Resilient Scheme Research Articles

Resilient Time-Varying Formation Tracking Control for General Linear Multiagent Systems With a Nonautonomous Leader and Adversarial Followers.

This article is concerned with resilient formation tracking problems for general linear multiagent systems, where the leader's control input is unavailable to all the followers and partial followers' behaviors are malicious due to the node attacks. Despite the presence of the nonautonomous leader and the adversarial followers, the remaining benign followers are still expected to track the leader's trajectory with the prescribed time-varying formation. To this end, a resilient scheme comprising an attack detection and isolation strategy and a formation tracking protocol is proposed. The detection strategy enables every benign follower to identify its adversarial neighbors with two-hop communication information, as long as the underlying topology meets given conditions. Then, the detected adversarial agents are directly removed to avoid the spread of their influence, which induces a new problem called node loss. To accommodate possible node loss events, the designed tracking protocol is independent of certain global knowledge, and its convergence is demonstrated by means of the impulsive Lyapunov functions. Finally, the proposed resilient scheme is verified by two simulation examples.

Attack-resilient framework for wind power forecasting against civil and adversarial attacks

Forecasting wind power generation accurately is crucial for reliable, economical, and efficient integrations in smart grids, promoting applications of cleaner energy sources. Although effective wind power forecasting methods exist, power grids still require resilient schemes enabling accurate predictions under cyber-attacks. This paper introduces civil attack (CA) and fast gradient sign method (FGSM) attacks to wind power forecasting to analyze their impacts with countermeasures. The impacts of CA and FGSM attacks on a deep learning-based forecasting method are evaluated, finding FGSM attacks more severe. Also, an attack identification and corrupted data replacement-based pre-processing robust framework is proposed, outperforming other countermeasures. To detect and classify attacks, random forest (RF) has outperformed extreme gradient boosting (XGBoost), decision tree (DT), support vector machine (SVM), and k-nearest neighbors (KNN). Experimental results on two different zones during CA and FGSM attacks indicate that the decrease in accuracy can be up to 0.4103, 0.3152, and 0.1683 in terms of root mean square error (RMSE), mean absolute error (MAE), and mean squared error (MSE), respectively. The proposed framework successfully achieves an accuracy of 0.1204, 0.0835, and 0.0145 for the worst case in terms of RMSE, MAE, and MSE, respectively, signifying its importance for academic and industrial applications.

Effectiveness of climate resilient water safety plans in Nepal

ABSTRACT Water supply schemes (WSSs) in Nepal are managed by water user committees with basic knowledge of climate change. The Government of Nepal has committed and prioritized improving the quality of water services by implementing climate-resilient water safety plans (CR-WSPs) in 10 WSSs. In this study, how tough water sanitation and hygiene (HTIW) framework was adopted to assess the effectiveness of these CR-WSPs, which include four groundwater and six protected springs-based WSSs. Employing the HTIW framework, this study adopted the six key indicators environment, infrastructure, management, community governance and engagement, institutional support, and supply chains to evaluate CR-WSPs effectiveness. The indicators were then assessed using a Likert scale. Resilient schemes are needed to demonstrate a capacity to respond effectively to challenges such as unforeseen extreme events and potential hazards, together with an aptitude for financial management, laboratory maintenance, and social inclusion. Less resilient schemes tend to be those linked to social inclusion or financial issues. Institutional support and supply chain domain scored four and were relatively strong among them. The findings of this study suggest that CR-WSPs can be an important metric tool to assess climate resilience and guide policymakers in low- and middle-income countries.

Static-dynamic characteristics and management scheme of county space resilience based on geographical natures—An empirical study of 95 counties from Jiangsu Province, China

Resilient counties has the capability to navigate adverse environmental changes, adaptively reallocate resources during challenges, and bolster county competitiveness. This study introduces an original framework for nurturing resilient counties based on geographical natures, emphasizing the role of geographic space evolution, termed county space resilience (CSR). This study focuses on 95 counties in Jiangsu, a prominent province in the rapidly urbanizing region of eastern China, as a case study. Employing a multi-dimensional feature model and LISA spatiotemporal transition analysis, this study analyzes the static-dynamic characteristics of CSR and proposes a regional guidance scheme. This study draws three key conclusions. Firstly, it reveals that the average CSR value decreased from 0.327 in 2000 to 0.320 in 2005, then increased to 0.380 in 2021, and the geographic trend of transitioning from more economically developed zones to less developed ones. Secondly, the general structural characteristics of CSR were classified into four groups: upgrade transformation, focus optimization, potential enhancement, and safety adjustment. Furthermore, the spatial–temporal coalescence of the Moran’s I scatterplot equals 0.684, signifying stability in the spatial correlation of CSR. Additionally, the dynamic evolution characteristics of CSR were categorized into positive and negative types, with the Yangtze River Green Development Belt acting as the boundary. Lastly, this study constructs a management scheme comprising zoning control and classification strategy tailored for different counties, offering strategic recommendations customized for each. This scheme can serve as a decision-making foundation for policymakers in county development endeavors, fostering the cultivation of resilient counties.

Agriculture climate change resilience in sub-Saharan Africa: the Badolo scientific framework AgricultureResilience.

Abstract The climate is, in sub-Saharan Africa, one of the main obstacles to the development of agriculture, which is essentially rain-fed. Extreme climatic events have significant impacts on agricultural production, reducing its contribution to economic and social development. Climate change, which will increase the frequency and intensity of extreme climatic events, poses multiple threats to agriculture in sub-Saharan Africa that include loss of development gains, alteration of development prospects and regression dynamics. A response to these threats is an innovation in agricultural resilience policies to accelerate the achievement of agricultural resilience configurations to climate change. In this article, we propose the Badolo AgricultureResilience scientific framework for improving the relevance, efficiency and impact of resilience policies in the agricultural sector to climate change. This framework implements the approach, tools and resilience schemes of the ClimResilience theoretical framework to establish innovative trajectories of resilience to climate change in sub-Saharan Africa for the agricultural sector. It suggests an approach to resilience governed by climate change resilience configurations. It includes families of impacts, vulnerability and resilience solutions that determine the relevance, efficiency and performance of the proposed scientific framework. It integrates an agricultural resilience function to climate change to establish agricultural resilience trajectories, taking into account resilience needs, resilience capacities and contextual specificities. For the agricultural sector in sub-Saharan Africa, the Badolo AgricultureResilience scientific framework is a decision support tool for innovating resilience policies, accelerates the achievement of agricultural resilience configurations and preserve the contributions of agriculture to social and economic development.

A Scalable Formal Framework for the Verification and Vulnerability Analysis of Redundancy-Based Error-Resilient Null Convention Logic Asynchronous Circuits

The increasing demand for high-speed, energy-efficient, and miniaturized electronics has led to significant challenges and compromises in the domain of conventional clock-based digital designs, most notably reduced circuit reliability, particularly in mission-critical hardware. At scaled technology nodes, devices are vulnerable to transient or soft errors, such as Single Event Upset (SEU) and Single Event Latch-up (SEL). External radiation, internal electromagnetic interference (EMI), or noise are the primary sources of these errors, which can compromise the circuit functionality. In response to these challenges, the Quasi-Delay-Insensitive (QDI) Null Convention Logic (NCL) asynchronous design paradigm has emerged as a promising alternative, offering advantages such as ultra-low power performance, reduced noise and EMI, and resilience to process, voltage, and temperature variations. Moreover, its unique architecture and insensitivity to timing variations offers a degree of resistance against transient errors; however, it is not entirely resilient. Several resiliency schemes are available to detect and mitigate soft errors in QDI circuits, with approaches based on redundancy proving to be the most effective in ensuring complete resilience across all major QDI implementation paradigms, including NCL, Pre-charge/Weak-charge Half Buffers (PCHB/WCHB), and Sleep Convention Logic (SCL). This research focuses on one such redundancy-based resiliency scheme for QDI NCL circuits, known as the dual-modular redundancy-based NCL (DMR-NCL) architecture, and addresses the absence of formal methods for the verification and analysis of such circuits. A novel methodology has been proposed for formally verifying the correctness of DMR-NCL circuits synthesized from their synchronous counterparts, covering both safety (functional correctness) and liveness (the absence of deadlock). In addition, this research introduces a formal framework for the vulnerability analysis of DMR-NCL circuits against SEU/SEL. To demonstrate the framework’s efficacy and scalability, a prototype computer-aided support tool has been developed, which verifies and analyzes multiple DMR-NCL benchmark circuits of varying sizes and complexities.

Output Synchronization of Heterogeneous Multiagent Systems With Resilience to Link and Actuator Attacks: A Fully Distributed Event-Triggered Mechanism

In this paper, we propose a distributed resilient control method to solve an output synchronization problem for linear heterogeneous multi-agent systems (MASs) in the presence of both link and actuator attacks. A fully distributed event-trigger-based observer is proposed to estimate the state of the leader, where global information is not required and the leader's system matrices are identified in finite time. An intermittent event-triggered mechanism is also designed to avoid continuous monitor triggered conditions. For actuator attacks, a compensator, based on a distributed normal state predictor, is developed to recover paralyzed states. Theoretical analysis shows that an MAS steered by our proposed fully distributed adaptive resilient scheme achieves output synchronization, and Zeno-behaviors are excluded. Finally, a numerical example is provided to verify the effectiveness of our proposed scheme.

Cyber resilience in industrial networks: A state of the art, challenges, and future directions

Industrial networks, and more particularly, industrial control systems (ICSs) and industrial Internet of things (IIoT), are no longer isolated environments. The rapid increase of functional needs in Industry 4.0 has indeed exposed them to numerous cyberattacks. Cyberattacks against ICSs or IIoT can cause considerable societal and economic disruption. Cyber resilient and cybersecurity practices are essential to integrate secure networks, control systems, physical processes, and their interconnections toward handling cyberattacks. In this paper, we survey relevant cyber resilience strategies for industrial networks, focusing on ICSs and IIoT. First, we provide a coverage of resilient networks and the fundamental components of ICSs and IIoT. Second, state of the art articles that propose cyber resilience assessment frameworks are reviewed. They are classified according to the resilience aspects they address and the defense mechanism, anomaly detection, failure management and survivability strategy, as well as resilience measure they present. As a result, the main technical and human related challenges, practical limitations, and current cyber resilience needs of industrial networks are identified. Finally, we establish the principal requirements that cyber resilience schemes for industrial networks should meet shortly and suggest promising directions for future research.

Online evaluation of the distribution system resiliency criteria using Choquet‐based graph technique

AbstractNowadays, due to network expansions, system operators are dealing with natural events including system failures. Evaluating the system readiness to maintain the network interconnections during severe faults are known as an important challenge of today's distribution networks. To do this, this paper presents an online non‐model‐based scheme of evaluating the system resiliency and supplying critical loads within severe natural conditions. In this case, by developing system resiliency as multi‐metric decision making problem and proposing the Choquet integral and graph theoretic methodology, the system resiliency is evaluated. The proposed resiliency scheme is an online non‐model‐based approach can be used for all distribution system configurations with the potential of natural event failures. In this case, by proposing online resiliency criteria based on the system critical loads and branches and developing the proposed criteria on Choquet integral scheme in the form of optimization procedure, the system resiliency is evaluated. The validity of the proposed approach is carried out on two different systems including the IEEE 123‐bus test system and the Consortium for Electric Reliability Technology Solutions (CERTS) microgrid. Simulation results present effectiveness of the proposed scheme to provide proper protective switching strategy and design the system resiliency criteria for future distribution systems.

Microgrids Resiliency Enhancement against Natural Catastrophes Based Multiple Cooperation of Water and Energy Hubs

With the ever-growing frequency of natural catastrophe occurrences such as hurricanes, floods, earthquakes, etc., the idea of resilient microgrids (MGs) has attracted more attention than before. Providing the opportunity for a multi-carrier energy supply after a natural catastrophe can lessen power losses and improve power resiliency and reliability. Critical loads within the MG can be prioritized and restored in the shortest possible time based on the condition of the network after the damaging occurrence by considering the energy hub (EH) systems and the optimum design and allocation of these multi-carrier systems. To this end, this paper aims to address the resilience framework in MGs considering sets of water and EHs (WEHs) consisting of CHP (combined heat and power), a boiler, energy storage, and a desalination unit. This study focused on considering an effective resilient scheme to restore critical loads in a short period after a natural catastrophe when the MG experiences an unpredictable event. By applying the idea of WEHs, there would be a chance of restoring the system by using two sets of WEH systems in the appropriate islanded points to restore the system and critical loads of electricity, heat, and water. For this purpose, different scenarios were considered for assessing the resiliency of the system against a natural catastrophic event that causes serious damage to the network by analyzing the energy-not-supplied (ENS) factor. Moreover, the allocated WEHs can adequately supply the electrical, water, and thermal demand loads throughout the day after the natural catastrophe. To mitigate the unforeseen variations in the renewable sources, a battery is located in the WEH, which can attend to the optimal scheduling effectively. A scenario-based method is also introduced to improve the resiliency of MGs in an uncertain environment such as electrical, heat, and water stochastic demands. The appropriate efficiency of the offered model was considered on a modified IEEE test system.

Adaptive Resilient Tracking Control With Dual-Terminal Dynamic-Triggering for a Linear Multi-Agent System Against False Data Injection Attacks

False data injection (FDI) attacks on sensors and actuators are adverse in multi-agent systems (MASs), and they degrade system performance and even cause instability by tampering transmission signals. Resilient control for such attacks is critical in the real world. In this paper, a distributed adaptive resilient control scheme is proposed. This scheme is based on observers for reconstructing signals with projection operators and dual-terminal dynamic event-triggered mechanism. The update of the controller and intermittent communication among agents are determined by the proposed dual-terminal triggered mechanism, and two triggered functions work independently in individual follower. Compared with traditional static one, it not only achieves satisfactory consensus performance but also reduces triggered number. Also, state estimators are developed for reconstruction of combined measurements, and continuous monitoring is removed. Theoretical analysis shows that our proposed adaptive resilient scheme attenuates adverse effects of FDI attacks and the followers track the leader with Zeno-free behaviors. Finally, two illustrative examples are presented to verify the effectiveness of our adaptive resilient scheme.

Strategic Capabilities for Enhancing the Flood Resilience of Business Premises: An Expert Review and Lessons from Case Studies

Sustainable development entails socio-economic wellbeing, which is often threatened by weather hazards. Indeed, the need to minimise the adverse impact of climate change and extreme weather events cannot be overstressed. Notably, damage to the built environment by extreme weather and its consequential effects is highly significant. This emphasises the need for a climate-resilient built environment. Thus, this study derived the strategic capability areas required by business organisations to achieve the flood resilience of their built environment. The research method involved rounds of review by a carefully selected team of experts, and the review of lessons from four case studies. Twenty-six capability areas were identified from literature but were consolidated to nineteen at the end of data collection and analysis. The capability areas covered how properties are used and managed as well as the actual fabric and design of business premises/properties. The capability areas included awareness and understanding of flood risk to property, review for a flood resilience scheme, product acquisition for flood risk management, dynamic stakeholder identification and strong network, maintenance and post-flood management scheme, physical characteristics of the property and business data management. Professionals and business organisations can use the outcome of this study as a guide for business premises flood resilience enhancement planning and decision making.

A High Resilience and High Scalable Key Pre-distribution Scheme Based on Combinatorial Designs for Resource-Constrained Devices in IoT Networks

A High Resilience and High Scalable Key Pre-distribution Scheme Based on Combinatorial Designs for Resource-Constrained Devices in IoT Networks

An effective intrusion-resilient mechanism for programmable logic controllers against data tampering attacks

Programmable Logic Controllers (PLCs) play a prominent role in critical infrastructures, such as power grid, transportation, and petrochemical industry. Suffering from data tampering attacks, PLCs are fragile as the forged data could cause significant damage to industrial machines and human safety. However, less attention has been paid to develop resilience mechanisms for automatically recovering PLCs systems from anomalous states under malicious attacks. In this work, we present the first resilience approach for protecting PLCs against data tampering attacks. The key observation we leverage is that the programmable characteristic of a PLC enables a defender to ensure its data integrity by embedding security mechanism into its control logic. In particular, we design a novel data authentication mechanism to generate and authenticate the message digest of the communication data between PLCs. An anomaly alert will be triggered if the data authentication fails. The execution on received malicious commands is disabled to avoid detrimental effect and keep the system stable. Furthermore, to recover real data from malicious modifications, a data sender is required to encrypt data using the proposed RC5-based data recovery algorithm and re-transmit it. The data authentication and recovery approaches can be implemented on the programmable logic circuit of PLCs through code updating, which requires no alterations to its current hardware architecture. We present the prototype of our resilience scheme and conduct real-world experiments to validate its efficacy under 12 typical attack scenarios. Our results show that our approach achieves 97.4% of accuracy in data authentication and 98.1% of success rate in abnormal state recovery. Finally, we assess the practicality of the proposed mechanism in terms of execution delay.

Urban resilience as a mitigating factor against economically driven out-migration during COVID-19: The case of Eilat, a tourism-based city

The COVID-19 pandemic has created an ongoing global crisis. The unprecedented shock has been particularly devastating for tourism-based cities and has tested their resilience. This study addresses the mitigating role of urban resilience in the interplay between acute crises and the phenomenon of urban outmigration. Leveraging a unique dataset collected during the first national lockdown that followed the outbreak of COVID-19 in the city of Eilat (Israel)—a geographically isolated single economic sector-based city with no feasible options to commute—we offer here a new conceptual framework and an empirical framework for measuring perceived resilience. Using validated psychometric questionnaires and employing the nested hierarchical modeling approach, we estimate the impact of perceived resilience on the decision to migrate from the city. We find that even though Eilat has all the attributes to experience significant out-migration, its residents are not inclined towards migration due to its prior investment in resilience measures, which strengthened the local community and created a unique credo shared by its residents. These findings call for policymakers to focus on long-term resilience schemes directed at increasing the appeal that cities have for their residents and ensuring their endurance in times of extreme hardship.

A Secure and Resilient Scheme for Telecare Medical Information Systems With Threat Modeling and Formal Verification

A Secure and Resilient Scheme for Telecare Medical Information Systems With Threat Modeling and Formal Verification

Resilience Assessment in a Low Voltage Power Grid with Photovoltaic Generation in a University Building

High integration of photovoltaic (PV) systems into the power systems causes negative or positive impacts. Typically, research considers the PV impacts on the RMS voltage, power losses, transformers and feeder stress, and power quality indicators. However, a generalising assessment of the electrical parameters and indicators (P&I) describes the power grid performance. It considers a complete holistic view of the real impacts that many events cause over the power grid operation. Therefore, this research proposes the resilience index in order to quantify and assess the impacts that the PV systems cause in low voltage. This scheme has four stages: i) P&I measurement, ii) P&I normalisation, iii) P&I weights assignment, and iv) resilience index quantification and assessment. The resilience scheme assessment has been applied in a low voltage university building with a PV system interconnected of 11.53 kWp. Monitoring has lasted for a month, with data acquisition every ten minutes. P&I monitored have been RMS voltage, RMS current, active, and non-active power, voltage imbalance, total harmonic distortion of voltage and current, and harmonic components of voltage and current. Results indicate that the PV system has positively affected the resilience index in the point of common coupling and floor four-node because the THDv, Vh, THDi, and Ih improved.

A resilient control strategy for networked multi-agent systems subject to covert attacks

In this paper, a resilient distributed control scheme against covert attacks for multi-agent networked systems subject to input and state constraints is developed. The idea consists in a clever deployment of predictive arguments with a twofold aim: detection of malicious agent behaviors affecting the normal system operations and consequent specific control actions implementation to mitigate as much as possible undesirable knock-on effects resulting from adversary actions. Specifically, the multi-agent system is organized in terms of a grid topology and set-theoretic receding horizon control ideas are exploited to develop a distributed algorithm capable to recognize the attacked agent. In essence, the resulting solution relies on the combined use of predictive control and set-invariance ideas that are exploited to generate redundant control sequences randomly selected on the actuator side such that the malicious agent is never aware about the effective control action indeed exploited. As a consequence, countermeasures on the sensor-to-controller channel could lead to significantly erroneous data not complying with the expected evolution of the system modeling. Finally, numerical simulations are carried out to show benefits and effectiveness of the proposed approach.

Resilient communication model for satellite networks using clustering technique

Satellite networks are regarded as significant communication infrastructures to provide high-quality services. With global coverage and flexible deployment, they are able to transfer data swiftly and reliably over long distances. Smooth communication in case of attacks and damage has been paid more attention in recent years. However, little research has addressed resilient schemes for satellite networks so far. To that end, a resilient communication model applicable to satellite networks is put forward. A cluster architecture is constructed with the goal of stable management, data fusion and fault tolerance. In a cluster, there are three types of satellites, clusterhead, core member and ordinary member. The clusterhead is selected depending on the residual energy and the reliability importance of satellites. Moreover, network resilience is comprehensively evaluated in terms of reliability, availability and quality of service (QoS). On that basis, a cluster-based routing protocol with handshake is proposed for maximizing network resilience within basic constraints. Using dynamic programming and deep reinforcement learning method, the routing protocol not only reduces the computation load but also processes data efficiently. Finally, the simulation results demonstrate that the satellite network with the proposed model achieves resilient communication while maintaining high energy efficiency.

PRISM

Multicores increasingly deploy safety-critical parallel applications that demand resiliency against soft-errors to satisfy the safety standards. However, protection against these errors is challenging due to complex communication and data access protocols that aggressively share on-chip hardware resources. Research has explored various temporal and spatial redundancy-based resiliency schemes that provide multicores with high soft-error coverage. However, redundant execution incurs performance overheads due to interference effects induced by aggressive resource sharing. Moreover, these schemes require intrusive hardware modifications and fall short in providing efficient system availability guarantees. This article proposes PRISM, a resilient multicore architecture that incorporates strong hardware isolation to form redundant clusters of cores, ensuring a non-interference-based redundant execution environment. A soft error in one cluster does not effect the execution of the other cluster, resulting in high system availability. Implementing strong isolation for shared hardware resources, such as queues, caches, and networks requires logic for partitioning. However, it is less intrusive as complex hardware modifications to protocols, such as hardware cache coherence, are avoided. The PRISM approach is prototyped on a real Tilera Tile-Gx72 processor that enables primitives to implement the proposed cluster-level hardware resource isolation. The evaluation shows performance benefits from avoiding destructive hardware interference effects with redundant execution, while delivering superior system availability.