Impact Of Cyber Attacks Research Articles

3-layer modelling method to improve the cyber resilience in Industrial Control Systems

Cyberattacks against Industrial Control Systems (ICS), which play a crucial role in many industrial domains, could bring environmental and safety damages as well as huge economic loss. To decrease such cybersecurity risks, it is needed to improve the cyber resilience, that is the capability to respond to and recover from the threat in case cyberattacks occur. To this end, we propose the 3-layer modelling method that reproduces ICS by the actor, asset, and process models. The modelling approach based on Petri-Nets is used to express the state of all models in time series and quantify the availability of ICS influenced by cyberattacks, considering the behavior of personnel involving both cybersecurity and industrial operations. To demonstrate the effectiveness, resilience curves, which draw the availability as a function of time, are finally calculated for multiple cases of cyberattacks, assuming a hypothetical manufacturing factory. As a result, the production rate, which represents the availability of the manufacturing industry, is calculated in time series. The resilience curve can be used to determine what and when to do to minimize the impact of cyberattacks, which leads to the improvement of the cyber resilience.

The Impact of Cyber Attack on Emergency Energy System

An emergency energy system is a backup power system used in critical situations with the aim of protecting lives and property from the consequences of energy loss, as is the case in hospitals (heart monitors, Ventilator,…etc), and also in sensitive facilities (military industries and government buildings). The emergency power system can contain batteries of all kinds, in addition to solar and wind energy equipment and other cheap types of energy. The concept of cyber security arose several decades after the invention of the computer. At first, there was no need for cyber security, as it was difficult for electronic attacks to occur, because access to computers was limited to specific numbers of users, as the devices were giant confined to a room with certain specifications and were not Linked to networks at the time, Energy sectors expose themselves to a range of cyber threats that can damage control systems. So management, engineering, and IT must adhere to a comprehensive approach that includes threat prevention, detection, and elimination. In this research we will try to mitigate the effects of the cyber attack on these systems by applying some algorithms in order to detect, identify and prevent such attacks, and we will see through the results we obtained that we have made remarkable progress in this field.

Exploring Customer Awareness towards Their Cyber Security in the Kingdom of Saudi Arabia: A Study in the Era of Banking Digital Transformation

The annual rate of cybersecurity breaches has risen in the last few years, exposing millions of records in some cases. The average data breach cost in 2021 was a massive $4.24 million. This study examines customer awareness and satisfaction with cybersecurity in the context of the digital transformation of banking in Saudi Arabia. The study is empirical and based on the data collected from 355 banking customers in Saudi Arabia. Three significant aspects of cybersecurity, including cyberattacks, phishing, and hacking, have been analyzed through various dimensions. Customer satisfaction with bank cybersecurity assistance and their expectations of technical support and services on cybersecurity has also been studied. ANOVA and bivariate regression analysis are used to study the impact of cyberattack, phishing, hacking, cybersecurity assistance, and expectations on cybersecurity’s technical awareness on customer satisfaction. The results show that digital transformation has boosted the banking sector, and users benefit from online services. However, an increase in the awareness level of customers on cyberattack, phishing, and hacking activities will influence customers’ satisfaction with digital transactions. The results also revealed that customers need more satisfaction on security level aspects from the bank’s side, and banks should provide regular training programs to safeguard customers from cyberattacks. If banks prepare more secure cybersecurity management, their long-term sustainability goals could be easily achieved.

Impact of cyber-attacks on the financial institutions

In this paper we are presenting the impact of cyber-attacks on the financial institutions and highlighting the potential impact of these attacks on the global economy.Given their role in the economy the financial institutions are necessary to ensure liquidity, to guarantee the money supply in the economy, provide loans, savings and deposits, but also to ensure payments and settlements are made. Financial institutions are the backbone of the economy. Due to this last the impact of cyber-attacks against the financial institutions can have very severe effects.We will examine the increase of cyber-attack vectors financial institutions are facing, the methods of attack most used by cybercriminals. The impact of COVID-19 and large-scale attacks are huge topics; thus, we will only analyze their direct impact on the financial institutions. We will review the possible cyber security measures: strategies and DLT as a possible solution against cyber threats. Finally, we will touch the topic of cyberwarfare.

Quantifying Impact on Safety from Cyber-Attacks on Cyber-Physical Systems

We propose a novel framework for modeling attack scenarios in cyber-physical control systems: we represent a cyber-physical system as a constrained switching system, where a single model embeds the dynamics of the physical process, the attack patterns, and the attack detection schemes. We show that this is compatible with established results in hybrid automata, namely, constrained switching linear systems. The proposed attack modeling approach admits a large class of non-deterministic attack policies and enables the characterization of system safety as an asymptotic property. By calculating the maximal safe set, the resulting new impact metrics intuitively quantify the degradation of safety and the impact of cyber attacks on the safety properties of the system under attack. We showcase our results via an illustrative example.

The impact of cyber-attacks on the stock prices and bid-ask spreads of target firms: Australian evidence

The impact of cyber-attacks on the stock prices and bid-ask spreads of target firms: Australian evidence

Cyber Resilience, a Survey of Case Studies

Considering the potential magnitude and impact of cyber-attacks, organizations must be able to understand their capabilities to prevent, respond and re-cover from these attacks as well to implement and refine adequate resilience plans. Due to the importance of cyber resilience, this survey aimed to review relevant case studies published in the scientific literature. The identified case studies followed different approaches since some of them were focused on risk assessment and risk management processes and the complexity of their implementation, while others were focused on the use of well-known frameworks to assess cyber resilience or on proposing new cyber resilience frameworks and tools.

An LMI-Based Risk Assessment of Leader–Follower Multi-Agent System Under Stealthy Cyberattacks

This paper proposes a methodology for assessing the potential risk from cyberattacks in multi-agent systems (MASs). MASs inherently rely on communication between agents, rendering them more vulnerable to cyberattacks than single-agent systems. The impact of cyberattacks could lead to performance disruption and safety violations. To address these concerns, we propose a risk assessment method for MASs using reachability analysis which computes the reachable set of the MASs via a Lyapunov function and its corresponding linear matrix inequalities (LMIs). The proposed method can quantify the potential risk against cyberattacks at agent and entire system levels by deriving ellipsoidal over-approximated reachable sets. An illustrative example is provided to validate the potency of the method, which shows the risk associated with the formation control of a leader-following MAS in an adversarial environment with scattered obstacles.

WAMS-Based HVDC Damping Control for Cyber Attack Defense

Owing to the fast and large power regulating the capacity of the HVDC system, the wide-area measurement system (WAMS) based high voltage direct current (HVDC) system has been regarded as a prospective solution to deal with the low-frequency oscillation issue. However, due to the vulnerability of the WAMS communication, WAMS based HVDC system control can be a prime target of malicious penetrations that could lead to disastrous events. To remediate this adverse effect, an improved WAMS based HVDC damping control framework is proposed. First, a lightweight network named Attack Shuffle convolutional neural Networks (ASNet) is proposed to learn the characteristics of cyber attacks. Then, a model-free-based cyber attack defense framework is introduced to quickly identify the attack types based on the continuous wavelet transform and ASNet. Additionally, an improved control framework of the WAMS and HVDC-based wide-area power oscillation damping control (WH-PODC) is developed to provide different response control for mitigation of the impact of cyber attacks. Finally, the performance of the proposed WH-PODC control framework is evaluated with real PMU data in multiple scenarios in RTDS, where the results indicate that the response intensity can be kept under multiple types of cyber attacks while providing similar effectiveness in oscillation suppression to conventional controls.

Systematic assessment of cyber-physical security of lane keeping control system for autonomous vehicles

In this article, a systematic assessment of cyber-physical security is developed for the lane-keeping control (LKC) system of autonomous vehicles (AVs), which has not been attempted before. A novel impact analysis methodology for typical cyber-attacks is proposed with new evaluation metrics from the viewpoint of safety and performance and innovative index-based resilience and security criteria. Specifically, a security criterion is investigated by tracking performance, comfort and vehicle stability to evaluate the safety and security of the vehicle LKC system. Hardware-in-the-Loop (HiL) experimental results show that the proposed evaluation metrics are effective in analyzing the impact of cyber-attacks on the commercial LKC system of Dongfeng Motor comprehensively. Finally, the conclusion provides guidelines for attack detection, diagnosis, and countermeasures for AVs.

MCAD: A Machine Learning Based Cyberattacks Detector in Software-Defined Networking (SDN) for Healthcare Systems

The healthcare sector deals with sensitive and significant data that must be protected against illegitimate users. Software-defined networks (SDNs) are widely used in healthcare systems to ensure efficient resource utilization, security, optimal network control, and management. Despite such advantages, SDNs suffer from a major issue posed by a wide range of cyberattacks, due to the sensitivity of patients’ data. These attacks diminish the overall network performance, and can cause a network failure that might threaten human lives. Therefore, the main goal of our work is to propose a machine learning-based cyberattack detector (MCAD) for healthcare systems, by adapting a layer three (L3) learning switch application to collect normal and abnormal traffic, and then deploy MCAD on the Ryu controller. Our findings are beneficial for enhancing the security of healthcare applications by mitigating the impact of cyberattacks. This work covers the testing of MCAD using a wide spectrum of both ML algorithms and attacks, and provides a performance comparison for every pair of ML algorithms/attacks to illustrate the strengths and weaknesses of different algorithms against a specific attack. The MCAD shows impressive performance, achieving an F1-score of 0.9998 and of 0.9882 on normal and attack classes, respectively, which implies a high level of reliability. MCAD also achieved 5,709,692 samples per second on throughput, which reflects a high-performance real-time system with respect to complexity. Additionally, it showed a positive impact on the network KPIs by increasing the throughput by 609%, and decreasing delay and jitter by 77% and 23%, respectively, compared to attack results.

A methodology for empirical research and analysis in the field of cybersecurity

This article is considered to be a continuation of a publication by the author devoted to an algorithm for steganographic embedding of encrypted files in raster images (Yearbook Telecommunication, №9, 2022). The aim of this paper is proposing a methodology for empirical research and analysis on the field of cybersecurity which to contribute to various areas in cybersecurity. Its originality is expressed in the joint application of methods for research and analysis realized by various simulation environments for conducting experiments. This methodology has a specific structure as it is conditionally divided into two major parts depending on the type of the simulation process and software products used – a study of the direct impact of cyberattacks on communication networks by the method of the agent-based modelling and a study of potential steganography attacks using software for simulation of Artificial Neural Networks (ANNs) for the purposes of steganalysis.

Cyber-Attack and Reliability Monitoring of The Synchrophasor Smart Grid Network

The recent advancement of synchrophasor measurements technology in the conventional power grid can monitor and control the state variables of the network very accurately at a high sampling rate in real-time. The complete observability of system states can be achieved through the Phasor Measurement Unit (PMU). The inclusion of a zero injection bus (ZIB) optimized the total number of PMU requirements for complete observation of the synchrophasor network. The communication channels between measurement devices and control centers are highly vulnerable to cyber threats. Thus, an anomaly that occurs with PMU devices during a cyber-attack can affect the system’s reliability. Therefore, monitoring the reliability of the synchrophasor network has become essential for healthy power operation. Synchrophasor measurement technology can enhance wide-area surveillance and security functionality. However, the dependability of such technologies in the context of information network accessibility has yet to be investigated in a coherent model. Growing electric grid defence levels to mitigate the impact of cyber-attacks is essential. The cumulative effect of synchrophasor network observability and reliability is discussed in this paper by optimizing the number of PMUs deployed and the interruption load that occurs during an anomaly with PMU while taking ZIB into account.The backup PMU deployment modeling is also presented to secure the reliability and observability of the grid network during an anomaly occurs with PMU. The indices, Interrupted Load Probability Index (ILPI) and Expected Demand Not Supplied (EDNS), are used to evaluate the reliability of synchrophasor grid networks by integrating the state probability of PMU unavailability due to cyber intrusion.

A Proactive Protection of Smart Power Grids against Cyberattacks on Service Data Transfer Protocols by Computational Intelligence Methods.

The article discusses an approach to the construction and operation of a proactive system for protecting smart power grids against cyberattacks on service data transfer protocols. It is based on a combination of computational intelligence methods: identifying anomalies in network traffic by evaluating its self-similarity, detecting and classifying cyberattacks in anomalies, and taking effective protection measures using Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) cells. Fractal analysis, mathematical statistics, and neural networks with long short-term memory are used as tools in the development of this protection system. The issues of software implementation of the proposed system and the formation of a data set containing network packets of a smart grid system are considered. The experimental results obtained using the generated data set demonstrated and confirmed the high efficiency of the proposed proactive smart grid protection system in detecting cyberattacks in real or near real-time, as well as in predicting the impact of cyberattacks and developing efficient measures to counter them.

Protection of accounting information in the conditions of cyber security

In the given study, it is substantiated that the unauthorized use of information generated in the accounting system can lead to harmful consequences, risking loss of information, incorrect data entry and misuse of confidential information. Therefore, the issue of protecting information generated in the accounting system is extremely urgent, and ensuring its security is a priority in many companies. The purpose of the study was to generalize existing approaches and outline promising directions for the organization of accounting information protection in the context of cyber security. It has been proven that effective communication and joint strategies between management, accountants and auditors are important to reduce or protect against emerging threats to the accounting information system. To properly assess potential risks, accountants and auditors must be familiar with current and emerging technologies. Groups of risks are given, based on the selection of risks for all components of the accounting process, which are inherent in electronic accounting information systems (risks associated with the collection and input of data into an automated system, risks associated with information processing and its storage on electronic media, risks associated with stage of generalization and transfer of information) and analyzed their features in order to find ways of minimization. Controlling unauthorized access to accounting records is an important component of internal control. Access and password policies, encryption, digital signatures, disk locks, firewalls, and digital certificates are examples of controls that should be identified, documented, communicated, and tested when evaluating control effectiveness. Examples of the impact of cyberattacks on the accounting system and related costs are given. It is well-founded that the protection of accounting information and the avoidance of cyber-attacks is possible only if comprehensive measures and joint actions of management, accounting, auditors and educational institutions are followed in the training of future specialists.

Secure State Estimation of Cyber-Physical System under Cyber Attacks: Q-Learning vs. SARSA

This paper proposes a reinforcement learning (RL) algorithm for the security problem of state estimation of cyber-physical system (CPS) under denial-of-service (DoS) attacks. The security of CPS will inevitably decline when faced with malicious cyber attacks. In order to analyze the impact of cyber attacks on CPS performance, a Kalman filter, as an adaptive state estimation technology, is combined with an RL method to evaluate the issue of system security, where estimation performance is adopted as an evaluation criterion. Then, the transition of estimation error covariance under a DoS attack is described as a Markov decision process, and the RL algorithm could be applied to resolve the optimal countermeasures. Meanwhile, the interactive combat between defender and attacker could be regarded as a two-player zero-sum game, where the Nash equilibrium policy exists but needs to be solved. Considering the energy constraints, the action selection of both sides will be restricted by setting certain cost functions. The proposed RL approach is designed from three different perspectives, including the defender, the attacker and the interactive game of two opposite sides. In addition, the framework of Q-learning and state–action–reward–state–action (SARSA) methods are investigated separately in this paper to analyze the influence of different RL algorithms. The results show that both algorithms obtain the corresponding optimal policy and the Nash equilibrium policy of the zero-sum interactive game. Through comparative analysis of two algorithms, it is verified that the differences between Q-Learning and SARSA could be applied effectively into the secure state estimation in CPS.

Security Issues and Solutions for Connected and Autonomous Vehicles in a Sustainable City: A Survey

Connected and Autonomous Vehicles (CAVs) combine technologies of autonomous vehicles (AVs) and connected vehicles (CVs) to develop quicker, more reliable, and safer traffic. Artificial Intelligence (AI)-based CAV solutions play significant roles in sustainable cities. The convergence imposes stringent security requirements for CAV safety and reliability. In practice, vehicles are developed with increased automation and connectivity. Increased automation increases the reliance on the sensor-based technologies and decreases the reliance on the driver; increased connectivity increases the exposures of vehicles’ vulnerability and increases the risk for an adversary to implement a cyber-attack. Much work has been dedicated to identifying the security vulnerabilities and recommending mitigation techniques associated with different sensors, controllers, and connection mechanisms, respectively. However, there is an absence of comprehensive and in-depth studies to identify how the cyber-attacks exploit the vehicles’ vulnerabilities to negatively impact the performance and operations of CAVs. In this survey, we set out to thoroughly review the security issues introduced by AV and CV technologies, analyze how the cyber-attacks impact the performance of CAVs, and summarize the solutions correspondingly. The impact of cyber-attacks on the performance of CAVs is elaborated from both viewpoints of intra-vehicle systems and inter-vehicle systems. We pointed out that securing the perception and operations of CAVs would be the top requirement to enable CAVs to be applied safely and reliably in practice. Additionally, we suggested to utilize cloud and new AI methods to defend against smart cyber-attacks on CAVs.

An Improved Model to Analyze the Impact of Cyber-Attacks on Power Systems

An Improved Model to Analyze the Impact of Cyber-Attacks on Power Systems

Cyber-attack research for integrated energy systems by the correlated matrix based object-oriented modeling method

The rise of an integrated energy system requires the integration of multiple sources of energy to be embraced and transited over the power grid; that means the information and communication systems of traditional power systems will be extended, and their complexity will be increased. As the information and communication systems play a more important role in the infrastructure of the power system, a cyber-attack on them may have an impact on the power system and cause a serious threat to the integrated energy system. To analyze the threat to the complex and integrated system, some researchers provide some modeling methods to study the impact of cyber-attacks on the information and communication systems, such as the Attack Tree Model, Attack Graph Model, Petri Net Model for cyber-attack, Attack Description Language Model, State Transition Graph Model, etc. However, these modeling methods have some shortcomings. For example, they cannot describe the systematical cyber-attack and show the secure status during the cyber-attack; it is hard for them to analyze the larger and more complicated information and communication systems. To overcome the shortages, in this paper, a correlated matrix-based object-oriented model is proposed for cyber-attack modeling. With this model, the relationship between the attacker and victim can be directly built; the cyber-attack path and packets from the attacker can be tracked; and the status of the nodes and links can be shown during a cyber-attack. There are two steps to build the cyber-attack model. Firstly, the procedure and approach of the cyber-attack will be modeled by an object-oriented method; then, a correlated matrix model will be built for network topology, attack path, and attack procedure. By combining these two models, the whole cyber-attack model is created. Finally, to demonstrate the modeling method and its benefits, we use the MITM (Man-in-the-middle Attack) attack on measurement data of an AVC (Automation Voltage Control) system as examples, and build a hardware-in-the-loop (HIL) co-simulation platform to verify the model.

Cyber attack awareness and prevention in network security

<span>This article aims to provide an overview of cyber attack awareness and prevention in network security. This article discussed the different types of cyber attacks, current trends of cyber attacks, how to prevent cyber attacks and uum students' awareness of cyber attacks. First, we will go over the different types of cyber attack, current trend, impact of cyber attack and the prevention. The approach entailed comparing and observing the outcomes of 13 different papers. The survey's findings would demonstrate the results obtained after analyzing the data collection which are the questionnaire filled out by respondents after watching the cyber attack awareness video to improve awareness of students through the cyber attack. Depending on the outcome of this survey, we will have a better understanding of current students' knowledge and awareness of cyber attacks, allowing us to improve students' understanding of cyber threats and the necessity of cyber security.</span>