Security Level Of System Research Articles

SecuriDN: A Modeling Tool Supporting the Early Detection of Cyberattacks to Smart Energy Systems

SecuriDN v. 0.1 is a tool for the representation of the assets composing the IT and the OT subsystems of Distributed Energy Resources (DERs) control networks and the possible cyberattacks that can threaten them. It is part of a platform that allows the evaluation of the security risks of DER control systems. SecuriDN is a multi-formalism tool, meaning that it manages several types of models: architecture graph, attack graphs and Dynamic Bayesian Networks (DBNs). In particular, each asset in the architecture is characterized by an attack graph showing the combinations of attack techniques that may affect the asset. By merging the attack graphs according to the asset associations in the architecture, a DBN is generated. Then, the evidence-based and time-driven probabilistic analysis of the DBN permits the quantification of the system security level. Indeed, the DBN probabilistic graphical model can be analyzed through inference algorithms, suitable for forward and backward assessment of the system’s belief state. In this paper, the features and the main goals of SecuriDN are described and illustrated through a simplified but realistic case study.

Architecture and iot security systems based on fog computing

The subject of the study is is the security architecture of the Internet of Things (IoT) based on fog computing, which allows providing efficient and secure services for many IoT users. The goal is to investigate the security architecture for IoT systems based on fog computing. To achieve the goal, the following tasks were solved: the concept of fog computing is proposed, its architecture is considered and a comparative analysis of fog and cloud computing architectures is made; the principles of designing and implementing the architecture of a fog computing system are outlined; multi-level security measures based on fog computing are investigated; and the areas of use of fog computing-based Internet of Things networks are described. When performing the tasks, such research methods were used as: theoretical analysis of literature sources; analysis of the principles of designing and implementing the security architecture of the Internet of Things; analysis of security measures at different levels of the architecture. The following results were obtained: the architecture of fog computing is considered and compared with the cloud architecture; the principles of designing and implementing the architecture of fog computing systems are formulated; multi-level IoT security measures based on fog computing are proposed. Conclusions: research on IoT security systems based on fog computing has important theoretical implications. The fog computing architecture, in contrast to the cloud architecture, better meets the demand for high traffic and low latency of mobile applications, providing more advantages for systems that require real-time information processing. When designing and implementing the architecture of fog computing systems, the factors of memory capacity, latency, and utility should be taken into account to effectively integrate fog technologies with IoT. To ensure a high level of system security, multi-level security measures should be implemented using both software and hardware solutions.

NLP-Based Decision Support System for PUV Management: Enhancing Services Through Passenger Feedback Analysis

This paper presents the development and evaluation of an NLP-Based Decision Support System for Public Utility Vehicle (PUV) Management, focusing on enhancing services through passenger feedback analysis. The study addresses the need for improved public transportation quality in the Philippines, where PUVs play a vital role in daily commuting. The proposed system aims to digitize the passenger feedback process and utilize Natural Language Processing (NLP) techniques to provide decision support for PUV operators. Methodologically, the study follows a phased approach based on the System Development Life Cycle (SDLC). Developed primarily using PHP as the programming language, with Vanilla JS, Bootstrap, and jQuery for backend development and frontend technologies including HTML5, CSS3, and JavaScript (ES6) for creating an interactive user interface, the system caters to the needs of its different users. The evaluation process incorporates the ISO 25010 standard for evaluating systems, and with the participation of 43 respondents from the province of Iloilo, the evaluation results revealed an overall mean score of 4.34, indicating an "Excellent" level of system functionality, reliability, portability, usability, performance efficiency, security, compatibility, and maintainability. This implies that PUV operators and management can use the developed system.

Dynamic trust security approach for edge computing-based mobile IoT devices using artificial intelligence

The Industrial Internet of Things (IIoT) encompasses various applications such as smart cities, healthcare, and agriculture, which rely on a multitude of interconnected devices. These applications demand specific performance requirements, including low latency and sufficient bandwidth. Edge computing has emerged as a promising solution to address the challenges associated with data flow processing. Particularly, in scenarios like smart cities, where a massive number of IIoT devices are deployed, edge computing serves as the primary data processing layer. However, the limited resources of edge computing, compared to cloud computing, pose significant security concerns for IIoT applications. In fact, this paper proposes a novel security system to secure the relation between the IIoT devices and edge computing. Dynamic Trust Security Approach (DTSA) leverages Artificial Intelligence to analyze, evaluate and enhance the security and privacy aspects of the IIoT devices’ interaction with edge computing. DTSA improve the security level of the IIoT system and improve the performance with more than 45% compare to the traditional method.

Regulatory Implications for considering flexible resources in network expansion planning: main lessons from regional cases in the H2020 FlexPlan project

The FlexPlan Horizon2020 project aimed at establishing a new grid planning methodology which considers the opportunity to introduce new storage and flexibility resources in electricity transmission and distribution grids as an alternative to building new grid elements, in accordance with the intentions of the European Commission regulatory package "Clean Energy for all Europeans". FlexPlan creates a new innovative grid planning tool which is intended to go beyond the state of the art of planning methodologies by including the following innovative features: assessment of best planning strategy by analysing in one shot a high number of candidate expansion options provided by a pre-processor tool, simultaneous mid- and long-term planning assessment over three grid years (2030-2040-2050), incorporation of full range of cost benefit analysis criteria into the target function, integrated transmission distribution planning, embedded environmental analysis (air quality, carbon footprint, landscape constraints), probabilistic contingency methodologies in replacement of the traditional N-1 criterion, application of numerical decomposition techniques to reduce calculation efforts and analysis of variability of yearly RES and load time series through a Monte Carlo process. Six regional cases covering nearly the whole European continent are developed in order to cast a view on grid planning in Europe till 2050. The final step in FlexPlan was formulating guidelines for regulators and planning offices of system operators, by indicating to what extent system flexibility can contribute to reduce overall system costs (operational and investment) yet maintaining current system security levels and which regulatory provisions could foster such process. This paper focuses on the regulatory issues, which were uncovered during the initiation phase and of the project and refined in throughout six regional cases. In order to substantiate this, the paper explains in brief the developed and applied FlexPlan methodology and its testing in six regional cases.

Systematic Risk Characterisation of Hardware Threats to Automotive System

The increasing dependence of modern automotive systems on electronics and software poses cybersecurity risks previously not factored into design and engineering of such systems. Attacks on hardware components, communication modules and embedded software – many of which are purposefully designed for automotive control and communications – are the key focus of this paper. We adopt a novel approach to characterise such attacks using Gajski-Kuhn Y-charts to represent attack manipulation across behavioural, structural and physical domains. Our selection of attacks is evidence-driven demonstrating threats that have been demonstrated to be feasible in the real-world. We then risk assess impact of such threats using the recently adopted ISO/SAE 21434 standard for automotive cybersecurity risk assessment, including mitigations for potential adoption. Our work serves to provide unique insights into the complex dynamic of hardware vulnerabilities and how the industry may address system-level security and protection of modern automotive platforms.

Artificial intelligence in the sphere of cybersecurity: innovations, challenges, and development prospects

The relevance of the study is due to the need for effective protection of information systems in the face of ever-growing cyber threats. In the modern digital world, where cyberattacks are becoming increasingly complex and widespread, the use of artificial intelligence in cybersecurity is extremely relevant. The problem of cybersecurity is becoming increasingly important and conducting relevant research is becoming a necessary aspect of ensuring security in the digital space.In this context, we propose an article that examines the role of artificial intelligence, innovations, challenges, and prospects of its development in the sphere of cybersecurity. Additionally, it explores the utilization of artificial intelligence for automating processes of detecting, analysing, and responding to cyber threats, and its practical significance for enhancing security levels in the digital space and the effectiveness of cyber threat protection. The main approaches for this study are trend analysis and expert assessments, which allow for a comprehensive review of the directions of artificial intelligence development in the field of cybersecurity, the benefits and challenges of its implementation, as well as potential opportunities and threats to information security. The article discusses advanced security information and event management systems designed to collect, analyse and respond to cyber threats and other systems aimed at specific aspects ofprotection and expanding automation capabilities to improve the security level of information systems. The materials of the article are of theoretical value for further scientific research on the use of artificial intelligence in the sphere of cybersecurity and reflect important features of its influence on this area. This research can contribute not only to deepening the understanding of the theoretical aspects of the use of artificial intelligence in cybersecurity but also to identifying specific practical applications and innovations that will help improve protection against cyber threats in the future.

Sustainability of the Digital Economy in Indonesia: Opportunities, Challenges and Future Development

This study aims to evaluate the challenges and opportunities arising from digital transformation and the digital economy, as well as their impact on human and physical resource development in the context of Indonesia. The methods used were a literature review and a qualitative approach. This study used secondary data obtained from academic articles published in the last 10 years. Data analysis techniques include material collection, data reduction, analysis and synthesis stages, and drawing conclusions. The results indicate that digital transformation brings economic and social opportunities. However, challenges also arise, such as digital divides among different groups, the level of human resource development, data and online system security, and taxation issues. Obstacles to be faced include slow regulatory reforms, bureaucratic complexity, government promotion in various regions, and digital infrastructure limitations. Strategic steps that need to be taken include developing appropriate policies, fostering collaboration between the public and private sectors, enhancing cybersecurity capacity, and promoting digital transformation domestically and internationally to advance national and regional economies. The key conclusion is that the main impact of the digital economy on the Indonesian economy as a whole includes market share growth, increased brand awareness, expanded customer reach, ease of business transactions, and increased product variety at competitive prices.

Подходы к оценке защищённости информационных систем с криптографическим преобразованием объектов

The file system is one of the components of an information system, especially vulnerable to attacks by intruders. Consequently, it is impossible to increase the security level of an information system without ensuring a sufficient level of protection for file system objects, attacks on which affect, among other things, the interests of users of information systems. In order to make decisions on the use of certain mechanisms for protecting file system objects, a regular assessment of their current level of security is necessary. The purpose of the study. Building a model for assessing the security of an information system with cryptographic transformation of file system objects in the context of an attacker using a wide range of attacks on the file system. Materials and methods. The analysis of scientific publications on the problem of assessing the security of information systems allowed us to propose a methodology for assessing the security of information system assets. The methodology is based on a combination of a probabilistic approach to the analysis of possible scenarios for the implementation of threats in information systems for file system objects, expert assessments of basic attack events and representations in the form of attack trees. The threat implementation representation in the form of attack trees is used to simulate the actions of an attacker. Results. A structural model of an information system with cryptographic transformation of objects has been developed. Its valuable assets have been allocated. The list of the main threats to information security relevant for such systems is defined. Possible variants of the ways of implementing attacks and possible scenarios of the development of events in the processes of transferring file system objects with cryptographic transformation are modeled. A set of measures for the protection of information system objects with cryptographic transformation of objects is proposed. The calculation of the probabilities of attacks on an asset along the path determined by the attack tree, the possibility of implementing an attack, the degree of effectiveness of the proposed countermeasures is proposed. Conclusion. The presented methodology for assessing the security of an information system with cryptographic transformation of objects makes it possible to use well-known approaches in a comprehensive manner, and will be useful to developers and researchers in practical and scientific activities to ensure information security.

Towards System-Level Security Analysis of IoT Using Attack Graphs

Most IoT systems involve IoT devices, communication protocols, remote cloud, IoT applications, mobile apps, and the physical environment. However, existing IoT security analyses only focus on a subset of all the essential components, such as device firmware or communication protocols, and ignore IoT systems' interactive nature, resulting in limited attack detection capabilities. In this work, we propose <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Iota</small> , a logic programming-based framework to perform system-level security analysis for IoT systems. <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Iota</small> generates attack graphs for IoT systems, showing all of the system resources that can be compromised and enumerating potential attack traces. In building <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Iota</small> , we design novel techniques to scan IoT systems for individual vulnerabilities and further create generic exploit models for IoT vulnerabilities. We also identify and model physical dependencies between different devices as they are unique to IoT systems and are employed by adversaries to launch complicated attacks. In addition, we utilize NLP techniques to extract IoT app semantics based on app descriptions. <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Iota</small> automatically translates vulnerabilities, exploits, and device dependencies to Prolog clauses and invokes MulVAL to construct attack graphs. To evaluate vulnerabilities' system-wide impact, we propose three metrics based on the attack graph, which provide guidance on hardening IoT systems. Evaluation on 127 IoT CVEs (Common Vulnerabilities and Exposures) shows that <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Iota</small> 's exploit modeling module achieves over 80% accuracy in predicting vulnerabilities' preconditions and effects. We apply <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Iota</small> to 37 synthetic smart home IoT systems based on real-world IoT apps and devices. Experimental results show that our framework is effective and highly efficient. Among 27 shortest attack traces revealed by the attack graphs, 62.8% are not anticipated by the system administrator. It only takes 1.2 seconds to generate and analyze the attack graph for an IoT system consisting of 50 devices.

Improving Sme Accountability In The M-Wallet Era Postadoption Implications

This research aims to investigate the impact of M-Wallet adoption on SME financial accountability and its implications for small and medium business practices. The research method uses a mixed approach which combines qualitative (interviews) and quantitative (questionnaire) approaches. The population in this study is UKM in Bengkulu that have adopted M-Wallet in operations. The sampling technique uses survey techniques. Data collection techniques used interviews and questionnaires with a Linkert scale of 1-5. Data testing uses multiple linear regression analysis. Based on the research results, it can be concluded that there has been an increase in SME accountability in the mwallet era with post-adoption implications. The regression results show that system security influences SME accountability. SMEs feel that a high level of system security can reduce the risk of data loss or financial theft, thereby increasing accountability in managing finances. The regression results show that system effectiveness influences SME accountability. The effectiveness of the system in processing transactions more quickly, providing financial reports that are easy to understand, and providing good visibility into cash flow has a role in improving accountability practices.

Regulatory Implications for considering flexible resources in network expansion planning: main lessons from regional cases in the H2020 FlexPlan project.

The FlexPlan Horizon2020 project aimed at establishing a new grid planning methodology which considers the opportunity to introduce new storage and flexibility resources in electricity transmission and distribution grids as an alternative to building new grid elements, in accordance with the intentions of the European Commission regulatory package "Clean Energy for all Europeans". FlexPlan creates a new innovative grid planning tool which is intended to go beyond the state of the art of planning methodologies by including the following innovative features: assessment of best planning strategy by analysing in one shot a high number of candidate expansion options provided by a pre-processor tool, simultaneous mid- and long-term planning assessment over three grid years (2030-2040-2050), incorporation of full range of cost benefit analysis criteria into the target function, integrated transmission distribution planning, embedded environmental analysis (air quality, carbon footprint, landscape constraints), probabilistic contingency methodologies in replacement of the traditional N-1 criterion, application of numerical decomposition techniques to reduce calculation efforts and analysis of variability of yearly RES and load time series through a Monte Carlo process. Six regional cases covering nearly the whole European continent are developed in order to cast a view on grid planning in Europe till 2050. The final step in FlexPlan was formulating guidelines for regulators and planning offices of system operators, by indicating to what extent system flexibility can contribute to reduce overall system costs (operational and investment) yet maintaining current system security levels and which regulatory provisions could foster such process. This paper focuses on the regulatory issues, which were uncovered during the initiation phase and of the project and refined in throughout six regional cases. In order to substantiate this, the paper explains in brief the developed and applied FlexPlan methodology and its testing in six regional cases.

A novel IoT intrusion detection framework using Decisive Red Fox optimization and descriptive back propagated radial basis function models

The Internet of Things (IoT) is extensively used in modern-day life, such as in smart homes, intelligent transportation, etc. However, the present security measures cannot fully protect the IoT due to its vulnerability to malicious assaults. Intrusion detection can protect IoT devices from the most harmful attacks as a security tool. Nevertheless, the time and detection efficiencies of conventional intrusion detection methods need to be more accurate. The main contribution of this paper is to develop a simple as well as intelligent security framework for protecting IoT from cyber-attacks. For this purpose, a combination of Decisive Red Fox (DRF) Optimization and Descriptive Back Propagated Radial Basis Function (DBRF) classification are developed in the proposed work. The novelty of this work is, a recently developed DRF optimization methodology incorporated with the machine learning algorithm is utilized for maximizing the security level of IoT systems. First, the data preprocessing and normalization operations are performed to generate the balanced IoT dataset for improving the detection accuracy of classification. Then, the DRF optimization algorithm is applied to optimally tune the features required for accurate intrusion detection and classification. It also supports increasing the training speed and reducing the error rate of the classifier. Moreover, the DBRF classification model is deployed to categorize the normal and attacking data flows using optimized features. Here, the proposed DRF-DBRF security model's performance is validated and tested using five different and popular IoT benchmarking datasets. Finally, the results are compared with the previous anomaly detection approaches by using various evaluation parameters.

Methods and techniques for the information and analytical systems of data protection and conversion assessment

The goal of the research is to create an algorithm for analyzing vulnerabilities discovered and to enhance the data protection technique based on system penetration testing as a means of evaluating data security. The primary responsibility is to modify established security assessment techniques to fit the evolving technical landscape, namely cloud technologies and security system requirements. The issue of data protection evaluation of electronic documents is discussed in the article, and specifically, an A/B test was conducted. To address this issue, an analysis was conducted on current data protection evaluation methodologies and techniques, and an A/B testing system was constructed. These methods help to determine the level of danger of vulnerabilities, which allows you to effectively and visually determine the overall level of system security by evaluating each vulnerability found. The article examines the practical use of the method, prospects for further development, and features of the effectiveness of penetration testing as a method of assessing the security of information systems and the development of an algorithm for evaluating the vulnerabilities found. Researching the methods and means of security assessment, the work was aimed at creating a convenient and effective tool for assessing the security of data and documents in the network. The theoretical significance of the work is determined by the expansion of scientific knowledge in the field of information and analytical systems of electronic document management. The research aims to explore and apply big data analysis and machine learning techniques to improve data protection. The novelty of the research lies in the synthesis of modern methodologies of A/B testing and analytics within a single platform, which will allow electronic documents to protect data and increase efficiency from hacker attacks. The principles of the method are described along with the main approaches and techniques that contribute to the analysis of hacker attacks on online systems and cloud environments. The components of the method, which provide for data protection, were separately analyzed, and an analysis of system testing was carried out to determine the requirements for the new system and increase the level of protection against data theft. The application of methods and tools for assessing the security of networks, which use a complex of general scientific, experimental, practical, statistical, and mathematical methods for the implementation of algorithms and the formation of the determination of the levels of danger of vulnerabilities, is considered. The method includes data analysis tools, as well as analysis techniques that provide an opportunity to conduct flexible testing of changes on the site with further analysis and impact on conversion, which is important for increasing data protection and meeting consumer needs.

Attack graph-based security metrics: Concept, taxonomy, challenges and open issues

Context: Security issues have increased recently because of the increased use of networking. The researchers have proposed many models, approaches, and models, for example, attack graphs. The attack graph model is a valuable tool for vulnerability analysis as well as for displaying all network paths. In general, attack graphs can be utilized for a variety of purposes, including the calculation of security metrics. Nonetheless, in order to sufficiently safeguard networks, a technique for gauging the security degree provided by these activities is required, as “you cannot improve what you cannot measure.” The security level of a system or network is typically represented by network security metrics in qualitative and quantitative ways. The network security metrics are typically employed to evaluate a system's security level and meet security objectives. Aim: This study aims to present a review of attack graph-based security metrics and analyse the previous work. Provides the limitations and issues the researchers faced to improve this important research area. Methodology: The attack graph security metrics field was thoroughly investigated in all research, and four databases—ScienceDirect, Web of Science (WoS), Scopus, and IEEE—were used to collect data between 2001 and 2022. Results: 46 papers were founded on attack graph security metrics with different methods and techniques based on the exclusion and inclusion criteria. The results of the taxonomy created three significant categories: proposed, implemented, reviewed, and surveyed. We believe this study will aid in highlighting research ability, which will subsequently broaden and establish new research topics.

Beaf:BD – A Blockchain Enabled Authentication Framework for Big Data

The widespread utilization of Internet-based applications in our daily routines has resulted in enormous amounts of data being generated every minute. This data is not only produced by humans but also by various machines such as sensors, satellites, CCTV, etc. For many organizations, Apache Hadoop is the solution for handling big data. Big data refers to the extensive set of dissimilar data that can be processed to derive meaningful insights. For its security needs, Hadoop relies on trusted third-party security providers such as Kerberos. Kerberos has several security vulnerabilities. The focus of this paper is to eliminate security issues, particularly dictionary attacks and single points of failure, by proposing a model based on blockchain technology and threshold cryptography.In comparison to other existing schemes, the proposed approach offers superior computational overhead and storage requirements while maintaining the system's security level.

Risk sensitivity analysis of AIS cyber security through maritime cyber regulatory frameworks

Given the increasing frequency and sophistication of methods and strategies employed in cyberattacks, cyber resilience has become a basic notion of cyber risk management. To be cyber-resilient against cyber risks, shipping companies must be proactive in establishing and implementing actions, constructing effective strategies, and adopting mitigation methods to strengthen their assets. However, shipping companies have only lately tended to fully recognize the necessity for a cybersecurity perspective to enable effective cyber risk management and mitigation of increasing cyberattacks. Aside from deficiencies in system design, integration, or maintenance, human factors are the prime weakness that potentially jeopardizes the ship's cybersecurity by simply making intentional or unintentional errors, revealing critical information, or generating entry points for attackers. Therefore, the current study aims to conduct a quantitative human risk assessment based on the SOHRA method, which is integrated with the NIST cybersecurity framework, to provide ships with the ability to be cyber resilient, and respond to and recover from cyber-attacks. The AIS has been considered for the research application not only because it is one of the most vulnerable systems on board a ship, but also because modifying and breaching the AIS data might have disastrous outcomes. The study results clearly indicate that the most likely error related to AIS cybersecurity risk occurs in the tasks defined under the "protect", "respond", "detect", "identify", and "recover" functions. Accordingly, suitable control and preventative measures have been developed to guarantee high-level cyber security for AIS and to provide cyber resilience and the structure for constructive decision-making by integrating various international standards, which include system security requirements and security levels for industrial communication networks, specifically with the IACS and NIST framework for the AIS cyber security.

Steganographic method of acoustic information protection in critical applications systems

The subject of the study is the process of protecting acoustic information in critical computer systems to ensure the required level of system security. The purpose of the article is to study the method of protecting acoustic information in critical computer systems by means of masking to ensure the impossibility of unauthorized access to the system. The paper outlines the following tasks: to analyze the software and hardware masking of speech; to study the masking of speech messages in order to introduce unrecognizability; to consider the features of speech message compression; to investigate methods of covert transmission of acoustic information. The results of the work, which were obtained using mathematical methods of information transformation in computer systems, are potentially possible methods of masking speech messages to ensure the impossibility of unauthorized access to the system. The analysis of the functioning of the proposed methods made it possible to formulate specific conclusions. The research has shown that the use of direct expansion of the spectrum of discrete signals for steganographic purposes helps to covertly embed information messages in still images. The task of extracting a message on the receiving side of a steganography system is equivalent to the task of detecting information from a mixture of a useful signal and an interference in a broadband communication system. The research revealed certain disadvantages of steganographic systems with an expanded spectrum of discrete signals: the probability of correct extraction of embedded data depends on the amount of distortion introduced, which depends on the provided bandwidth of the steganographic channel. Further research is desirable to analyze the possible use of methods for synthesizing large ensembles of quasi-orthogonal discrete signals with improved ensemble, structural, and correlation properties to ensure higher security of acoustic channels in computer systems for critical applications.

Hardware/software security co-verification and vulnerability detection: An information flow perspective

Security vulnerabilities provide attackers unauthorized access to critical resources and effective attack surfaces to compromise a system. Security verification is an emerging technique for detecting and locating such threats. However, existing security verification methods are typically restricted within the hardware or software boundary and incapable of meeting cross-layer verification requirements due to the differences in design semantics and the lack of a security model that fits both hardware and software. We attempt to address such a limitation from the perspective of information flow analysis and propose a hardware/software security co-verification method, which can check information flow security properties on fine-grained hardware information flow models. The proposed method can pinpoint security vulnerabilities by capturing information flow security property violations under clues of malicious information flows. Our information flow security model and properties are described using standard hardware design and verification languages, which allows our method to be seamlessly integrated with electronics design automation flows. Experimental results using RISC-V hardware/software designs show that the proposed method detects software, hardware and system-level security vulnerabilities, effectively.

Regulatory Implications for considering flexible resources in network expansion planning: main lessons from regional cases in the H2020 FlexPlan project

The FlexPlan Horizon2020 project aimed at establishing a new grid planning methodology which considers the opportunity to introduce new storage and flexibility resources in electricity transmission and distribution grids as an alternative to building new grid elements, in accordance with the intentions of the European Commission regulatory package "Clean Energy for all Europeans". FlexPlan creates a new innovative grid planning tool which is intended to go beyond the state of the art of planning methodologies by including the following innovative features: assessment of best planning strategy by analysing in one shot a high number of candidate expansion options provided by a pre-processor tool, simultaneous mid- and long-term planning assessment over three grid years (2030-2040-2050), incorporation of full range of cost benefit analysis criteria into the target function, integrated transmission distribution planning, embedded environmental analysis (air quality, carbon footprint, landscape constraints), probabilistic contingency methodologies in replacement of the traditional N-1 criterion, application of numerical decomposition techniques to reduce calculation efforts and analysis of variability of yearly RES and load time series through a Monte Carlo process. Six regional cases covering nearly the whole European continent are developed in order to cast a view on grid planning in Europe till 2050. The final step in FlexPlan was formulating guidelines for regulators and planning offices of system operators, by indicating to what extent system flexibility can contribute to reduce overall system costs (operational and investment) yet maintaining current system security levels and which regulatory provisions could foster such process. This paper focuses on the regulatory issues, which were uncovered during the initiation phase and of the project and refined in throughout six regional cases. In order to substantiate this, the paper explains in brief the developed and applied FlexPlan methodology and its testing in six regional cases.