allotment considers the objectives like makespan, execution time, security parameters (risk evaluation), utilization cost, maximal service level agreement (SLA) adherence and power usage effectiveness (PUE). For resolving this issue, a novel hybrid algorithm termed as rock hyraxes updated shark smell with logistic mapping (RHU-SLM) is introduced in this work. At last, the superiority of developed approach is proved on varied measures.

Using Blockchain to Track Government Fund Distribution

All along, a blockchain is a making synopsis of records, called blocks, related utilizing cryptography. Each block contains a hash of the past transaction, a timestamp, and transaction information. By plan, a blockchain is invulnerable to alteration of the data. In this, we propose a design to follow holds appointed to the public authority as they cross via the general power operation at per step. This framework utilizes blockchain improvement to remain mindful of straightforwardness and security at each development as the assets push forward. This design permits a bare essential record with all connected clients in the chain to exchange information on a piece of restricted data. The framework utilizes encryption to secure unexpected information including hash values to keep a square of exchanges a chain way that is given and checked by each center point expected to assert the conversation and save the information in an immediate plan inside the public power. The design ponders a full-check, secure and exact asset task, and overall arranging framework to assist with shaping an ethical government system.

A survey on deep learning for cybersecurity: Progress, challenges, and opportunities

As the number of Internet-connected systems rises, cyber analysts find it increasingly difficult to effectively monitor the produced volume of data, its velocity and diversity. Signature-based cybersecurity strategies are unlikely to achieve the required performance for detecting new attack vectors. Moreover, technological advances enable attackers to develop sophisticated attack strategies that can avoid detection by current security systems. As the cyber-threat landscape worsens, we need advanced tools and technologies to detect, investigate, and make quick decisions regarding emerging attacks and threats. Applications of artificial intelligence (AI) have the potential to analyze and automatically classify vast amounts of Internet traffic. AI-based solutions that automate the detection of attacks and tackle complex cybersecurity problems are gaining increasing attention. This paper comprehensively presents the promising applications of deep learning, a subfield of AI based on multiple layers of artificial neural networks, in a wide variety of security tasks. Before critically and comparatively surveying state-of-the-art solutions from the literature, we discuss the key characteristics of representative deep learning architectures employed in cybersecurity applications, we introduce the emerging trends in deep learning, and we provide an overview of necessary resources like a generic framework and suitable datasets. We identify the limitations of the reviewed works, and we bring forth a vision of the current challenges of the area, providing valuable insights and good practices for researchers and developers working on related problems. Finally, we uncover current pain points and outline directions for future research to address them.

ევროპის „მწვანე შეთანხმება“ და მისი გავლენა საქართველოს ენერგეტიკულ სექტორზე

Energy is a key field of not only economic, ecological, climatic, but also political challenges and risks of modernity. Special attention is paid to the energy sector in the context of global climate change. Increasing the use of solar, wind, hydropower, geothermal energy and biomass will reduce greenhouse gas emissions and switch to fossil fuel-based economies of clean sources. The European Union- goals to replace traditional energy with renewables - are becoming more ambitious each time. The “Global Green Agreement”, which should be the basis of the EU's economic vision, provides additional incentives for this. In the paper has been conducted an energy economic analysis of Georgian energy; Have been discussed the target indicators and characteristics of the energy sector; The most important tasks of energy security, energy saving and raising the level of energy efficiency is formulated; The directions to solve these problems are outlined in this work. Second of all, Georgia should try to engage in a series of radical, revolutionary changes known as the "4th Energy Transition." With this transition, the use of fossil fuels will be reduced to a minimum in the next 10 years, and in 2050 the correction of "carbon neutral" energies around the world is announced. The use of solar and wind energy requires backup capacities, the cheapest source of which is again hydropower. In the paper we have substantiated and analyzed the most important issues of the need to develop hydropower resources and give recommendations based on research. In our opinion, in order to deepen political and economic relations with the EU, it is important to gradually bring Georgian legislation closer to the European one, which will help establish a concrete, transparent and efficient energy market model, create an attractive and stable investment environment, develop energy resources through the development of renewable energy resources and the implementation of energy efficiency measures. On the other perspective the Green Agreement” of Europe is a long-term path to the transition to a lowcarbon economy, in accordance with the terms of the Paris Agreement. It envisions Europe as the first carbon neutral continent by 2050. To achieve this goal, the EU plans to reduce emissions by 50% by 2030 compared to 1990. Naturally, this can only be achieved through the adoption and implementation of relevant strategic documents and decisions. Accordingly, our paper discusses the main essence of the Green Agreement, the challenges associated with its implementation and its impact on the future of the Eastern Partnership, especially Georgia.

Intrusion identification using GMM-HMM for perimeter monitoring based on ultra-weak FBG arrays.

Intrusion identification has been an intractable task for perimeter security. One of the primary challenges is to possess high identification rate over a long-distance range monitoring. This paper proposes an intrusion identification scheme based on ultra-weak fiber Bragg grating (UWFBG) arrays. The scheme is acquired by the combination of a Gaussian mixture model (GMM) and a hidden Markov model (HMM). The time dependencies are obtained by the analysis of relevant sensors in UWFBG arrays from the procedure of intrusions. The features extracted from vibration signals with time dependencies are used as the input of GMM-HMM. The GMM-HMM simultaneously analyzes features and time dependencies to identify intrusion. Experimental demonstration verifies that the proposed scheme can identify three intrusions (walking, knocking and climbing) and two non-intrusions (heavy truck passing and wind blowing) with the average identification rate of 98.2%. By the comparison tests with other six classifiers, the proposed GMM-HMM scheme shows a solid performance in the integrated evaluation for intrusion identification.

A Robust Security Task Offloading in Industrial IoT-Enabled Distributed Multi-Access Edge Computing

The rapid increase in the Industrial Internet of Things (IIoT) use cases plays a significant role in Industry 4.0 development. However, IIoT systems face resource constraints problems and are vulnerable to cyberattacks due to their inability to implement existing sophisticated security systems. One way of alleviating these resource constraints is to utilize multi-access edge computing (MEC) to provide computational resources at the network edge to execute the security applications. To provide resilient security for IIoT using MEC, the offloading latency, synchronization time, and turnaround time must be optimized to provide real-time attack detection. Hence, this paper provides a novel adaptive machine learning–based security (MLS) task offloading (ASTO) mechanism to ensure that the connectivity between the MEC server and IIoT is secured and guaranteed. We explored the trade-off between the limited computing capacity and high cloud computing latency to propose an ASTO, where MEC and IIoT can collaborate to provide optimized MLS to protect the network. In the proposed system, we converted the MLS task offloading and synchronization problem into an equivalent mathematical model, which can be solved by applying Markov transition probability and clock offset estimation using maximum likelihood. Our extensive simulations show that the proposed algorithm provides robust security for the IIoT network with low latency, synchronization accuracy, and energy efficiency.

Intelligent Tracking and Navigating Moving Objects in a Smart Environment Using IoT Network

Internet of Things (IoT) constitutes the combinations of sensors, controllers, actuators, and connectivity. Tracking and navigating moving objects are crucial tasks for security as well as a secure and smart environment. By using the sensory data, location of objects can be identified then that sensory data will be transferred to controllers for the further processes. One pivot role of the system is to identify the trajectory and location of the object using the speed, velocity, acceleration, maps, etc., and this can be done by machine learning programs. Analyzing service required, prediction of the trajectory and real-world knowledge of maps or locations, To avoid the loop-carry dependency, service request parameters are dynamically changed to locate relevant virtual objects. In order to track moving items, this study provides an architecture based on IoT self-aware environment technology that facilitates the tracking and allocation of relevant virtual objects.

Региональный опыт поддержки развития сельскохозяйственной потребительской кооперации

The development of agricultural consumer cooperation in Russia is one of the main tasks of national food security. The research objective was to analyze the current state of agricultural consumer cooperation in the Lipetsk region, Altai Territory, and the Republic of Tatarstan, as well as their development prospects
 The research featured agricultural consumer cooperatives and their market environment. It was based on empirical methods, analysis, synthesis, modeling, and abstraction.
 The paper introduces various patterns of formation and development of agricultural cooperation at the regional level. In the Lipetsk region, the number of agricultural consumer cooperatives was found to increase every year. The regional three-level system for managing the development of “region – district – settlement” cooperation proved to be very effective, as did the local cooperation development institutions. The Altai territory appeared to have implemented a pilot model of agricultural consumer cooperation. This model allows cattle farmers who received financial support from the Agrostartup to sell their products to a cooperative. In the Republic of Tatarstan, agricultural consumer cooperation is based on models that are specific for each area.
 The Lipetsk region appeared to be on the cutting edge of cooperation development. The three-level management they use coordinates the efforts of local authorities and regional governments in the chain “settlement – district – region”. This integrated approach provides an effective regional system of agricultural consumer cooperation in the Russian Federation.

Investigation of information security policy violations among oil and gas employees: A security-related stress and avoidance coping perspective

Information security is one of the most crucial considerations in digitising Oil and Gas (O&G) organisations. For ensuring information security policy compliance, O&G organisations enforce heavy security requirements. The purpose of this article is to assess how O&G employees cope with stressful information security tasks and how security-related stress (SRS) is related to information security policy violations among O&G employees in developing countries. Based on the coping theory, this article develops a theoretical framework to examine O&G employees’ intention to violate information security policies. The framework is tested using a survey of 270 managers/executives from 150 Malaysian O&G organisations. The results indicated that O&G employees perceive security requirements as stressful to follow and adopt avoidance coping strategies that lead them to violate organisational information security policies. For practitioners, the study findings demonstrate the prevalence of technostress in O&G organisations and suggest alternative mechanisms to address the stressful effects of information security requirements. This article contributes to the information system security literature by testing procrastination and psychological detachment with SRS in the context of developing countries' O&G organisations’ employees and provides an understanding of how O&G employees adopt avoidance coping.

Instability of the North Korean Regime and the Residents Defection: A Plan for Enhancing the Capacity of Security Police for Their Settlement in South Korea -With a Focus on the Rank of the Security Police s Department of Service-

Purpose: Given the situation where it is expected that a plan of improvement for the North Korean refugee related support policy will be required in view of the recent incident of the North Korean defector returning to North Korea, which has become a problem in the South Korean society, the job satisfaction of the security police was surveyed based on the work area. This is because, given the situation where the security police perform various settlement related support activities as well as security tasks, which are their original duties, their job satisfaction can help improve the work efficiency and practically improve the settlement of the North Korean defectors. Method: In this study, among police officers in the security department as of 2020 who had experience in work related North Korean defectors, 100 trainees in the Police Human Resources Development Institute were surveyed via self-administration method. Among the collected survey questionnaires, 91 were selected as valid samples, excluding those whose answers were incomplete or missing. Results: First, the job satisfaction turned out to be higher as the number of employees of the police organization with which the police organization was affiliated increased, and second, the relationship between the division of work and authority and responsibility of the police working in large cities was clearer than that of the police working in small and medium cities, and as they are further classified and efficiently assigned, the commanders and superiors demonstrate a higher job satisfaction with the awareness that they are leading the staff by exam-ple rather than direct control. Conclusion: As a result of the study of this paper, the status of the North Korean defectors who are experienc-ing considerable difficulties in adapting and integrating into the South Korean society was identified, and the internal job satisfaction of the security police who are practically responsible for their settlement support was sur-veyed. Since the end of the Cold War, the status and job satisfaction of the security police have declined due to political reasons where the systemic competition between the South and the North has not surfaced, and the survey of their job satisfaction may yield a plan of improvement.

A Treatise on the Paradigm of Security Theory

Mankind, whose development has been significantly affected in the last few decades by deepening globalization processes, now faces many security problems, threats, risks and challenges. For this reason, in the 21st century, solving security problems is part of the management processes at all levels and in all areas of life of contemporary human society, not only at the state level. To be able to solve the security problems, eliminate security threats and risks and face new security challenges, adequate findings, knowledge, experience, methodological and other tools to perform its security tasks are necessary – a security theory is needed. That is why the author of the study submitted uses relevant methods of interdisciplinary scientific research and discusses the need for security theory, focusing primarily on the paradigm of security theory.

Monitoring Operational States of a Nuclear Reactor Using Seismoacoustic Signatures and Machine Learning

Abstract Monitoring nuclear reactors is an important safety and security task with growing requirements. We explore the possibility of using seismic and acoustic data for inferring the power level of an operating reactor. Continuous data recorded at a single seismoacoustic station that is located about 50 m away from a research reactor was visualized and analyzed. The data show a clear correlation between seismoacoustic features and reactor main operational states. We designed a workflow that includes two machine learning (ML) models to classify the reactor operational states (OFF, transition, and ON) and estimate reactor power levels (10%, 30%, 50%, 70%, and 90%). We applied and compared five ML algorithms for the reactor OFF-transition-ON and four approaches for the power level classification. We also compared the performance of ML models trained with seismic-only, acoustic-only, and both types of data. Five-fold cross validations were implemented to assure a thorough evaluation of the model performances. The results show the extreme boosting gradient algorithm worked best for the first model, whereas random forests performed best for the second model. Combining seismic and acoustic data leads to better performance than using a single type of data. Seismic data contributed more than acoustic data for both models. We reached an accuracy of 0.98 for reactor OFF and ON. The accuracies for the transition state and power levels are less optimal with a minimum accuracy of 0.66. However, our results suggest seismic and acoustic data contain useful information about the transition state as well as power levels. Seismic and acoustic data could be integrated with other observations to improve monitoring performance.

Malware Binary Image Classification Using Convolutional Neural Networks

The persistent shortage of cybersecurity professionals combined with enterprise networks tasked with processing more data than ever before has led many cybersecurity experts to consider automating some of the most common and time-consuming security tasks using machine learning. One of these cybersecurity tasks where machine learning may prove advantageous is malware analysis and classification. To evade traditional detection techniques, malware developers are creating more complex malware. This is achieved through more advanced methods of code obfuscation and conducting more sophisticated attacks. This can make the manual process of analyzing malware an infinitely more complex task. Furthermore, the proliferation of malicious files and new malware signatures increases year by year. As of March 2020, the total number of new malware detections worldwide amounted to 677.66 million programs. In 2020, there was a 35.4% increase in new malware variants over the previous year. This paper examines the viability of classifying malware binaries represented as fixed-size grayscale using convolutional neural networks. Several Convolutional Neural Network (CNN) architectures are evaluated on multiple performance metrics to analyze their effectiveness at solving this classification problem.

RECONOCIMIENTO FACIAL CON FINES DE SEGURIDAD PÚBLICA EN URUGUAY. ANÁLISIS DESDE LA PERSPECTIVA DE LA ORGANIZACIÓN ADMINISTRATIVA.

In recent times, ICTs have burst into force, spreading their use in multiple areas of society. The Public Administration is one of the most fertile fields for the application of these new technologies, especially as tools to fulfill the tasks of the State, among which Public Security stands out. Among the most innovative instruments that have made a place in the state organization, artificial intelligence stands out, especially tools based on biometrics, such as facial recognition, by allowing a person to be identified through the parameters of the face. A technology of these characteristics was acquired by the Ministry of the Interior to fulfill its Public Security tasks, approving a series of articles in Budget Law No. 19,924 that seek to make it possible for the Police to use it. This tool and the approved articles are the object of analysis of this paper from the perspective of the administrative organization.

Empowerment of the Marine Task Force for Safeguarding the Outer Islands to Increase Development of Maritime Potential in the Border Area, especially the North Natuna Sea

The purpose of this study is to describe the empowerment of the marine task force in carrying out the security task force for the outer islands, the authority of the role of the marine task force in maritime development, the regulatory authority for the role of the marine task force to improve the development of maritime potential in the North Natuna Sea border area. The method used is qualitative research. Analysis using data analysis techniques Soft System Methodology (SSM). The results showed that the communication of related stakeholders was well established and constructive, the efforts were made by having limited defense capabilities against attacks; supervisory ability; and the ability to prevent the transit of illegal activities. For Maritime Development in the North Natuna Sea Border Area, Assistant Dankormar Col. Mar is responsible to the Marine Corps Commander in carrying out his daily tasks. The Indonesian Navy agency in the Natuna Region to compile a Regulation on the implementation of the Marine Task Force in increasing maritime potential development

The Reshaping of Professional Discourse among Young Military Leaders during the COVID-19 Pandemic in Ukraine

The research aimed to outline the features of “new normal” communication behavior of young military leaders due to the COVID-19 pandemic influence. To study this critical problem we used some general scientific and empirical methods like literature analysis, synthesis and theoretical modelling, pedagogical experience, statistical data processing. The author found that the changes include development of closed and indirect forms, introduction of new lexical, grammatical, and stylistic units, fake information spread, misuse of information and communication technologies (ICT), periodical refusal to message with non-verbal tools. The findings show that professional discourse among young military leaders changes fast because of the COVID-19 pandemic. And the transformations involve different communication behavior, the more significant role of leaders in study group especially in the context of peer-to-peer learning, critical thinking development, independent production and comprehension of professional utterances, higher responsibility of a speaker. The experiment demonstrates that military officers and cadets are likely to cope with new “rules of the game” and they continue to carry out security tasks prioritizing discipline, considerable motivation, psychological readiness to high-risk conditions and adaptability to counteract dramatic challenges. The article is one of the early researches reviewing the features of young military leaders’ discourse and describing its current transformations. The research can contribute to developement of recommendations for professional discourse improvements and, consequently, to enhance the efficiency of professional activities of military officers.

The life, death and diversity of pro-government militias: The fully revised pro-government militias database version 2.0

This article presents version 2.0 of the Pro-Government Militias Database (PGMD). It is increasingly clear that it is untenable to assume a unified security sector, as states often rely on militias to carry out security tasks. The PGMD 2.0 provides new opportunities for studying questions such as when states rely on militias, how they chose among different types and the consequences for stability and peace. We detail how the PGMD 2.0 provides new information on the characteristics, behaviour, life cycle and organization of 504 pro-government militias across the globe between 1981 and 2014.

Сутність поняття «критична інфраструктура» з позицій національної безпеки України

At the present stage, critical infrastructure is recognized as the main component of the national economy and the basis of both government and regional policy in the context of ensuring national security. Given this, the purpose of the present study is to generalize and systematize theoretical approaches to the interpretation of the concept of «critical infrastructure»; a closer definition of the essence and content of this term from the standpoint of recovering the national economy and ensuring the national security of Ukraine. As a result of the study, it is found that the concept of «critical infrastructure» is identified with such definitions as: infrastructure; life support systems; critical infrastructure objects; vital social functions; production, goods, services, and related processes. Using a systematic approach and a classification method, the interpretation of the term «critical infrastructure», which is proposed by various scientific schools, is conditionally systematized according to the following groups: system; elements of the system; structure (network, physical, organizational); aggregate of assets; security direction; key security task on the part of the State; object of protection (administrative, legal, cybernetic); component of national infrastructure; object of public administration; information security component, etc. The article provides the authors’ own approach to the definition of the concept of «critical infrastructure» as an aggregate of objects, systems, networks that are of priority and of strategic importance for the development of a competitive national economy and provision of an adequate level of national security, the neutralized or disrupted functioning of which may harm the national interests of the State, lead to the emergence of possible threats and risks, significant expenditures and losses. It is proposed to consider critical infrastructure as a scientific category from the standpoint of effective implementation of the priority security tasks of the State; ensuring the national security; increasing the level of resilience of the functioning of systems and infrastructure objects; risk management; implementation of the State policy in the field of their protection; recovery of the national economy.