System Security Risk Research Articles

Research on Security Model of Airport Luggage Remote Office System Based on Zero Trust

With the continuous development of modern information society, remote office equipment itself has many benefits and is widely respected by the public, but at the same time, it also brings many network security issues. In order to help the airport luggage remote office system achieve stability and solve security issues encountered during luggage inspection, an analysis of existing system security risks based on the zero trust concept is conducted, including factors such as data leakage, insufficient monitoring, and incomplete identity authentication. Combined with the characteristics of the luggage system and remote office technology, the security model is ensured to be sufficiently reliable, providing some reference for airlines preparing to implement zero trust airport luggage remote office.

RiskTree: Decision Trees for Asset and Process Risk Assessment Quantification in Big Data Platforms

The inherent characteristics of big data lies in its voluminous scale, varied data formats, and swift processing velocity. The intrinsic characteristics of big data undermine the efficacy of conventional data security techniques and data management standards, consequently compromising the security of big data. As a consequence, big data possesses susceptibilities to security incidents, including unauthorized data access, data manipulation, and data compromise throughout the transmission, storage, and processing stages. Conventional information system security risk assessment methodologies are constrained by human resources and computational techniques, rendering them unsuitable for direct application to big data platforms. Consequently, there is an urgent necessity to develop a risk assessment framework tailored specifically for big data environments, capable of quantifying potential risks and losses. In response to this need, we have devised an automated risk assessment theory that assimilates the unique characteristics of big data with traditional quantitative methods, introducing a risk metric system suited to the big data context. Utilizing the risk-related data generated during operations on the big data platform, we train a decision tree model to derive the weights for each risk indicator. These weights are then employed to conduct a weighted summation of the operational risk indicators, thereby achieving a quantitative evaluation of the platform's risk profile. To substantiate the proposed framework, experiments were conducted on a simulated big data platform. The experimental outcomes demonstrate that, compared to existing quantitative risk assessment methodologies, our approach enables an automatic, objective, and efficient assessment and quantification of the risks associated with tangible assets and data processing operations within the big data platform.

Security Event-Trigger-Based Distributed Energy Management Of Cyber-Physical Isolated Power System With Considering Nonsmooth Effects.

Due to cyber-physical fusion and nonsmooth characteristics of energy management, this article proposes a security event-trigger-based distributed approach to address these issues with developed smoothing technique. To tackle with nonconvex and nondifferentiable issue, a randomized gradient-free-based successive convex approximation is developed to smooth economic objective function. Due to resilience ability against security issue, a security event-triggered mechanism-based distributed energy management is proposed to optimize social welfare, which coordinately controls both power generators and load demand. The security event-triggered mechanism is designed to reduce power system security risks, and relieve communication burden caused by smoothing calculation, the convergence of proposed distributed algorithm is also properly proved. According to those obtained results on both IEEE 9-bus and IEEE 39-bus systems, it reveals that the proposed approach can achieve good convergence performance and have less security risks than other alternatives, which also proves that the proposed approach can be a viable and promising way for tackling with energy management issue of cyber-physical isolated power system.

FINANCIAL TECHNOLOGY INNOVATION AND BANKING INDUSTRY TRANSFORMATION

This research aims to innovate in technology, finance, and transformation in the banking industry. The research method used in this research is qualitative. Qualitative research is a research method used to understand social phenomena in depth. This type of research is library research, which researchers carry out by collecting, studying, and analyzing references or sources. obtained in writing or written form, such as books, journals, articles, documents, and other sources of information that are significant to the topic or title being researched. The research results show that the impact of development technology on industry banking in Indonesia is positive, namely: Improvement Efficiency and Productivity: Adoption technology has brought significant enhancements to efficiency bank operations, with automation of processes and usage intelligence artificial to reduce costs and improve productivity. Enhancement Experience Customer: Innovation technology has allowed banks to increase customer experience through applications in digital banking, customer chatbot-based services, and self-service platforms. Enhancement Security and Management Risk: Although there are worries related to data security, development technology has the potential to repair significant system security and management risks. With the use of data encryption and analysis behavior, users can identify and respond to threats to security more quickly. Innovation Products and Services: Technology has pushed the development of new products and services in the banking industry, including robo-advisors, peer-to-peer lending platforms, and applications for mobile payments, which deliver a markup for customers and help banks expand their market share. Enhancement Efficiency and Transparency Management: System Management Integrated information and analytical dashboards have increased efficiency and transparency in bank management.

Development of a mechanism for information security risk management of transport service provision systems

The object of the study is the process of analysis, assessment, and management of information security risks in transport service provision systems. The problem of applying the information security risk management approach in the activities of transport business entities was investigated. As a result of the application of effective forms, methods, and means of information security risk management based on international standards, a risk management mechanism was developed. The risk assessment process of transport systems has been systematized. This allows business entities in the transport sector to determine ways to prevent and counter information threats and challenges in their activities, both when designing and operating systems for providing transport services. Verification of the devised methodical approach to information security risk management was carried out on an example of the taxi company «Taxifay N». Threats and challenges of the company’s information system were evaluated by an expert method. Based on the results of the analysis of expert risk assessment, it was found that the concordance coefficient (0.86) confirms the high level of agreement of experts’ opinions. As a result, the company’s information security risk management program was developed. The effectiveness of the program was assessed by the efficiency ratio, which was 0.64. This testifies to the effectiveness of the implemented program of measures to manage information security risks. The scope of application may be the activity of business entities that provide transport services to the population, aimed at data storage and processing. The prospect of this study is to expand the list of threats and categories of vulnerabilities depending on the characteristics of the economic activity of various enterprises

Gradient-guided hierarchical feature attack for object detector

Deep neural networks (DNNs) are vulnerable to adversarial attacks, which can cause security risks in computer information systems. Feature disruption attacks, as a typical form of adversarial attack, optimize adversarial examples by disrupting the intermediate features extracted by DNN. The existing feature disruption attacks have limitations when it comes to objects of different scales within resolution features, favoring low-resolution feature maps and low-scoring objects. The imbalance above affects their effectiveness in object detection tasks. Gradient-guided Hierarchical Feature Attack (GHFA) is proposed to solve these problems, which disrupts detector-extracted features using gradient-guided feature weighting. GHFA incorporates receptive field scaling and gradient scaling to balance the focus among feature maps and enhance attack performance. The evaluation of GHFA on 9 object detectors demonstrates its superior transferability compared with the 6 comparative methods, surpassing the second-ranked method by 2.4%. Furthermore, the real-world applicability of GHFA is validated available by testing it on a commercial online object detection platform.

Using Visual Cryptography, A Safe Online Payment Method

Due to the growing usage of online shopping and online payments in recent years, the E-Payment system has experienced enormous growth. The acceptance of electronic payments for offline transfers is made easier by an electronic payment system. An electronic payment system is a technique to conduct transactions or pay for goods and services online. Systems for electronic payments are now widely employed across all industries, including banking, finance, online commerce, and many more. There were some security risks in the conventional e-payment systems, including phishing, credit card fraud, and debit card fraud. In order to solve this issue, we developed an electronic payment system that combines visual and quantum cryptography methods for safe transmission. Quantum cryptography secures the transmission of the one-time password, whereas visual cryptography conceals customer information by creating shares. We adjusted our system using the email OTP notification mechanism for OTP processing. The share is securely transmitted to the bank thanks to image steganography, which embeds a one-time password in the share. The proposed approach offers unconditional security as opposed to the conventional E-payment mechanism. Key Words: One-time passwords, online payments, image processing Quantum cryptography, visual cryptography, and image encryption.

Research on reliable transmission and application security architecture of power IoT based on energy interconnection

Power Internet of Things (IoT) is an important support for digital innovation service of power energy internet, covering all aspects of power system. Power IoT security defense system may have customer data information leakage during transmission because of the use of traditional means of isolation. This paper proposes a reliable transmission and application security architecture for power smart IoT based on energy interconnection, aiming to solve the reliable transmission and security authentication problems existing in power systems. The paper first analyzes the security risk of the grid wise IoT system, proposes an effective power IoT security transmission scheme, and evaluates the safe and reliable transmission of the grid wise IoT system. Then designed a safe and reliable transmission of the grid smart IoT system, to deal with the traditional power network transmission security and communication security problems. The final application is in the construction of the security transmission platform of the wisdom park of Shanxi Electric Power Company, which provides the corresponding security protection capability in the power IoT through the situational awareness security measures of each layer, and realizes the reliable transmission and security application of the source network load storage and other links in the power IoT environment.

Network security risk detection method for smart microgrid monitoring system

AbstractAlthough the smart microgrid improves the power quality of the power system, it still has some security risks. So, this paper proposes a network security risk detection method of an intelligent microgrid monitoring system based on the artificial immune algorithm. By analyzing the structure of a smart microgrid monitoring system and introducing Policy Protection Detection Response (P2DR) dynamic network security model and ale static network security analysis method, the network security risk of the microgrid monitoring system is evaluated. The theoretical model is analyzed by the overall framework of the artificial immune algorithm, and its term definition is given. The mutation self is detected by self‐dynamic description and immune cell evolution process with the network structure brought into and the risk of the computing network facing different attack subjects is analyzed. This method has a high detection accuracy for more than 10 kinds of network attack modes, the highest detection accuracy is 98%, and the average time is only 0.8 s. Compared with other methods, this method has higher detection accuracy and faster detection speed. It is universal in various network attack modes and can detect the possible network security risks of the intelligent microgrid monitoring system and protect its safe and stable operation.

A Review Paper on New Approaches of Vulnerability

Vulnerability assessment is a critical process in identifying and mitigating potential security risks in various systems. With the increasing complexity and diversity of modern technologies, traditional vulnerability assessment methods may not be sufficient to address emerging threats effectively. In recent years, new approaches have emerged that leverage advanced techniques, including machine learning and artificial intelligence, to enhance the accuracy and efficiency of vulnerability assessment. In this review paper, we explore the latest developments in vulnerability assessment and provide a comprehensive analysis of various new approaches. We discuss the advantages and limitations of these approaches and provide insights into their practical applications.

Interrupt Stack Protection for Linux Kernel in Hardware Virtualization Layer of ARM64 Architecture

Kernel security is of paramount importance in computer systems. As the number of vulnerabilities in the kernel continues to grow, computer systems security risks are increasing. To prevent the kernel interrupt stack from being attacked, researchers provide discussion over complete hypervisor supervision and kernel co-layer security domain techniques. Complete hypervisor supervision brings a heavy overhead and co-layer security domain techniques cannot achieve privilege-level isolation. We focus on memory-based security threats in kernel security vulnerabilities, protecting the kernel at a higher level by using virtualization technology. Compared with the existing work, our implementation method achieves a small performance loss to protect the interrupt stack. We have implemented our system on openEuler operating systems and Phytium processors. Although the deployment of protection code will result in increased kernel interrupt latency and processor overhead, experimental verification shows that the overall system overhead is acceptable.

An Access Control Model Based on System Security Risk for Dynamic Sensitive Data Storage in the Cloud

In cloud computing, dynamic storage of data generated by users, applications, tasks, workflows, etc. requires frequent access operations, so traditional encryption cannot be applied in this case. Considering the vulnerability of dynamic data, its protection needs to consider an efficient and dynamic security protection scheme. In data-oriented access control, the traditional approach is generally static policy matching, which cannot deal with emergencies and has the problem of privileged users. To solve this problem, this paper proposes a data-oriented risk-based access control model, which adds risk assessment to the traditional attribute-based access control and aims at the source of risk from three aspects: subject attribute, resource attribute, and environment attribute. A set of risk assessment indexes is proposed, and the calculation method of risk assessment is quantitatively analyzed by combining fuzzy consistency AHP analysis method, and finally, the realization of XACML is given. The validity of the proposed model is analyzed, and the carried out experimental analysis verifies its effectiveness. The proposed model benefits cloud data storage applications that require dynamic data storage, for example, medical/patient data storage.

Defining Cyber Risk Scenarios to Evaluate IoT Systems

The growth of the Internet of Things (IoT) has accelerated digital transformation processes in organizations and cities. However, it has also opened new security challenges due to the complexity and dynamism of these systems. The application of security risk analysis methodologies used to evaluate information technology (IT) systems have their limitations to qualitatively assess the security risks in IoT systems, due to the lack of historical data and the dynamic behavior of the solutions based on the IoT. The objective of this study is to propose a methodology for developing a security risk analysis using scenarios based on the risk factors of IoT devices. In order to manage the uncertainty due to the dynamics of IoT behaviors, we propose the use of Bayesian networks in conjunction with the Best Worst Method (BWM) for multi-criteria decision-making to obtain a quantitative security risk value.

Vulnerability assessment of electrical and thermal cyber physical system considering dual coupling characteristics

With the continuous improvement of the informatization and intelligence of the Electrical and Thermal Cyber Physical System (ETCPS), the coupling between the various subsystems is getting closer and closer. When the system fails, due to the coupling characteristics, the system security risk is intensified. On this basis, the dual coupling characteristics of ETCPS have been analyzed according to the cyber physical model established first. Secondly, a two-state optimal scheduling model and comprehensive vulnerability (CV) index, which consider various characteristics of ETCPS, are established, and interactions between the subsystems are analyzed quantitatively. Then, the source load loss rate is defined, which quantifies system security risk. Finally, five vulnerability assessment methods as well as the proposed method are compared. The feasibility and rationality of the proposed method are proved by two test systems.

Probabilistic power flow calculation considering electro-thermo-mechanical dynamics of overhead conductor

Conductor temperature and tension are important physical states that determine the security of the overhead line. The states are sensitive to the line power flow and the meteorological conditions around the conductor that have strong uncertainty. In this paper, the electro-thermo-mechanical coupling dynamics of the power system are modeled. Then, focusing on the calculation of the distributions of the electro-thermo-mechanical dynamics (ETMDs) of critical spans under the uncertain operational environment of the power system, the implementation framework and the fast calculation methods for the probabilistic power flow considering electro-thermo-mechanical dynamics (PPF-ETMD) are proposed. The work presented in this paper provides an effective method for operators to capture distributions of the ETMDs of critical spans under the uncertain environment and detect the underlying system security risk based on the thermal and mechanical essence of the security of the overhead line. Numerical simulations based on a regional power system in China and the IEEE 300-node system are carried out to verify the effectiveness of the proposed method.

Security Risk Intelligent Assessment of Power Distribution Internet of Things via Entropy-Weight Method and Cloud Model.

The current power distribution Internet of Things (PDIoT) lacks security protection terminals and techniques. Network security has a large exposure surface that can be attacked from multiple paths. In addition, there are many network security vulnerabilities and weak security protection capabilities of power distribution Internet of Things terminals. Therefore, it is crucial to conduct a scientific assessment of the security of PDIoT. However, traditional security assessment methods are relatively subjective and ambiguous. To address the problems, we propose to use the entropy-weight method and cloud model theory to assess the security risk of the PDIoT. We first analyze the factors of security risks in PDIoT systems and establish a three-layer PDIoT security evaluation index system, including a perception layer, network layer, and application layer. The index system has three first-level indicators and sixteen second-level indicators. Then, the entropy-weight method is used to optimize the weight of each index. Additionally, the cloud model theory is employed to calculate the affiliation degree and eigenvalue of each evaluation index. Based on a comprehensive analysis of all evaluation indexes, we can achieve the security level of PDIoT. Taking the PDIoT of Meizhou Power Supply Bureau of Guangdong Power Grid as an example for empirical testing, the experimental results show that the evaluation results are consistent with the actual situation, which proves that the proposed method is effective and feasible.

Analyzing Security Risks in Cyber-Physical Manufacturing Systems with Actor–Network Theory

Abstract This article suggests that actor–network theory (ANT) can reveal unique challenges and consequences of cyberattacks in manufacturing. As an approach, ANT rejects the dualism that often separates humans and nonhumans, recognizing the active role of both in affecting events. Our approach adds an important new perspective to an existing body of research that focuses on analyzing vulnerabilities in cyberspace instead of their ramifications in the material world. Drawing on the case study of a faulty airbag inflator in an automobile, we use concepts and vocabularies drawn from ANT to discuss the consequences of attacks in manufacturing, such as viewing altered products as actants with agency to alter subsequent networks (e.g., when a manufactured part is integrated into an automotive vehicle). By tracing the movement of specific materials and products through networks it is possible to elucidate how cyberattacks not only impact cyber-physical systems themselves, but also reverberate into a multitude of broader impacts, potentially endangering physical safety, shaping public opinion, and influencing economic markets. Our examination of one particular context draws on existing work that has brought ANT and cybersecurity in dialogue, but we extend this work by focusing on the role of “translation” and “depunctualization” across the lifecycle of a cyberattack in manufacturing. This analysis stresses the need for sector-specific examinations of cyberthreats, while also demonstrating the value of interdisciplinary methods like ANT that do not reify artificial dualisms in addressing for conceptualizing security risks in cyber-physical manufacturing systems.

JISWorkshop on Robotic Process Automation (RPA) Research: Views from RPA Industry Leaders and AIS Researchers

<i>JIS</i>Workshop on Robotic Process Automation (RPA) Research: Views from RPA Industry Leaders and AIS Researchers

Measuring development assistance for health systems strengthening and health security: an analysis using the Creditor Reporting System database

Background: Health systems strengthening (HSS) and health security are two pillars of universal health coverage (UHC). Investments in these areas are essential for meeting the Sustainable Development Goals and are of heightened relevance given the emergence of the 2019 novel coronavirus disease (COVID-19). This study aims to generate information on development assistance for health (DAH) for these areas, including how to track it and how funding levels align with country needs. Methods: We developed a framework to analyze the amount of DAH disbursed in 2015 for the six building blocks of the health system (‘system-wide HSS’) plus health security (emergency preparedness, risk management, and response) at both the global (transnational) and country level. We reviewed 2,427 of 32,801 DAH activities in the Creditor Reporting System (CRS) database (80% of the total value of disbursements in 2015) and additional public information sources. Additional aid activities were identified through a keyword search. Results: In 2015, we estimated that US$3.1 billion (13.4%) of the US$22.9 billion of DAH captured in the CRS database was for system-wide HSS and health security: US$2.5 billion (10.9%) for system-wide HSS, mostly for infrastructure, and US$0.6 billion (2.5%) for system-wide health security. US$567.1 million (2.4%) was invested in supporting these activities at the global level. If responses to individual health emergencies are included, 7.5% of total DAH (US$1.7B) was for health security. We found a correlation between DAH for HSS and maternal mortality rates, and we interpret this as evidence that HSS aid generally flowed to countries with greater need. Conclusions : Achieving UHC by 2030 will require greater investments in system-wide HSS and proactive health emergency preparedness. It may be appropriate for donors to more prominently consider country needs and global functions when investing in health security and HSS.

Security risks in cyber physical systems—A systematic mapping study

AbstractThe increased need for constant connectivity and complete automation of existing systems fuels the popularity of Cyber Physical Systems (CPS) worldwide. Increasingly more, these systems are subjected to cyber attacks. In recent years, many major cyber‐attack incidents on CPS have been recorded and, in turn, have been raising concerns in their users' minds. Unlike in traditional IT systems, the complex architecture of CPS consisting of embedded systems integrated with the Internet of Things (IoT) requires rather extensive planning, implementation, and monitoring of security requirements. One crucial step to planning, implementing, and monitoring of these requirements in CPS is the integration of the risk management process in the CPS development life cycle. Existing studies do not clearly portray the extent of damage that the unattended security issues in CPS can cause or have caused, in the incidents recorded. An overview of the possible risk management techniques that could be integrated into the development and maintenance of CPS contributing to improving its security level in its actual environment is missing. In this paper, we are set out to highlight the security requirements and issues specific to CPS that are discussed in scientific literature and to identify the state‐of‐the‐art risk management processes adopted to identify, monitor, and control those security issues in CPS. For that, we conducted a systematic mapping study on the data collected from 312 papers published between 2000 and 2020, focused on the security requirements, challenges, and the risk management processes of CPS. Our work aims to form an overview of the security requirements and risks in CPS today and of those published contributions that have been made until now, towards improving the reliability of CPS. The results of this mapping study reveal (i) integrity authentication and confidentiality as the most targeted security attributes in CPS, (ii) model‐based techniques as the most used risk identification and assessment and management techniques in CPS, (iii) cyber‐security as the most common security risk in CPS, (iv) the notion of “mitigation measures” based on the type of system and the underline internationally recognized standard being the most used risk mitigation technique in CPS, (v) smart grids being the most targeted systems by cyber‐attacks and thus being the most explored domain in CPS literature, and (vi) one of the major limitations, according to the selected literature, concerns the use of the fault trees for fault representation, where there is a possibility of runtime system faults not being accounted for. Finally, the mapping study draws implications for practitioners and researchers based on the findings.