Security Assessment Research Articles

Assessment of Future Water Security under Climate Change: Practical Water Allocation Scenarios in a Drought-Prone Watershed in South Korea

Seomijn River Basin has numerous hydraulic structures designed to satisfy water demands and mitigate future droughts. However, the increasing water demand and export to neighboring areas cause water deficits and conflicts between water users. Therefore, practical strategies to mitigate the potential damage from climate change are essential. In this study, we aimed to propose practical strategies under climate change by examining the future water security of the Seomjin River Basin under five different water allocation scenarios referenced from the practical policies of various countries. Future climate models determined based on extreme precipitation indices of the ETCCDI were used to investigate their impact on water security, which was evaluated using unmet demand; demand coverage; reliability, resilience, and vulnerability; and aggregation index metrics. We found that prioritizing domestic and industrial water use is the optimal water security strategy, and unconditional allocation of instream flow can cause a significant water deficit for other water uses. However, prioritizing all water uses equally also proved effective under some conditions. Thus, our study highlights the importance of adaptive management and suggests that the optimal water allocation strategy lies in its flexibility in response to varying circumstances.

Development of a Cloud Computing-Based Collaboration Information System

The rapid advancement of information and communication technology has created a demand for efficient and effective information systems to facilitate collaboration among institutions. This study develops a cloud computing-based collaboration information system designed to enhance real-time communication, data management, and collaboration among users. The system comprises key modules, including collaboration management, document management, and integrated collaboration features. Testing involved various scenarios with 10 to 100 active users simultaneously, revealing that the system maintained stable performance with response times under 3 seconds for each user request. Furthermore, security assessments utilizing encryption protocols and two-factor authentication confirmed that the managed data is protected from external threats. The findings underscore the system's potential to improve collaborative efficiency while ensuring data security, making it a valuable solution for future collaborative initiatives.

New Fermatean Fuzzy Distance Metric and Its Utilization in the Assessment of Security Crises Using the MCDM Technique

The problem of insecurity is a global phenomenon that has several forms like terrorism, banditry, kidnappings, etc. Insecurity has taken hold in the Sub-Saharan Region of West Africa, especially in Nigeria, for over two decades. Nigeria’s security crisis is more pronounced in the Northern Region, with a new wave in the North-Central Region of Nigeria. It is herculean to assess insecurity in the North-Central Region of Nigeria because of the region’s fuzzy or imprecise nature of insecurity. This constitutes the rationale for deploying the Fermatean fuzzy technique to assess insecurity due to the capacity of the Fermatean fuzzy scheme to handle imprecision. To this end, a new Fermatean fuzzy distance metric is presented to evaluate insecurity in the North-Central Region of Nigeria using a multi-criteria decision-making technique. To express the logic for creating the new Fermatean fuzzy distance metric, some existing Fermatean fuzzy distance metrics are discussed, along with their drawbacks. The mathematical properties of the new technique are discussed, and the new method is applied computationally to assess insecurity in the North-Central Region of Nigeria. The data for the security assessment are collected via Fermatean fuzzy linguistic variables using the opinions of security experts and analyzed using the technique for order of preference by similarity to ideal solution, which is a commonly used multi-criteria decision-making method. Finally, the numerical validity of the new technique is expressed with comparative results, and the finding shows the benefit of the new distance approach over the existing methodologies. The outcome of the work will provide reliable traveling advisories for safe voyages within the region.

Data-Driven Dynamic Security Partition Assessment of Power Systems Based on Symmetric Electrical Distance Matrix and Chebyshev Distance

A rapid dynamic security assessment (DSA) is crucial for online preventive and restoration decision-making. The deep learning-based DSA models have high efficiency and accuracy. However, the complex model structure and high training cost make them hard to update quickly. This paper proposes a dynamic security partition assessment method, aiming to develop accurate and incrementally updated DSA models with simple structures. Firstly, the power grid is self-adaptively partitioned into several local regions based on the mean shift algorithm. The input of the mean shift algorithm is a symmetric electrical distance matrix, and the distance metric is the Chebyshev distance. Secondly, high-level features of operating conditions are extracted based on the stacked denoising autoencoder. The symmetric electrical distance matrix is modified to represent fault locations in local regions. Finally, DSA models are constructed for fault locations in each region based on the radial basis function neural network (RBFNN) and Chebyshev distance. An online incremental updating strategy is designed to enhance the model adaptability. With the simulation software PSS/E 33.4.0, the proposed dynamic security partition assessment method is verified in a simplified provincial system and a large-scale practical system in China. Test results demonstrate that the Chebyshev distance can improve the partition quality of the mean shift algorithm by approximately 50%. The RBFNN-based partition assessment model achieves an accuracy of 98.96%, which is higher than the unified assessment with complex models. The proposed incremental updating strategy achieves an accuracy of over 98% and shortens the updating time to 30 s, which can meet the efficiency of online application.

NetSentinel applications for website security

NetSentinel is an extensive web security platform designed to scan, detect and protect websites from potential vulnerabilities and cyber-threats. NetSentinel offers a proactive approach to strengthen and safeguard the website’s security, in an era where data breaches and cyber-attacks are common. The platform analyzes critical security features like SSL security validity, DNSSEC implementation, threat detection, security headers, firewall, and open ports. The main feature of the platform is the scoring mechanism, which assesses the website’s overall security to ensure it is protected from potential threats. The scoring method assigns different weights to the various security features according to their importance in the calculation. This scoring system helps users focus on the most important vulnerabilities and gives clear, practical advice on how to mitigate risks. Along with the main scoring feature the platform also includes 24 other critical security features which are Server location, Whois, DNS Data, DNS Records, Archives, Carbon Footprint, TLS Cipher Suites, TLS Security Configuration, TLS Handshake Simulation, Status, Traceroute, Blocklists, Pages, Social Tags, Headers, HSTS Check, Domain Rank, Tranco Rank, Linked Pages, Mail Services, Redirects, Security Txt, Robots Txt. NetSentinel breaks down complex information into a simple, easy to understand security score, which makes security assessment easier. It also offers clear explanations of the issues and provides step-by-step recommendations on how to fix them, helping users improve their overall security without needing advanced technical knowledge to be possessed. Using this platform, organizations can enhance their site’s ability to withstand cyber threats, ensuring data integrity and secure communication. NetSentinel helps users take control of their web security by balancing technical accuracy with easy-to-use interfaces, making it simple for everyone to stay proactive about their safety online.

Assessment and forecasting of water ecological security and obstacle factor diagnosis in the Hexi Corridor of Northwest China

The water ecological security pattern is a core factor. A scientific, accurate, and practical evaluation of water ecological security provides a theoretical basis for regional water ecological management. Using water resource data from five cities in the Hexi Corridor of Gansu Province (Jiuquan (JQ), Jiayuguan (JYG), Zhangye (ZY), Jinchang (JC), and Wuwei (WW)) from 2006 to 2021, a water ecological security evaluation index system based on the PSR (pressure-state-response) framework was constructed, covering 27 factors related to water resources, socio-economics, and the ecological environment. The main obstacle factors of water ecological security were identified using the obstacle degree model, and the grey GM(1,1) model was employed to predict water ecological security. Results indicated that the comprehensive assessment index of water ecology in the Hexi Corridor increased from 2006 to 2021, showing a transition from relatively unsafe (0.319) to basic safety and then to relatively safe (0.672). The pressure and response systems were the main limiting factors affecting water ecological security in the Hexi Corridor. After a slight decline in 2008, the overall spatial distribution continued to rise, with WW City and ZY City leading since 2016. ZY had a higher safety grade proportion (25%) compared to other areas in the Hexi region. The pressure system was the most significant obstacle to water ecological security after 2006. Prediction results indicated that the comprehensive evaluation index of water ecological security would continue to rise annually from 2022 to 2031, reaching a very safe level by 2025. The evaluation results provide a scientific basis for ecological security and risk decision-making in the study area.

Strategic Evaluation of Whistleblower Software Security in Government: ISO/IEC 25010 and AHP Method

To assess the effectiveness of software security measures in government whistleblower systems, we will utilize the ISO/IEC 25010 standard and the Analytic Hierarchy Process (AHP) methodology. Through the integration of various frameworks, our objective is to build a complete evaluation model that effectively identifies and enhances any vulnerabilities in these crucial systems. The strategy we employ combines the qualitative and quantitative evaluation capabilities of ISO/IEC 25010 and AHP, respectively, to offer a comprehensive perspective on software security performance. The results indicate substantial improvements in the security and reliability of whistleblower software, underscoring the effectiveness of our suggested evaluation technique in identifying crucial areas for refinement. Moreover, the utilization of AHP permitted the ranking of security qualities, guaranteeing focused and efficient improvements. Ultimately, the study emphasizes the significance of thorough security assessments for government whistleblower systems and verifies the effectiveness of utilizing ISO/IEC 25010 and AHP as a methodical approach to improve software security. This research enhances the ongoing endeavor to protect confidential data, fostering a more secure and reliable atmosphere for individuals who expose wrongdoing.

Security Assessment Framework for DDOS Attack Detection via Deep Learning

Internet of Things (IoT) is a broad network of actual, physical objects that can exchange data and communicate with other devices and systems over the Internet. Due to the scalability of the internet, the number of IoT users is increasing, and therefore it is vital to ensure the security of user info. Attacks such as DDoS (Distributed Denial of Service) and MitM (Man-in-the-Middle) can seriously interrupt operations and threaten the confidentiality and integrity of sensitive data. In this paper, a novel Iot based Security Assessment for intrusion using Deep Learning (ISAI-DL) technique has been proposed to identify IoT device vulnerabilities such as DDoS and MitM attacks. Initially, the features are extracted from the API documents using Bag of Words (BoW) and Term Frequency-Inverse Document Frequency (TF-IDF) techniques. In proposed ISAI-DL technique, it triggers or activates the vulnerabilities deep within target devices by sending API documents. The vulnerability is detected via the GloVe-CNN-BiLSTM Model; if the attack occurs in an IoT device, the output is classified as either DDoS, MitM, or normal. Evaluation metrics such as accuracy, recall, precision, time efficiency, F1 score, false alarm rate, and detection rate have been used to measure how effective the proposed ISAI-DL technique is. Based on a comparative investigation, the detection rate of the proposed ISAI-DL technique is 17.23%, 18.53%, and 3.24% greater than that of the existing P2ADF, HDA-IDS, and BT-TPF techniques respectively.

Geostrategic dimensions of recent food policy decisions

AbstractThis article analyzes the geostrategic dimensions in food policy responses to two recent global shocks: the Corona‐SARS‐CoV‐2 pandemic and the Russian war against Ukraine. The analysis adds to the general assessments of economic security by providing a case study of food policy and food security as an element of economic security. Strong national path dependent trajectories in food policies can be observed. However, geostrategic dimensions related to interstate interaction and political considerations in policymaking that go beyond food security are also observed.

How to benefit from the risk assessment process: Analyzing the threats that pose a threat to the national security of the state

This essay focuses on the recent evolution of national security assessments (NSAs) and national security strategies (NSSs) and evaluates how best to make use of them. While accepting that NSAs are a fairly novel development that indicates more joined-up thinking at the government level, they remain limited for two primary reasons. First, they have tended to be laden with cognitive bias, often reflecting near-term security interests and short-term thinking. Second, there is often a range of implementation problems related to moving from the assessment of risk to the realization of effective security policy. As such, truly benefitting from these risk assessments requires that policymakers counter cognitive biases and develop policy processes that are able to move from the identification of threats to a policy response.

PreSCAN: A Comprehensive Review of Pre-Silicon Physical Side-Channel Vulnerability Assessment Methodologies

Physical side-channel attacks utilize power, electromagnetic (EM), or timing signatures from cryptographic implementations during operation to retrieve sensitive information from security-critical devices. This paper provides a comprehensive review of these potent attacks against cryptographic hardware implementations, with a particular emphasis on pre-silicon leakage assessment methodologies. We explore the intricacies of cryptographic algorithms, various side-channel attacks, and the latest mitigation techniques. Although leakage assessment techniques are widely adopted in the post-silicon phase, pre-silicon leakage assessment is an emerging field that addresses the inherent limitations of its post-silicon counterpart. We scrutinize established post-silicon techniques and provide a detailed comparative analysis of pre-silicon leakage assessment across different abstraction levels in the hardware design and verification flow. Furthermore, we categorize and discuss existing pre-silicon power and electromagnetic modeling techniques for leakage detection and mitigation that can be integrated with electronic design automation (EDA) tools to automate security assessments. Lastly, we offer insights into the future trajectory of physical side-channel leakage assessment techniques in the pre-silicon stages, highlighting the need for further research and development in this critical area of cybersecurity.

Assessment of food security by using the core food security model (CFSM) in beedi workers: A case study in Murshidabad district of West Bengal

Assessment of food security by using the core food security model (CFSM) in beedi workers: A case study in Murshidabad district of West Bengal

Development of Energy Security Definition and Indexes for Sustainable Future: A Systematic Literature Review

Abstract In recent years, energy security has been gaining increasing attention worldwide, leading to a rapid growth in research and literature on the subject. As a result, many definitions regarding energy security have been proposed, reflecting the diverse perspectives and considerations involved in ensuring a secure and sustainable energy supply. There has also been a growing interest in how to measure, which has in turn led to the energy security indicators and indices development. Thus, this paper explores the definition of energy security, as well as its various dimensions and the indices employed to measure it. As a result, the scope of energy security has broadened to encompass contemporary concerns such as the environment, governance, social aspects, and technological efficiency, which were not traditionally given much consideration in the past. As a result, multiple themes have been considered, leading to a more holistic understanding and approach to energy security. This evolution has significant implications for the construction of the energy security index especially in Indonesia, as a more comprehensive set of indicators is now required to offer a comprehensive assessment of energy security within a country and provide valuable insights for energy policymakers.

Integrated assessment of water security in D-8 countries

In terms of evaluating the water security situation of communities, it is necessary to use appropriate indicators. To do this, composite indicators are especially useful for policy-making on water resources, aiming to enhance water security, implementation, and monitoring of policy actions. The composite indicators of water security at the national level reflect the country's status in terms of water resource sustainability, human well-being, and water environment. In this study, the composite indicators of water security for D-8 countries were investigated in various dimensions using the data envelopment analysis model. Moreover, the status of selected countries was examined with regard to indicators related to the dimension of water security sustainability. The results provided by the proposed model showed that Malaysia, Bangladesh, Indonesia, Nigeria, and Turkey have better positions regarding the sustainability dimension compared to other countries. The water exploitation intensity in these countries was less than 40 %. Furthermore, the level of water availability in Malaysia, Bangladesh, and Indonesia was higher than 7000 cubic meters per person. It is worth noting that Low exploitation intensity and high availability of water in a country increased its water security in terms of sustainability dimension. The low water availability and very high water exploitation in Iran, Pakistan, and Egypt exacerbate their insecurity in the sustainability dimension. Due to the importance of the sustainability dimension in determining the water security status of countries, it is recommended to take this dimension into account.

Cyber Security Assessment of An Interoperable Port Call and Voyage Optimization tool

Abstract The MISSION project aims to revolutionize maritime transport by developing a digital tool for real-time optimization of port calls and voyages, thereby reducing fuel consumption, cutting greenhouse gas emissions, and decreasing waiting times through enhanced coordination and information sharing among stakeholders. However, the security of the involved IT systems is critical to ensure safe and reliable operations. This paper introduces harborLang, a novel threat modeling language tailored for the maritime sector, built on the Meta Attack Language (MAL) framework. harborLang addresses the unique security challenges in maritime transport by enabling the modeling and mitigation of potential threats through detailed attack simulations. By integrating harborLang with the Yet Another Cybersecurity Risk Assessment Framework (YACRAF), the project enhances its risk analysis capabilities, allowing for precise threat scenarios that reflect the maritime environment’s complexities. The combined use of harborLang and YACRAF facilitates comprehensive cybersecurity risk assessments, significantly improving decision-making, operational safety, and the overall cybersecurity posture of maritime and port operations.

National security assessment for the Russian Federation

National security assessment for the Russian Federation

Legacy ICS Cybersecurity Assessment Using Hybrid Threat Modeling—An Oil and Gas Sector Case Study

As security breaches are increasingly widely reported in today’s culture, cybersecurity is gaining attention on a global scale. Threat modeling methods (TMM) are a proactive security practice that is essential for pinpointing risks and limiting their impact. This paper proposes a hybrid threat modeling framework based on system-centric, attacker-centric, and risk-centric approaches to identify threats in Operational Technology (OT) applications. OT is made up of software and hardware used to manage, secure, and control industrial control systems (ICS), and its environments include factories, power plants, oil and gas refineries, and pipelines. To visualize the “big picture” of its infrastructure risk profile and improve understanding of the full attack surface, the proposed framework builds on several threat modeling methodologies: PASTA modeling, STRIDE, and attack tree components. Nevertheless, the continuity and stability of vital infrastructure will continue to depend heavily on legacy equipment. Thus, protecting the availability, security, and safety of industrial environments and vital infrastructure from cyberattacks requires operational technology (OT) cybersecurity. The feasibility of the proposed approach is illustrated with a case study from a real oil and gas production plant control system where numerous significant cyberattacks in recent years have targeted OT networks more frequently as hackers realized the possibility of disruption due to insufficient OT security, particularly for outdated systems. The proposed framework achieved better results in detecting threats and severity in the design of the case study system, helping to increase security and support cybersecurity assessment of legacy control systems.

The analysis of Hermite factor of BKZ algorithm on small lattices

Lattice cryptography is one of the promising directions in modern cryptography research. Digital signatures and key encapsulation mechanisms on lattices have already been used in practice. In the future, such quantum-resistant transformations on lattices replace all standards that are not resistant to attacks on quantum computers. This makes the analysis of their security extremely relevant. Analysis of the security of cryptographic transformations on lattices is often reduced to the estimation of the minimum block size in the lattice reduction algorithm. For the expansion of small vectors, a reduction algorithm can be obtained for a given block size, the GSA model is often used, which uses the so-called Hermitian factor to predict the size of the vectors that the lattice reduction algorithm can obtain given the parameters. Asymptotic formulas have been developed to evaluate it in practice, but the question of their accuracy on cryptographic lattices has not been fully investigated. The work obtained estimates of the accuracy of the existing asymptotic estimates of the Hermite factor for lattices of sizes 120, 145, 170 for the classical BKZ algorithm. Research was conducted using the fpylll library. It was shown that the existing estimators are equivalent from a practical point of view and have a sufficiently small root mean square deviation from the true values. A formula was obtained that binds the root-mean-square error of approximation of the Hermit factor to the cryptographic parameters of lattices. The obtained results are useful for refining the security assessments of existing cryptographic transformations.

Multifactor assessment of food security in the region

Multifactor assessment of food security in the region

Development of a Enhanced System Review for Public Agency Multi-Sectoral Integrated Data Systems

While traditional security assessments (such as mandated external security reviews which include a penetration test tied to a security framework) are a critical component to securing your data infrastructure, the complexities and governance structures around integrated data systems that involve multiple public sector agencies require a more comprehensive framework to address comprehensive risk, regulatory, and governance considerations that are critical to the confidentiality of the data within these systems. In January of 2024, the Data Integration Support Center (DISC) created and piloted an enhanced system review that includes components that are often overlooked or oversimplified when working with today's technologies such as cloud-based secure enclaves. By following up on a mandated security review, an enhanced system review can help a maturing Integrated Data System (IDS) address both security and privacy risks as it moves forward. An enhanced system review looks primarily, though not necessarily exclusively, at the following aspects of an IDS, principally in the interest of ensuring privacy: IDS alignment with its legal framework and other structuring documents (e.g., policies, procedures, interagency agreements) Training to support privacy and security Use of technology to prevent or mitigate human error The results of the review are provided directly to the IDS leadership and generally include a list of recommendations in the areas of improved legal agreements, leveraging privacy enhancing technologies to mitigate or reduce errors, procedural/policy gap identification and/or architectural recommendations to improve the security.