Security Management Framework Research Articles

Blockchain with secure data transactions and energy trading model over the internet of electric vehicles

The rise of Electric Vehicles (EVs) has introduced significant advancement and evolution in the electricity market. In smart transportation, the EVs have earned more popularity because of its numerous benefits including lower carbon footprints, higher performance, and sophisticated energy trading mechanisms. These potential benefits have resulted in widespread EV adoption across the world. Despite its benefits, energy management remains the biggest challenge in EVs and it is mainly because of the lack of Charging Stations (CSs) near EVs. This creates a demand for an effective, secure and reliable energy management framework for EVs. This study presents a secure data and energy trade paradigm based on Blockchain (BC) in the Internet of EVs (IoEV). BC technology prepares for the high volume of EV integration that serves as the foundation for the next generation, and to assist in developing unique privacy-protected BC-based D-Trading and storage Models. Entities evaluated for the proposed model include Trusted Authority (TA), Vehicles, Smart Meters, Roadside Units (RSU), BC, and Inter-Planetary File System (IPFS). In addition, E-trading involves several phases, including the acquiring E-trading demand requests, E-trading response requests, request matching and token assignment. Moreover, account mapping is performed using a Mayfly Pelican Optimization Algorithm (MPOA), which is created by merging the Mayfly Algorithm (MA) and Pelican Optimization Algorithm (POA). Various security features are used to protect data and energy trade in IoEV, including encryption, hashing, polynomials, and others. The testing results revealed that the MPOA outperformed the state-of-the-art results regarding memory consumption, trading rate, transaction cost, and trading energy volume with values of 4.605 MB, 91%, 0.654, and 90 kW, respectively.

A Comprehensive Machine Learning Framework for Robust Security Management in Cloud-based Internet of Things Systems

The purpose of this paper is to explore the role of Machine Learning (ML) in fortifying the security of cloudbased Internet of Things (IoT) systems, using a comprehensive security management approach. The methodological approach involved comparing different ML techniques such as Decision Trees, Random Forest, Support Vector Machines, and Convolutional Neural Networks. Their effectiveness was evaluated based on the accuracy of threat detection in cloud-based IoT systems. The findings revealed that Convolutional Neural Networks demonstrated the highest accuracy rate (98%) in threat detection, thereby significantly enhancing the security of IoT systems. It also identified improvements in threat detection, prevention, response, and system recovery across all ML techniques. Research limitations were primarily the rapidly evolving nature of both ML and IoT technologies, necessitating continual reassessments. The scope was also limited to cloud-based IoT systems, leaving room for further research on other types of IoT systems. The practical implications included improved system security, which could lead to increased trust and wider adoption of IoT technology in various sectors, from healthcare to home security. The social implications entail a safer digital environment, contributing to data privacy and reducing the risk of cyber threats for individuals and communities. The originality of this paper lies in its comprehensive approach to IoT security management using ML, providing valuable insights into the effectiveness of different ML techniques in enhancing threat detection accuracy.

Risk management under weighted limited expected loss

We present and solve an optimal asset allocation problem under a weighted limited expected loss (WLEL) constraint. This formulation encompasses the risk management problem with a limited expected loss (LEL) constraint as a specialized instance and offers a pertinent internal risk management instrument for firms. We observe that a WLEL constraint makes the optimizing investor pursue less volatile payoffs than the unconstrained Merton solution. Compared to the LEL-constrained problem with the same weighted default threshold, the WLEL optimal terminal wealth displays a less dispersed distribution with a smaller variance, suggesting a more secure risk management framework. Conducting a comprehensive equilibrium analysis in the presence of a WLEL risk manager, we validate the relatively conservative investment approach undertaken by the WLEL manager. Subsequently, we expand our findings to encompass broader incomplete market settings, wherein the uniqueness of the equivalent local martingale measure is not assured.

Regulatory frameworks for securing electoral processes in Ukraine: managing information security challenges

The administrative and legal framework for managing the information security of electoral processes in Ukraine includes regulations, various measures and procedures that are primarily aimed at ensuring the reliability and security of the electoral process due to the negative impact of external information, manipulation and illegal interference. Cyberattacks, media manipulations, and imperfect legal frameworks in the electoral sphere can lead to the invalidation of election results and the loss of confidential information. The main purpose of the domestic legislation is to strengthen the relevant protection of information from cyber threats. The relevance of studying this issue is primarily related to the administrative and legal framework for managing the information security of electoral processes in the spectrum of modern technological capabilities and external influences connected with the digital sphere. The purpose of the academic paper is to determine the administrative and legal framework for managing the information security of electoral processes in Ukraine. The academic paper the problems caused by the violation of information security in the process of electoral activity have been revealed. The features of the administrative and legal framework for managing the information security of electoral processes have been established. The legal and regulatory framework for information security management during elections has been studied. The academic paper also emphasizes the inexpediency of holding elections during the period of martial law and identifies the causes and consequences.

Information Security and Privacy Management in Intelligent Transportation Systems

With the global digitalization of services, passenger Intelligent Transportation Systems (ITSs) have emerged as transformative components, yet the practical implementation of state-of-the-art measures to ensure information security and privacy presents substantial challenges. In this article, we propose a framework for information security and privacy management. The framework is validated through two empirical studies. First, the framework is used to extract data during the literature review defining state-of-the-art aspects and measures. Second, a survey-based analysis of running passenger ITSs in selected regions of the European Union provides insights into real-life ITS implementations, enabling a thorough comparison with the proposed state-of-the-art measures. The study also showed that the proposed framework depicts some dependencies between measures, and, thus, using its matrix structure for the state of information security and privacy management in the organization helps to cross-check the usage of policies or methodologies by the organization departments. Our findings resulted in recommendations for organizations developing ITSs to enhance their information security and privacy management systems and bridge the gap between research proposals and practical implementation.

Business Process Outsourcing 14 Cybersecurity KPIs Towards a Strategic Information Security

In today’s rapidly evolving digital landscape, the Business Process Outsourcing (BPO) industry faces an ever-increasing threat of cyber-attacks and data breaches, underscoring the critical importance of robust information security practices. To address these challenges, organizations must develop effective strategic information security, supported by reliable performance measurement tools such as Key Performance Indicators (KPIs). This research aims to investigate the information security implemented by BPO companies and their utilization of the 14 cybersecurity KPIs to track and enhance their information security measures. A mixed-methods strategy is used in the study, integrating qualitative and quantitative techniques. The qualitative component involves thematic analysis of key informant interviews, while the quantitative component entails the analysis of Likert-scale questionnaires and numerical data. The findings of this research provide valuable insights into the significance of strategic information security in achieving effective information security management within the BPO industry. The study reveals the specific elements incorporated in these plans, such as risk assessment methodologies, security controls implementation, employee training, incident response strategies, and compliance measures. The implications of this study offer valuable insights for BPO organizations to develop robust strategic information security tailored to their specific context, ensuring effective alignment with organizational objectives and risk management strategies. Moreover, the research contributes to the existing literature on information security management frameworks, emphasizing the role of cybersecurity KPIs in evaluating security performance. Keywords: cybersecurity, information security, KPI, business process outsourcing industry, information security management

An IoT and Blockchain-Based Secure and Transparent Supply Chain Management Framework in Smart Cities Using Optimal Queue Model

An IoT and Blockchain-Based Secure and Transparent Supply Chain Management Framework in Smart Cities Using Optimal Queue Model

Dynamic Risk Assessment in Cybersecurity: A Systematic Literature Review

Traditional information security risk assessment (RA) methodologies and standards, adopted by information security management systems and frameworks as a foundation stone towards robust environments, face many difficulties in modern environments where the threat landscape changes rapidly and new vulnerabilities are being discovered. In order to overcome this problem, dynamic risk assessment (DRA) models have been proposed to continuously and dynamically assess risks to organisational operations in (near) real time. The aim of this work is to analyse the current state of DRA models that have been proposed for cybersecurity, through a systematic literature review. The screening process led us to study 50 DRA models, categorised based on the respective primary analysis methods they used. The study provides insights into the key characteristics of these models, including the maturity level of the examined models, the domain or application area in which these models flourish, and the information they utilise in order to produce results. The aim of this work is to answer critical research questions regarding the development of dynamic risk assessment methodologies and provide insights on the already developed methods as well as future research directions.

A blockchain-assisted security management framework for collaborative intrusion detection in smart cities

Aiming to safeguard a decentralized setup such as smart cities, collaborative intrusion detection system (CIDS) has become a mainstream security mechanism to protect different types of computer networks, especially decentralized computing platforms such as Internet of Things (IoT). The main benefit of CIDS relies on the information sharing process among devices, nodes, software and hardware entities. However, traditional CIDS often requires a trusted third partner, e.g., a centralized computing server, to help build up a trusted communication channel among various entities. Such requirement is not practical in real-world implementation, making the integrity of shared information compromised easily. With the wide adoption, blockchain technology has given a solution to protect the distributed/collaborative detection system. In the current market, blockchain technology has been extensively researched across many detection scenarios, but there is a need to explore how such technology can overall contribute to CIDS and a general distributed detection system. In this work, we introduce a blockchain-assisted security management framework for CIDS, which summarizes and provides an integrated protection given by blockchain. In the case study, we evaluate our proposed framework in both a simulated and a real CIDS setup with challenge-based mechanism. The results demonstrate the promising benefits provided by blockchain in CIDS.

Enhancing Security and Efficiency in Underwater Wireless Sensor Networks: A Lightweight Key Management Framework

Underwater Wireless Sensor Networks (UWSNs) obtains more attention due to their wide range of applications such as underwater oil field discovery, Tsunami monitoring systems, surveillance systems, and many more. In such a resource-constrained environment, sensors are more vulnerable to malicious attacks. Node authentication and secure communication is one of the vital issues in UWSNs. In this study, a secure and lightweight key management framework for UWSNs is proposed. The proposed framework includes key generation, key distribution, revocation, and authentication mechanisms along with lightweight implementation, and scalability. We use an elliptic curve-based algorithm for key distribution, and certificate revocation list (CRL) for key revocation. We also examine the performance of the proposed framework taking into account the amount of communication overhead as well as the level of security. The simulation results show that the proposed framework provides better security with less communication overhead compared to existing frameworks. This framework can be used for secure data communication in UWSNs, which has various applications in oceanography, environmental monitoring, and military operations.

FSAS: An IoT-Based Security System for Crop Field Storage

Internet of Things abstracts the ability to remotely associate and observe things or objects over the Internet. When it comes to agriculture, this idea has been incorporated to make agriculture-related tasks smart, secure, and automated. Agriculture is vital for economic growth and also for the survival of humans. Farmers living in rural areas of India face a common problem of the theft of equipment like induction motors from small storage houses meant for storing commodities in crop fields. In this study, we present a remote security management framework for monitoring the crop field storage house, known as the farm security alert system (FSAS). FSAS is a small, energy efficient, low cost, and accurate security management system that uses microcontroller-based passive infrared (PIR) sensor and global system for mobile communication (GSM) module to generate an alert to the farm owner if there is an intrusion event at the crop field store. The microcontroller board utilized in the proposed model is the Arduino Uno, and PIR motion sensor is used to recognize the intruder. In addition, FSAS also can be used for monitoring of induction motor by utilizing a similar arrangement of sensors. The sensor signal is transmitted to the cloud whenever the intruder is within the sensing range of the sensor node. Naive Bayes’ prediction model is used to identify the level of encroachment as no (green), mild (yellow), or high (red) threat. The status and the alarms can be received by the farm owners, either on their smartphones as application alerts or as a short message/phone call, at any distance, and independent of whether their cell phones are connected to the Internet.

Current security and privacy posture in wireless body area networks

Wireless Body Area Networks (WBANs) have emerged as a promising technology for remote health monitoring and healthcare applications. However, ensuring the security and privacy of sensitive health data in WBANs is crucial to foster user trust and prevent unauthorized access or data breaches. This paper provides an overview of the key challenges, techniques, and research gaps in WBAN security and privacy. The findings indicate that the challenges in WBAN security and privacy include resource constraints, compatibility issues, privacy concerns, dynamic network environments, security and usability trade-offs, emerging threat landscape, and user awareness and education. To address these challenges, various security techniques have been developed, such as authentication and authorization mechanisms, encryption, access control, secure communication protocols, intrusion detection systems, and privacy-preserving data handling techniques. Despite the progress made, there are research gaps that require further investigation. These research gaps include the development of secure and lightweight authentication mechanisms, privacy-preserving data analysis techniques, trust and security management frameworks, resilience to insider threats, security of data aggregation and fusion, user-centric security designs, and addressing legal and ethical considerations. Addressing these research gaps and challenges requires collaboration between researchers, device manufacturers, policymakers, and end-users. Ongoing research and innovation are necessary to develop robust security techniques, privacy-enhancing technologies, and user-friendly solutions tailored for WBANs. Additionally, compliance with privacy regulations, user education, and awareness are critical for responsible and ethical use of WBANs.

A blockchain‐enabled security management framework for mobile edge computing

AbstractMobile edge computing (MEC) integrates mobile and edge computing technologies to provide efficient computing services with low latency. It includes several Internet of Things (IoT) and edge devices that process the user data at the network's edge. The architectural characteristic of MEC supports many internet‐based services, which attract more number of users, including attackers. The safety and privacy of the MEC environment, especially user information is a significant concern. A lightweight accessing and sharing protocol is required because edge devices are resource constraints. This paper addresses this issue by proposing a blockchain‐enabled security management framework for MEC environments. This approach provides another level of security and includes blockchain security features like temper resistance, immutable, transparent, traceable, and distributed ledger in the MEC environment. The framework guarantees secure data storage in the MEC environment. The contributions of this paper are twofold: (1) We propose a blockchain‐enabled security management framework for MEC environments that address the security and privacy concerns, and (2) we demonstrate through simulations that the framework has high performance and is suitable for resource‐constrained MEC devices. In addition, a smart contract‐based access and sharing mechanism is proposed. Our research uses a combination of theoretical analysis and simulation experiments to demonstrate that the proposed framework offers high security, low latency, legitimate access, high throughput, and low operations cost.

Information Security Management Framework for Cloud Computing Environments

Cloud computing has become a popular paradigm for delivering computing resources and services over the internet. However, the adoption of cloud computing also brings new security challenges and risks, including data breaches, insider attacks, and unauthorized access. Therefore, it is critical to have a comprehensive information security management framework to address these challenges and ensure the security and privacy of cloud computing environments. This paper proposes a machine learning (ML) based information security management (ISM) framework for cloud computing environments that integrates best practices and standards from various domains, including cloud computing, information security, and risk management. The proposed framework includes residual recurrent network to effectively discriminate different patterns of cloud security attacks. The proposed framework emphasizes the importance of threat detection, security controls, and continuous monitoring and improvement. The framework is designed to be flexible and scalable, allowing organizations to tailor it to their specific needs and requirements.

A Comprehensive Framework for Systemic Security Management in NoC-Based Many-Cores

A Comprehensive Framework for Systemic Security Management in NoC-Based Many-Cores

Cloud Mining Pool Aided Blockchain-Enabled Internet of Things: An Evolutionary Game Approach

The past few years have witnessed an exponential growth of diverse Internet of Things (IoT) devices as well as compelling applications ranging from industrial production to medical care. Dramatic advances in IoT technology not only brought enormous economic opportunities but also challenges (e.g., privacy and security vulnerabilities). Recently, with the appearance of blockchain technology, the integration of IoT and blockchain (BCoT) is considered a promising solution to address these issues. Blockchain provides a secure and scalable data management framework for IoT devices. However, the huge computation and energy cost of the consensus process in blockchain prevents it from being directly applied as a generic platform. To overcome this challenge, in this article, we propose a cloud mining pool-aided BCoT architecture, where the IoT devices can rent the computing resources from the cloud mining pools to offload the mining process. Based on this architecture, we study the mining pool selection problem and analyze the colony behaviors of IoT devices with different pooling strategies. We propose a centralized evolutionary game-based pool selection algorithm for the sake of maximizing the system utility. Considering the non-cooperative relationship among multiple miners, we also propose a lightweight distributed reinforcement learning algorithm, named the ‘WoLF-PHC’ algorithm.

A Novel Stochastic Blockchain-Based Energy Management in Smart Cities Using V2S and V2G

This paper proposes a secure management framework for optimal scheduling and operation of energy systems in smart cities, which will bring balance in modern power systems. The expanded infiltration of energy systems along with stochastic performance and high data transfer rate can bring new challenges that may severely affect precise energy management. This research work investigates the optimal and secure operation of energy systems in the presence of smart transportation systems in a correlated energy system. To achieve the maximum efficiency from the transportation system, the ideas of vehicle-to-subway (V2S) and vehicle-to-grid (V2G) are utilized to develop a bilateral power flow strategy (charging/discharging or idle mode) to provide the chief charging requirements of energy systems. In this regard, the proposed model suggests a novel stochastic architecture based on unscented transformation (UT) to handle the operational uncertainties of the transportation systems when considering the correlated power generation of wind turbines (WTs). Moreover, blockchain technology is deployed to guarantee the security of data transfer within the smart city. Hence, there is a secure collaboration within all sub-systems in the smart cities, which has triggered the integrated management in this structure. The simulation results are discussed on a typical smart city test system to show the quality of the proposed model.

AI-Based Autonomic and Scalable Security Management Architecture for Secure Network Slicing in B5G

The vital importance of securing 5G and beyond networks while meeting their stringent performance requirements has promoted the recent shift towards fully automated and smart security management. In this article, we introduce a novel autonomic and cognitive security management framework that empowers fine-grained zero-touch security management through different levels (i.e., network functions, sub-slice, and slice) and different administrative and technological domains. We showcase the compliance of the proposed framework with the ongoing standards (e.g., ZSM, 3GPP, and NFV) and demonstrate its feasibility by advocating for potential open source solutions to implement its functional blocks in a cloud-native service-based environment.

A Security Management Framework for Telecommunications in Africa

A Security Management Framework for Telecommunications in Africa

A Security Management Framework for Telecommunications in Africa

A Security Management Framework for Telecommunications in Africa