Deliberate Attacks Research Articles

Investigating Electromagnetic Interference Induced Risks for Autonomous Driving

Abstract. The results of immunity tests on components of self-driving automobiles to radiated high power electromagnetic (HPEM) pulses are presented in this work. It is of particular interest to investigate such automobiles' resilience towards deliberate attacks with electromagnetic interference (EMI). Different types of HPEM capabilities at the Bundeswehr Research Institute for Protective Technologies and CBRN Protection (WIS) in Munster are applied for this investigation. Two types of automotive components have been tested, a two-axis acceleration sensor and an electronic power steering unit. Statistics of errors from the devices under test (DUTs), as well as a characterization of the applied pulses are presented. A correlation can be drawn between the pulse repetition rate or the amplitude of the applied pulses and the severity of the effect on the DUTs.

Overload cascading failure detection algorithm for multi-layer supply chain network considering delay probability factor

At present, the supply chain is multi-layered and complicated, and its failure detection is based solely on the characteristic threshold, which does not lack the ability to describe the complex supply chain. An overload cascading failure detection algorithm for multi-layer supply chain network considering delay probability is proposed. Based on the multi-layer supply chain network including raw material suppliers, manufacturers, distributors and retailers, the overload cascading failure model of the multi-layer supply chain network is constructed through networking, and the overload cascading failure process of the multi-layer supply chain network is described through three aspects: initial load, node capacity and overload node load distribution. By monitoring and analyzing the status update messages of each node in the supply chain network, and considering the delay probability factor, the node and path that may lead to cascading failure are identified by predicting the delay probability of the next message through the historical message delay probability, and the overload cascading failure detection of the multi-layer supply chain network is realized. The experimental results show that the algorithm can effectively detect the failure of each overloaded enterprise node in the multi-layer supply chain network, which is helpful to enhance the early warning and response ability of the cascade failure of the supply chain network. The algorithm can realize the failure detection of supply chain network under different attack conditions and initial failure ratio of nodes, and measure the anti-risk ability of supply chain network. Under deliberate attack and when the initial attack node is a supplier network layer node, it has a greater impact on the multi-layer supply chain network.

Resilience optimization analysis of smart mining cluster cyber-physical systems based on the NK model

This paper explores the challenges and opportunities presented by the digitization and intelligent clustering in the mining industry, focusing on the security and inter-system influences within Cyber-Physical Systems (CPS) of smart mining clusters. Utilizing the NK model and complex adaptive systems theory, we construct a dual-layered network and cascade failure model, alongside a dynamic repair strategy that adapts to environmental changes. By analyzing the critical parameters of node number (N) and relationship density (K), we assess the resilience of smart mining CPS under cascade failures with dynamic repairs. Our findings reveal that dynamic repair strategies significantly enhance network resilience against both random and deliberate attacks, with N and K acting as crucial regulators of repair effectiveness. This suggests that adapting N and K can improve repair outcomes and system resilience, despite increasing complexity. The paper discusses the practical implications of these strategies through simulation and real-world scenarios, highlighting the need for adaptive repair strategies in enhancing smart mining CPS resilience and process safety. Introducing the NK model to CPS resilience research offers new insights into the resilience of smart mining cyber-physical systems and provides a comprehensive risk analysis method for these systems in complex scenarios.

Research on the Robustness of Command and Control Networks under Cascading Failures

The current analysis of cascading failures in command and control networks pays little attention to their roles and mechanisms, resulting in challenges in quantifying survivability evaluation metrics and limiting practical application. To address these issues, this paper designs a command and control network model with a recovery strategy to improve the scientific evaluation of critical nodes and enhance the reliability of subsequent cascading failure simulations. Two capacity parameters are introduced to analyze the nonlinear behavior between network node load and capacity, and an optimal recovery strategy is proposed. This strategy prioritizes the recovery of critical nodes, thereby minimizing the overall probability of network failure. Simulations were conducted under both random failure and deliberate attack scenarios, comparing the proposed strategy with random recovery and betweenness-priority recovery strategies to identify the optimal recovery approach. The experiments showed that the optimal recovery strategy significantly enhanced the network’s survivability and recovery efficiency, allowing for the restoration of basic network functions in the shortest possible time and reducing the impact of cascading failures. By integrating the operability and uncertainty of real-world command and control networks, this method improved the network’s recovery capability and overall stability in the face of cascading failures through scientific evaluation and strategy optimization.

Targeting attack activity-driven networks.

Real-world complex systems demonstrated temporal features, i.e., the network topology varies with time and should be described as temporal networks since the traditional static networks cannot accurately characterize. To describe the deliberate attack events in the temporal networks, we propose an activity-based targeted attack on the activity-driven network to investigate temporal networks' temporal percolation properties and resilience. Based on the node activity and network mapping framework, the giant component and temporal percolation threshold are solved according to percolation theory and generating function. The theoretical results coincide with the simulation results near the thresholds. We find that targeted attacks can affect the temporal network, while random attacks cannot. As the probability of a highly active node being deleted increases, the temporal percolation threshold increases, and the giant component increases, thus enhancing robustness. When the network's activity distribution is extremely heterogeneous, network robustness decreases consequently. These findings help us to analyze and understand real-world temporal networks.

Critical lines dynamic identification for grid-connected wind power system under N-k contingency based on Oscillating equations

Abstract As the penetration rate of wind power and other renewable energy sources increases, power systems are more prone to experiencing multiple component failures, known as N-k contingency Identifying and then closely monitoring and protecting critical components during N-k contingency can effectively prevent widespread cascading failures. The primary task in identifying critical components is to model the power system; A refined model better captures the time-varying characteristics of electrical components. Therefore, a dynamic model of line power flow decay and oscillation based on swing equations is established; it introduces time-varying saturated cut-set and transfer margin indices to identify critical lines. Simulations on the IEEE-118 nodes system, along with MATCASC cascading failure simulations, demonstrate that targeting identified critical lines as deliberate attack points in the grid results in a normalized remaining load demand decrease to 50% of the original.

Causes and Consequences of Conflicts Among Agricultural Communities in Ethiopia: The Case of Tisho Kebele’s Deliberate Attacks on the Yebeno People in Burji Zone, Southern Ethiopia

This research was conducted in Burji zone South Ethiopia region. The main intent of the paper was to assess the causes and consequences of Tisho kebele’s deliberate attacks on Yebeno people in mid of April 2024. More precisely, the research was aimed to identify the underlying causes, to investigate the socio-economic effects of the conflicts, to assess the responses provided by Burji zone government to arisen conflict and to propose intervention strategies to end the conflict. As a result, the study employed a descriptive research design and followed qualitative research approach. Besides, the primary data of the study was collected from the kebele leaders, elders and religious leaders through focus group discussions and in-depth interviews. To select the respondents who have ample understanding about the conflict the researcher was used the purposive sampling techniques. Moreover, the conceptual information about the conflict was collected from secondary data sources such as journals and articles. Above all, the deliberate attack of Tisho kebele on the Yebeno people were out of the norm of Burji people in their long time history and it was destructive in nature. Due to this, a number of people were displaced and wounds within combination of burning and stealing of resources that estimated in millions of Birr. Thus, it is expected from the concerned stakeholders to search ways how to resolve the arisen conflict as soon as possible.

Spatial Structure and Vulnerability of Container Shipping Networks: A Case Study in the Beibu Gulf Sea Area

Ports play an important role in maintaining the effectiveness of maritime logistics. When ports encounter congestion, strikes, or natural disasters, the maritime container transportation network might be significantly affected. The Beibu Gulf sea area is a key channel to supporting China’s participation in international economic cooperation in the western region. It is highly susceptible to the influence of the political and economic instability. This study introduces a dual-component framework to analyze the inherent structure and potential vulnerabilities of the container transportation network in the Beibu Gulf Sea areas. The findings show that the core layer of the network exhibited circular solidification characteristics. The entire network heavily relies on some core ports, such as Haiphong Port, Ho Chi Minh Port, and Qinzhou Port, and it highlights the potential increases in vulnerability. The finding shows that deliberate attacks have a greater impact than random attacks on the normal operations of maritime networks. If ports with high intermediary centrality are attacked, the connectivity and transportation efficiency of the Beibu Gulf maritime network will be significantly affected. However, under such circumstances, redistributing cargo transportation through route adjustments can deal with the transmission of cascading failures and maintain the network’s resilience. Based on the existing knowledge and the data collected in a case study, this research stands out as the first to provide a critical examination of the spatial structure and vulnerability of container shipping networks in the Beibu Gulf sea.

Evaluation of ecological network resilience using OWA and attack scenario simulation in the Gansu section of the Yellow River Basin, NW China

Regional ecosystem quality has been rapidly declining as a result of rapid urbanization, which has also fragmented landscapes and reduced ecosystem connectedness. Strengthening ecological network resilience helps improve the ecological environment’s quality, protect biodiversity, and maximize ecological benefits. To quantitatively assess ecological network resilience based on 2020 data, we have selected the Gansu region of the Yellow River Basin as a case study in this study due to its significant ecological condition and sensitive vulnerability. Firstly, based on four ecosystem services (ESs)—water yield, carbon storage, soil conservation, and habitat quality—the ordered weighted averaging (OWA) method is introduced to determine ecological sources by calculating ordered weights under different risk coefficients to weigh multiple ESs. Two node attack simulations—random attack and deliberate attack—are used for quantitatively evaluating ecological network resilience, which can simulate the impact of external interference. The concept of a resilience threshold is introduced into the evaluation process of network resilience to improve the objectivity and accuracy of results. The findings indicate that (1) 156 ecological corridors spanning a total distance of 6,569.3 km and 73 ecological sources totalling 20,840 km2 were found in the study area. These findings generally demonstrate a concentrated and contiguous configuration in the southwestern region and a broken and scattered configuration in other regions. (2) With a mean degree of 4.27, a mean path length of 4.08, and a clustering coefficient of 0.47, an undirected and unweighted complex network with improved connectivity and no discernible clustering characteristics was established. (3) The ecological network is more resilient to perturbations from natural disasters when compared to assault simulations in two scenarios; the resilience threshold is 0.34. Considering the final results of node global features and resilience curves, ecological protection suggestions are proposed.

International Humanitarian Law and Business: Finding a Bridge

This article aims at analysing whether rules of international humanitarian law are applicable to business and if yes, to what extent. Additionally, the consequences for International Humanitarian Law (IHL) violations by companies are analysed. We highlight that enterprises, their personnel and property which are not directly linked to a conflict enjoy the protection under Geneva Conventions from deliberate or indiscriminate attacks, as well as from pillaging and violations of private property. However, keeping neutrality in armed conflicts is a difficult task for companies and there are different ways in which they can contribute to human rights violations and abuses as well as commit international crimes. In order to prevent such violations, companies should conduct hHRDD and comply with IHL rules. Non-compliance with them may lead to reputational and organisational risks for companies as well as bring companies to criminal and/or civil responsibility.

Analysis of Topological Properties and Robustness of Urban Public Transport Networks

With the acceleration of urbanization, public transport networks are an important part of urban transport systems, and their robustness is critical for city operation. The objective of this study is to analyze the topological properties and robustness of an urban public transport network (UPTN) with a view to enhancing the sustainability of urbanization. In order to present the topological structure of the UPTN, the L-Space complex network modeling method is used to construct a model. Topological characteristics of the network are calculated. Based on single evaluation indices of station significance, a comprehensive evaluation index is proposed as the basis for selecting critical stations. The UPTN cascading failure model is established. Using the proportion of the maximum connected subgraph as the evaluation index, the robustness of the UPTN is analyzed using different station significance indices and deliberate attack strategies. The public transport network of Xuzhou city is selected for instance analysis. The results show that the UPTN in Xuzhou city has small-world effects and scale-free characteristics. Although the network has poor connectivity, it is a convenient means to travel for residents with many independent communities. The network’s dynamic robustness is demonstrably inferior to its static robustness due to the prevalence of cascading failure phenomena. Specifically, the failure of important stations has a wider impact on the network performance. Improving their load capacity and distributing the routes via them will help bolster the network resistance against contingencies. This study provides a scientific basis and strategic recommendations for urban planners and public transport managers to achieve a more sustainable public transport system.

An Empirical Study on the Effect of Training Data Perturbations on Neural Network Robustness.

The vulnerability of modern neural networks to random noise and deliberate attacks has raised concerns about their robustness, particularly as they are increasingly utilized in safety- and security-critical applications. Although recent research efforts were made to enhance robustness through retraining with adversarial examples or employing data augmentation techniques, a comprehensive investigation into the effects of training data perturbations on model robustness remains lacking. This paper presents the first extensive empirical study investigating the influence of data perturbations during model retraining. The experimental analysis focuses on both random and adversarial robustness, following established practices in the field of robustness analysis. Various types of perturbations in different aspects of the dataset are explored, including input, label, and sampling distribution. Single-factor and multi-factor experiments are conducted to assess individual perturbations and their combinations. The findings provide insights into constructing high-quality training datasets for optimizing robustness and recommend the appropriate degree of training set perturbations that balance robustness and correctness, and contribute to understanding model robustness in deep learning and offer practical guidance for enhancing model performance through perturbed retraining, promoting the development of more reliable and trustworthy deep learning systems for safety-critical applications.

An exact method for trilevel hub location problem with interdiction

In this paper, we study the problem of designing a hub network that is robust against deliberate attacks (interdictions). The problem is modeled as a three-level, two-player Stackelberg game, in which the network designer (defender) acts first to locate hubs to route a set of flows through the network. The attacker (interdictor) acts next to interdict a subset of the located hubs in the designer’s network, followed again by the defender who routes the flows through the remaining hubs in the network. We model the defender’s problem as a trilevel optimization problem, wherein the attacker’s response is modeled as a bilevel hub interdiction problem. We study such a trilevel problem on three variants of hub location problems studied in the literature namely: p-hub median problem, p-hub center, and p-hub maximal covering problems. We present a cutting plane based exact method to solve the problem. The cutting plane method uses supervalid inequalities, which is obtained from the solution of the lower level interdiction problem. To solve the lower level hub interdiction problem efficiently, we propose a penalty-based reformulation of the problem. Using the reformulation, we present a branch-and-cut based exact approach to solve the problem efficiently. We conduct experiments to show the computational advantages of the above algorithm. To the best of our knowledge, the cutting plane approach proposed in this paper is among the first exact method to solve trilevel location–interdiction problems. Our computational results show interesting implications of incorporating interdiction risks in the hub location problem.

Airline safety: Still getting better?

We consider worldwide aviation safety on scheduled passenger flights over the years 2018–22, distinguishing the 34 weeks during the Covid-19 pandemic from the prior 26 weeks. Although the pandemic caused convulsions in airline operations, it caused no deviation from the trend under which global passenger death risk from accidents and deliberate acts dropped by about 7% per year. The nations of the world continued to differ substantially in passenger mortality risk, though nations in the previous “intermediate risk” category performed slightly better than those in the earlier “lowest risk” group. The difference, however, fell far short of statistical significance. Consistent with the previous pattern, passenger death risk in the “higher risk” nations was more than an order of magnitude higher than that in other nations. The transmission of Covid-19 aboard commercial flights may have taken thousands of lives worldwide over 3/20-12/22, which would have considerably exceeded passenger deaths over that period caused by accidents and deliberate attacks. However, this increase could be considered a transient effect if the pandemic is essentially over as of the mid-2020's.

Travel Characteristics and Vulnerability Analysis of Road Resource Utilization Based on Taxi GPS Data

Residents’ travel and logistics are greatly affected by urban transportation networks, which are one of the most important supports for urban socio-economic activities. Urban transportation systems tend to cripple when faced with challenges such as natural hazards and social unrest. This paper proposes a framework for a vulnerability analysis of urban road networks (URNs) based on real traffic flows with GPS data. An improved K-shell critical node identification method is proposed based on structural and traffic characteristics. Then, a cascade failure model is proposed to analyze the structural and functional vulnerability of the URN by combining the load capacity model and the vulnerability model. This paper takes the Harbin main city URN as an example and first analyzes the passenger travel distribution and the relationship between travel orders, population and POI. Four deliberate attack methods are proposed to analyze the vulnerability of the URN under deliberate attack on commute days and rest days. The experimental results show that URNs exhibit intense vulnerability, with the fastest cascading failure occurring based on improved K-shell node failure. Furthermore, URNs are more vulnerable on rest days compared to commuter days. These findings could be used to inform a vulnerability-based spatiotemporal design of UBNs and provide theoretical support for managing traffic congestion on different days.

Nuclear anxiety as an instrument of war: The use of news media to shape and respond to the disinformation campaign surrounding the Zaporizhzhia nuclear power plant

The Russian invasion of Ukraine has galvanized anxiety over a possible nuclear catastrophe, with threats ranging from deliberate attacks and shelling of nuclear power plants to the potential use of nuclear weapons. Russia’s occupation of the Zaporizhzhia Nuclear Power Plant (ZNPP), Europe’s largest such facility, raises fundamental questions about using NPPs in crisis and risk communication, and disinformation campaigns. Building upon interdisciplinary research bridging Communication and International Relations Studies, this article employs content analysis to examine how Ukrainian and Russian media outlets engaged in a rhetorical battle of frame perceptions about the threat of nuclear catastrophe related to ZNPP. They explore how Russia’s propagandists used news media to stir nuclear anxiety as part of a broader disinformation campaign, and investigate strategies employed by Ukrainian media agencies to manage the risk of nuclear anxiety and respond to Russian disinformation. The article contributes to conversations in the field of crisis and risk communication related to how political stakeholders use news media to influence audiences’ perceptions, and specifically how political actors use nuclear anxiety politicization and disinformation to gain political influence. The findings provide insights into developing effective news media strategies responding to threats of large-scale nuclear, biological, or chemical catastrophes and cyber-attacks on nuclear infrastructure.

Enhancing the Evaluation of District Heating System Resilience: A Literature Review

Ensuring an uninterrupted supply of energy, electricity, and heat is becoming an increasingly pressing necessity. Energy provides both social and economic growth therefore, the energy systems should be resilient to different external conditions. Resilience is the ability of a system to recover from adversity [1] and in connection with the critical infrastructure - the ability to prepare for and adapt to changing conditions and withstand and recover rapidly from disruptions. Resilience includes the ability to withstand and recover from deliberate attacks, accidents, or naturally occurring threats or incidents. Several factors influence the resilience of the energy supply system: energy security, reliability, robustness, flexibility, and resilience. If energy resilience has not been well considered or even ignored in the planning, design, and operation stages in district energy communities can lead to system fragility and vulnerability. Therefore, the research assesses the different methods for resilience assessment in energy systems by focusing on district heating. During climate change mitigation and adaptation energy supply system resilience is unclear. Based on current studies, the energy resilience factor for most is considered in the context of the electricity transmission system, and the heat transmission resilience study is limited. During the research of the literature, it has been concluded that there is no consistent quantitative and quality approach to resilience because there is no consistent treatment of the concept of resilience. The available literature sources about energy resilience are limited in their scope and usability and hence are not amenable for use outside the scope where they have been developed. The metric and formula used for calculating resilience, if any, and the input data required for such calculations are also dependent on the research scope. There is a need for a fundamental generic quantitative and quality approach for resilience that would be usable and useful across various scopes or sectors in a consistent manner, which can be used for the development of resilient systems and effective resilience strategies for district heating systems.

Identification of risk key factors and prevention strategies for collision accidents between merchant and fishing vessels in China waters based on complex network

In recent years, Collision Accidents between Merchant and Fishing Vessels (CAMF) in China waters have been increasing, resulting in severe casualties and property losses. To effectively prevent such frequent collision accidents and ensure the safety of waterways and navigation routes, this study aims to identify the key risk factors associated with CAMF. Firstly, the Human Factors Analysis and Classification System (HFACS) model is employed as a comprehensive framework to extract the risk factors contributing to CAMF. By introducing edge length as the weight of network edges, a directed weighted network of CAMF is constructed. Secondly, the overall topological characteristics of the network are analyzed, and the network's robustness is studied based on the degree centrality, weighted closeness centrality, and weighted betweenness centrality of the risk factors in the network, and the key factors contributing to the accidents are identified. The research findings indicate that the network exhibits evident scale-free characteristics and small-world network properties. Deliberate attacks on approximately top 15% of the risk factors lead to a 55% degradation in the global efficiency of the accident network. Ultimately, accident prevention and control strategies and recommendations are proposed from the perspectives of both merchant and fishing vessels.

Cascade failure modeling and resilience analysis of mine cyber physical systems under deliberate attacks

Guided by the intelligent construction of coal mines and integrating the concept of the Cyber-Physical System (CPS), a novel approach to a coal mine information-physical fusion system is proposed. This concept emerges from the advancement of intelligent mines and the growing need for enhanced safety in coal mine operations. From a system safety perspective, this approach aims to effectively evaluate security issues by better integrating the informational and physical layers of intelligent mines. Currently, research in areas such as power grids and water networks has widely adopted concepts of cascade failures and robustness. It is suggested that the CPS framework be adapted to the mining sector. Considering the critical role of coal mines in China's energy security and their vulnerability to cyber attacks, a mine-specific CPS system is designed. This system incorporates a model of mine information-physical fusion, including networks for mine operations, management, and control, tailored to the unique conditions of mine shafts and underground settings. Utilizing Markov process theory, the paper delves into the theoretical study of the cascade failure process under deliberate attack strategies. This analysis is essential to effectively assess the safety issues within the information-physical system, providing vital support for fault prediction and safety analysis. The model of cascading failures in the mine information-physical system is developed, and based on an analysis of resilience and robustness, the study identifies key factors influencing the security of mine information-physical systems. Critical factors affecting the reliability of these systems include the number of system nodes, node coupling, edge count, and the interconnection methods of the dual-layer dependency network. The paper concludes by discussing the challenges in analyzing the security of information-physical systems and suggesting directions for future research.

Impact of the Russia–Ukraine Conflict on Global Marine Network Based on Massive Vessel Trajectories

Maritime transportation plays a vital role in global trade, and studying the resilience of the global maritime network is crucial for ensuring its sustainable development. Currently, the ongoing conflict between Russia and Ukraine has garnered significant global attention. However, there is a lack of specific research on the impact of the conflict on maritime shipping, particularly the resilience of the global maritime network. This paper proposes a resilience assessment framework under the influence of significant events by combining complex network metrics and network performance indicators from the resilience triangle model. It quantitatively evaluates the resilience changes in the global maritime network before and after the outbreak of the Russia–Ukraine conflict. The experiment utilizes real automatic identification system (AIS) maritime trajectory data to quantify and visualize the changes in global maritime traffic during a 20-day period before and after the conflict, constructing the global maritime network for resilience calculations. The research findings indicate the following changes occurred after the Russia–Ukraine conflict. Firstly, the global maritime industry experienced overall growth, with increased ship transportation between ports. Transportation in certain regions was negatively affected, with a significant decrease in ship activities in the Black Sea and Adriatic Sea areas. The positions of Russia and Ukraine in the world maritime industry noticeably declined. Secondly, the network connectivity, network size, and network density of the global maritime network significantly increased, indicating an enhanced network resilience. According to our quantitative results, from a topological perspective, we observed the following changes: network connectivity increased by 27.2%, network scale increased by 36.6%, network density increased by 32.4%, and network resilience increased by 18.6%. Thirdly, the global maritime network is characterized by a high degree of heterogeneity, and the impact of conflicts on the heterogeneity of the shipping network is not significant. Finally, the network exhibited a slower performance decline under random attacks, while deliberate attacks led to a sharp decline. Due to the adaptive nature of the maritime network, the resilience of the network improves in terms of its topology following the outbreak of conflicts. After conflict incidents, the rate of performance decline during simulated attacks is lower compared to the pre-conflict period.