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On Cyber-Physical Fault Resilience in Data Communication: A Case From A LoRaWAN Network Systems Design 论数据通信中的网络物理故障恢复能力:LoRaWAN 网络系统设计案例
IF 2.3 Q3 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Pub Date : 2024-01-04 DOI: 10.1145/3639571
Chao Wang, Cheng-Hsun Chuang, Yu-Wei Chen, Yun-Fan Chen
Systems offering fault-resilient, energy-efficient, soft real-time data communication have wide applications in Industrial Internet-of-Things (IIoT). While there have been extensive studies for fault resilience in real-time embedded systems, investigations from cyber-physical systems (CPS) perspective are still much needed, as CPS faults occur not just from abnormal conditions in the software/hardware of the system, but also from the physical environment in which the system operates. At the same time, in addition to conventional fault tolerance strategies embedded in the software/hardware of the target system, CPS faults could be mitigated via some strategic systems re-configuration made available by the physical environment. This paper presents a design and implementation for CPS fault-resilient data communication, in the context of IIoT networks running LoRaWAN, a low-power wide-area networking standard. The proposed design combines collaborative IIoT end devices plus a network gateway piggybacked on a third-party cruising object that is part of the environment. With the focus on data communication, the study illustrates challenges and opportunities to address CPS fault resilience while meeting the needs for energy efficiency and communication timeliness that are common to IIoT systems. The implementation of the design is based on ChirpStack, a widely used open source framework for LoRaWAN. The results from experiment and simulation both show that the proposed scheme can tolerate limited errors of data communication while saving operating energy and maintaining timeliness of data communication to some extent.
在工业物联网(IIoT)中,提供故障弹性、高能效、软实时数据通信的系统有着广泛的应用。虽然对实时嵌入式系统的故障恢复能力进行了大量研究,但从网络物理系统(CPS)的角度进行研究仍然十分必要,因为网络物理系统的故障不仅来自系统软件/硬件的异常情况,还来自系统运行的物理环境。同时,除了目标系统软件/硬件中嵌入的传统容错策略外,还可以通过物理环境提供的一些战略性系统重新配置来缓解 CPS 故障。本文以运行低功耗广域网络标准 LoRaWAN 的物联网网络为背景,介绍了 CPS 容错数据通信的设计与实现。所提出的设计将协作式 IIoT 终端设备与网络网关结合在一起,网关搭载在作为环境一部分的第三方巡航物体上。该研究以数据通信为重点,说明了在满足 IIoT 系统对能效和通信及时性的共同需求的同时,解决 CPS 故障恢复能力问题所面临的挑战和机遇。设计的实现基于 ChirpStack,这是一个广泛使用的 LoRaWAN 开源框架。实验和仿真结果均表明,所提出的方案可以容忍有限的数据通信错误,同时在一定程度上节约了运行能耗,并保持了数据通信的及时性。
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引用次数: 0
DistressNet-NG: A Resilient Data Storage and Sharing Framework for Mobile Edge Computing in Cyber-Physical Systems DistressNet-NG:网络物理系统中移动边缘计算的弹性数据存储和共享框架
IF 2.3 Q3 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Pub Date : 2024-01-03 DOI: 10.1145/3639057
M.F.H. Sagor, Amran Haroon, R. Stoleru, S. Bhunia, A. Altaweel, M. Chao, Liuyi Jin, M. Maurice, R. Blalock
Mobile Edge Computing (MEC) has been gaining a major interest for use in Cyber-Physical Systems (CPS) for Disaster Response and Tactical applications. These CPS generate a very large amount of mission-critical and personal data that require resilient and secure storage and sharing. In this article, we present the design, implementation, and evaluation of a framework for resilient data storage and sharing for MEC in CPS targeting the aforementioned applications. Our framework is built on the resiliency of three main components: EdgeKeeper, which ensures resilient coordination of the framework’s components; RSock, which provides resilient communication among CPS’s nodes; and R-Drive/R-Share which, leveraging EdgeKeeper and RSock, provides resilient data storage and sharing. EdgeKeeper employs a set of replicas and a consensus protocol for storing critical meta-data and ensuring fast reorganization of the CPS; RSock decides an optimal degree for replicating data that is communicated over lossy links. R-Drive employs an adaptive erasure-coded and encrypted resilient data storage; R-Share, leveraging RSock provides resilient peer-to-peer data sharing. We implemented our proposed framework on rapidly deployable systems (e.g. manpacks, testMobile Edge Clouds) and on Android devices, and integrated it with existing MEC applications. Performance evaluation results from three real-world deployments show that our framework provides resilient data storage and sharing in MEC for CPS.
移动边缘计算(MEC)在用于灾难响应和战术应用的网络物理系统(CPS)中的应用越来越受到关注。这些 CPS 会产生大量关键任务数据和个人数据,需要弹性、安全的存储和共享。在本文中,我们介绍了针对上述应用的 CPS 中 MEC 弹性数据存储和共享框架的设计、实施和评估。我们的框架建立在三个主要组件的弹性之上:EdgeKeeper确保框架各组件的弹性协调;RSock提供CPS节点间的弹性通信;R-Drive/R-Share利用EdgeKeeper和RSock提供弹性数据存储和共享。EdgeKeeper 采用一组副本和共识协议来存储关键元数据,并确保 CPS 的快速重组;RSock 决定通过有损链路通信的数据的最佳复制度。R-Drive 采用自适应擦除编码和加密弹性数据存储;R-Share 利用 RSock 提供弹性点对点数据共享。我们在快速部署系统(如 manpacks、testMobile Edge Clouds)和安卓设备上实施了我们提出的框架,并将其与现有的 MEC 应用程序集成。三个实际部署的性能评估结果表明,我们的框架为 CPS 的 MEC 提供了弹性数据存储和共享。
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引用次数: 0
A Blockchain Architecture to Increase the Resilience of Industrial Control Systems from the Effects of a Ransomware Attack: A Proposal and Initial Results 提高工业控制系统抵御勒索软件攻击的能力的区块链架构:建议和初步结果
IF 2.3 Q3 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Pub Date : 2023-12-21 DOI: 10.1145/3637553
Stephen Kirkman, Steven Fulton, Jeffrey Hemmes, Christopher Garcia, Justin C. Wilson
The motivation of this research (and also one of the nation’s cyber goals) is enhancing the resilience of Industrial Control Systems (ICS)/Supervisory Control and Data Acquisition (SCADA) systems against ransomware attacks. ICS and SCADA systems run some of the most important networks in the country: our critical infrastructure (i.e. water flow, power grids, etc.). Disruption of these systems causes confusion, panic, and in some cases loss of life. We propose a SCADA architecture that uses blockchain to help protect ICS data from ransomware. We focus on the historian. In a SCADA system, the historian collects events from devices in the control network for real-time and future analysis. We choose to use Ethereum and its Proof of Stake (PoS) consensus protocol. The other goal of this research focuses on the resilience of blockchain. There is very little research in protecting the blockchain itself. By performing encryption testing on an Ethereum private network, we explore how vulnerable blockchain is and discuss potential ways to make a blockchain client more resilient.
这项研究的动机(也是国家的网络目标之一)是提高工业控制系统(ICS)/监控与数据采集(SCADA)系统抵御勒索软件攻击的能力。ICS 和 SCADA 系统运行着美国一些最重要的网络:我们的关键基础设施(如水流、电网等)。这些系统的中断会造成混乱、恐慌,有时还会导致生命损失。我们提出了一种 SCADA 架构,使用区块链来帮助保护 ICS 数据免受勒索软件的侵害。我们将重点放在历史记录程序上。在 SCADA 系统中,历史记录程序从控制网络中的设备收集事件,用于实时和未来分析。我们选择使用以太坊及其权益证明(PoS)共识协议。这项研究的另一个目标是区块链的弹性。保护区块链本身的研究很少。通过在以太坊私有网络上进行加密测试,我们探索了区块链的脆弱性,并讨论了使区块链客户端更具弹性的潜在方法。
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引用次数: 0
A Combinatorial Optimization Analysis Method for Detecting Malicious Industrial Internet Attack Behaviors 检测工业互联网恶意攻击行为的组合优化分析方法
IF 2.3 Q3 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Pub Date : 2023-12-15 DOI: 10.1145/3637554
Kejing Zhao, Zhiyong Zhang, K. Choo, Zhongya Zhang, Tiantian Zhang
Industrial Internet plays an important role in key critical infrastructure sectors and is the target of different security threats and risks. There are limitations in many existing attack detection approaches, such as function redundancy, overfitting and low efficiency. A combinatorial optimization method Lagrange multiplier is designed to optimize the underlying feature screening algorithm. The optimized feature combination is fused with random forest and XG-Boost selected features to improve the accuracy and efficiency of attack feature analysis. Using both the UNSW-NB15 and Natural gas pipeline datasets, we evaluate the performance of the proposed method. It is observed that the influence degrees of the different features associated with the attack behavior can result in the binary classification attack detection increases to 0.93, and the attack detection time reduces by 6.96 times. The overall accuracy of multi-classification attack detection is also observed to improve by 0.11. We also observe that nine key features of attack behavior analysis are essential to the analysis and detection of general attacks targeting the system, and by focusing on these features one could potentially improve the effectiveness and efficiency of real-time critical industrial system security. In this paper, CICDDoS2019 dataset and CICIDS2018 dataset are used to prove the generalization. The experimental results show that the proposed method has good generalization and can be extended to the same type of industrial anomaly data sets.
工业互联网在关键基础设施领域发挥着重要作用,是各种安全威胁和风险的目标。现有的许多攻击检测方法存在功能冗余、过度拟合和效率低等局限性。设计了一种组合优化方法拉格朗日乘法器来优化底层特征筛选算法。优化后的特征组合与随机森林和 XG-Boost 筛选特征相融合,提高了攻击特征分析的准确性和效率。我们使用 UNSW-NB15 和天然气管道数据集评估了所提方法的性能。结果表明,与攻击行为相关的不同特征的影响度可使二元分类攻击检测的准确度提高到 0.93,攻击检测时间缩短了 6.96 倍。多分类攻击检测的总体准确率也提高了 0.11。我们还观察到,攻击行为分析的九个关键特征对于分析和检测针对系统的一般攻击至关重要,通过关注这些特征,有可能提高实时关键工业系统安全的有效性和效率。本文使用 CICDDoS2019 数据集和 CICIDS2018 数据集来证明该泛化方法。实验结果表明,所提出的方法具有良好的泛化能力,可以扩展到同类型的工业异常数据集。
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引用次数: 0
Statistical Verification using Surrogate Models and Conformal Inference and a Comparison with Risk-aware Verification 使用替代模型和共形推理的统计验证以及与风险意识验证的比较
IF 2.3 Q3 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Pub Date : 2023-12-05 DOI: 10.1145/3635160
Xin Qin, Yuan Xia, Aditya Zutshi, Chuchu Fan, Jyotirmoy V. Deshmukh
Uncertainty in safety-critical cyber-physical systems can be modeled using a finite number of parameters or parameterized input signals. Given a system specification in Signal Temporal Logic (STL), we would like to verify that for all (infinite) values of the model parameters/input signals, the system satisfies its specification. Unfortunately, this problem is undecidable in general. Statistical model checking (SMC) offers a solution by providing guarantees on the correctness of CPS models by statistically reasoning on model simulations. We propose a new approach for statistical verification of CPS models for user-provided distribution on the model parameters. Our technique uses model simulations to learn surrogate models, and uses conformal inference to provide probabilistic guarantees on the satisfaction of a given STL property. Additionally, we can provide prediction intervals containing the quantitative satisfaction values of the given STL property for any user-specified confidence level. We compare this prediction interval with the interval we get using risk estimation procedures. We also propose a refinement procedure based on Gaussian Process (GP)-based surrogate models for obtaining fine-grained probabilistic guarantees over sub-regions in the parameter space. This in turn enables the CPS designer to choose assured validity domains in the parameter space for safety-critical applications. Finally, we demonstrate the efficacy of our technique on several CPS models.
安全关键型网络物理系统中的不确定性可以使用有限数量的参数或参数化输入信号进行建模。给定信号时序逻辑(STL)中的系统规范,我们希望验证对于模型参数/输入信号的所有(无限)值,系统满足其规范。不幸的是,这个问题通常是无法确定的。统计模型检验(SMC)通过对模型模拟进行统计推理来保证CPS模型的正确性,从而提供了一种解决方案。我们提出了一种新的方法来统计验证用户提供的模型参数分布的CPS模型。我们的技术使用模型模拟来学习代理模型,并使用共形推理来提供满足给定STL属性的概率保证。此外,对于任何用户指定的置信水平,我们可以提供包含给定STL属性的定量满意值的预测区间。我们将这个预测区间与使用风险估计程序得到的区间进行比较。我们还提出了一种基于高斯过程(GP)的代理模型的改进过程,用于在参数空间的子区域上获得细粒度的概率保证。这反过来又使CPS设计人员能够在参数空间中为安全关键型应用程序选择可靠的有效性域。最后,我们在几个CPS模型上展示了我们的技术的有效性。
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引用次数: 1
Mixed-Trust Computing: Safe and Secure Real-Time Systems 混合信任计算:安全可靠的实时系统
IF 2.3 Q3 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Pub Date : 2023-12-02 DOI: 10.1145/3635162
Dionisio de Niz, Bjorn Andersson, Mark H. Klein, J. Lehoczky, Amit Vasudevan, Hyoseung Kim, Gabriel Moreno
Verifying complex Cyber-Physical Systems (CPS) is increasingly important given the push to deploy safety-critical autonomous features. Unfortunately, traditional verification methods do not scale to the complexity of these systems and do not provide systematic methods to protect verified properties when not all the components can be verified. To address these challenges, this article proposes a real-time mixed-trust computing framework that combines verification and protection. The framework introduces a new task model, where an application task can have both an untrusted and a trusted part. The untrusted part allows complex computations supported by a full OS with a real-time scheduler running in a VM hosted by a trusted hypervisor. The trusted part is executed by another scheduler within the hypervisor and is thus protected from the untrusted part. If the untrusted part fails to finish by a specific time, the trusted part is activated to preserve safety (e.g., prevent a crash) including its timing guarantees. This framework is the first allowing the use of untrusted components for CPS critical functions while preserving logical and timing guarantees, even in the presence of malicious attackers. We present the framework its schedulability analysis and the coordination protocol between the trusted and untrusted parts. Our implementation on a Raspberry Pi 3 is also discussed along with experiments showing the behavior of the system under failures of untrusted components, and a drone application to demonstrate its practicality.
考虑到部署安全关键自主功能的推动,验证复杂的网络物理系统(CPS)变得越来越重要。不幸的是,传统的验证方法不能扩展到这些系统的复杂性,并且在并非所有组件都可以验证时,不能提供系统的方法来保护已验证的属性。为了应对这些挑战,本文提出了一种结合验证和保护的实时混合信任计算框架。该框架引入了一个新的任务模型,其中应用程序任务可以同时具有不受信任的部分和受信任的部分。不受信任的部分允许由完整的操作系统支持的复杂计算,并在由受信任的管理程序托管的VM中运行实时调度器。受信任的部分由管理程序中的另一个调度器执行,因此不受不受信任部分的影响。如果不可信部分未能在特定时间内完成,则激活可信部分以保持安全性(例如,防止崩溃),包括其时间保证。该框架是第一个允许将不受信任的组件用于CPS关键功能,同时保留逻辑和定时保证的框架,即使在存在恶意攻击者的情况下也是如此。给出了该框架的可调度性分析和可信部分与不可信部分之间的协调协议。我们在树莓派3上的实现也与实验一起讨论,显示了系统在不可信组件故障下的行为,以及无人机应用程序来展示其实用性。
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引用次数: 0
A Deep Time Delay Filter for Cooperative Adaptive Cruise Control 一种用于协同自适应巡航控制的深度延迟滤波器
Q3 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Pub Date : 2023-11-08 DOI: 10.1145/3631613
Kuei-Fang Hsueh, Ayleen Farnood, Isam Al-Darabsah, Mohammad Al Saaideh, Mohammad Al Janaideh, Deepa Kundur
Cooperative adaptive cruise control (CACC) is a smart transportation solution to alleviate traffic congestion and enhance road safety. The performance of CACC systems can be remarkably affected by communication time delays, and traditional control methods often compromise control performance by adjusting control gains to maintain system stability. In this paper, we present a study on the stability of a CACC system in the presence of time delays and highlight the trade-off between control performance and tuning controller gains to address increasing delays. We propose a novel approach incorporating a neural network module called the deep time delay filter (DTDF) to overcome this limitation. The DTDF leverages the assumption that time delays primarily originate from the communication layer of the CACC network, which can be subject to adversarial delays of varying magnitudes. By considering time-delayed versions of the car states and predicting the present (un-delayed) states, the DTDF compensates for the effects of communication delays. The proposed approach combines classical control techniques with machine learning, offering a hybrid control system that excels in explainability and robustness to unknown parameters. We conduct comprehensive experiments using various deep-learning architectures to train and evaluate the DTDF models. Our experiments utilize a robot platform consisting of MATLAB, Simulink, the Optitrack motion capture system, and the Qbot2e robots. Through these experiments, we demonstrate that when appropriately trained, our system can effectively mitigate the adverse effects of constant time delays and outperforms a traditional CACC baseline in control performance. This experimental comparison, to the best of the author’s knowledge, is the first of its kind in the context of a hybrid machine learning CACC system. We thoroughly explore initial conditions and range policy parameters to evaluate our system under various experimental scenarios. By providing detailed insights and experimental results, we aim to contribute to the advancement of CACC research and highlight the potential of hybrid machine learning approaches in improving the performance and reliability of CACC systems.
协同自适应巡航控制(CACC)是一种缓解交通拥堵、提高道路安全的智能交通解决方案。通信时延对CACC系统的性能影响很大,传统的控制方法往往通过调整控制增益来维持系统的稳定性,从而降低控制性能。在本文中,我们研究了存在时间延迟的CACC系统的稳定性,并强调了控制性能和调谐控制器增益之间的权衡,以解决不断增加的延迟。我们提出了一种新的方法,结合称为深度延迟滤波器(DTDF)的神经网络模块来克服这一限制。DTDF利用了这样一个假设,即时间延迟主要来自CACC网络的通信层,这可能会受到不同程度的对抗性延迟的影响。通过考虑汽车状态的时滞版本并预测当前(未延迟)状态,DTDF补偿了通信延迟的影响。该方法将经典控制技术与机器学习相结合,提供了一种混合控制系统,该系统在可解释性和对未知参数的鲁棒性方面表现出色。我们使用各种深度学习架构进行了全面的实验来训练和评估DTDF模型。我们的实验利用由MATLAB、Simulink、Optitrack运动捕捉系统和Qbot2e机器人组成的机器人平台。通过这些实验,我们证明,经过适当的训练,我们的系统可以有效地减轻恒定时间延迟的不利影响,并且在控制性能方面优于传统的CACC基线。据作者所知,这种实验比较是混合机器学习CACC系统背景下的第一次。我们深入探索了初始条件和范围策略参数,以在各种实验场景下评估我们的系统。通过提供详细的见解和实验结果,我们的目标是促进CACC研究的进步,并强调混合机器学习方法在提高CACC系统性能和可靠性方面的潜力。
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引用次数: 0
Graph-Based Deadlock Analysis and Prevention for Robust Intelligent Intersection Management 基于图的智能交叉口鲁棒管理死锁分析与预防
Q3 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Pub Date : 2023-11-08 DOI: 10.1145/3632179
Kai-En Lin, Kuan-Chun Wang, Yu-Heng Chen, Li-Heng Lin, Ying-Hua Lee, Chung-Wei Lin, Iris Hui-Ru Jiang
Intersection management systems, with the assistance of vehicular networks and autonomous vehicles, have potential to perform traffic control more precisely than contemporary signalized intersections. However, as infrastructural intersection management controllers do not directly activate motions of vehicles, it is possible that the vehicles fail to follow the instructions from controllers, undermining system properties such as deadlock-freeness and traffic performance. In this paper, we consider a class of robustness issues, the time violations, which stem from possible discrepancies between scheduled orders and real executions. We refine a graph-based intersection model to build our theoretical foundations and analyze potential deadlocks and their resolvability. We develop solutions that mitigate negative effects of time violations. Particularly, we propose a Robustness-Aware Greedy Scheduling (RGS) algorithm for robust scheduling and evaluate the deadlock-free robustness of different intersection models and scheduling algorithms. Experimental results show that the RGS algorithm is able to significantly improve robustness and keep a good balance with traffic performance.
在车辆网络和自动驾驶汽车的辅助下,交叉口管理系统有可能比现代信号交叉口更精确地执行交通控制。然而,由于基础设施交叉口管理控制器不直接激活车辆的运动,车辆有可能无法遵循控制器的指令,从而破坏系统属性,如无死锁和交通性能。在本文中,我们考虑了一类鲁棒性问题,即时间违反,它源于计划顺序与实际执行之间可能存在的差异。我们改进了一个基于图的交集模型来建立我们的理论基础,并分析了潜在的死锁及其可解性。我们开发解决方案,以减轻违反时间的负面影响。特别地,我们提出了一种鲁棒感知贪婪调度(RGS)算法用于鲁棒调度,并评估了不同交叉口模型和调度算法的无死锁鲁棒性。实验结果表明,RGS算法能够显著提高鲁棒性,并与流量性能保持良好的平衡。
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引用次数: 0
System Resilience through Health Monitoring and Reconfiguration 通过运行状况监视和重新配置实现系统弹性
Q3 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Pub Date : 2023-11-03 DOI: 10.1145/3631612
Ion Matei, Wiktor Piotrowski, Alexandre Perez, Johan de Kleer, Jorge Tierno, Wendy Mungovan, Vance Turnewitsch
We demonstrate an end-to-end framework to improve the resilience of man-made systems to unforeseen events. The framework is based on a physics-based digital twin model and three modules tasked with real-time fault diagnosis, prognostics and reconfiguration. The fault diagnosis module uses model-based diagnosis algorithms to detect and isolate faults and generates interventions in the system to disambiguate uncertain diagnosis solutions. We scale up the fault diagnosis algorithm to the required real-time performance through the use of parallelization and surrogate models of the physics-based digital twin. The prognostics module tracks fault progression and trains the online degradation models to compute remaining useful life of system components. In addition, we use the degradation models to assess the impact of the fault progression on the operational requirements. The reconfiguration module uses PDDL-based planning endowed with semantic attachments to adjust the system controls to minimize the fault impact on the system operation. We define a resilience metric and use a fuel system example to demonstrate how the metric improves with our framework.
我们展示了一个端到端框架,以提高人工系统对不可预见事件的弹性。该框架基于基于物理的数字孪生模型和三个模块,负责实时故障诊断、预测和重新配置。故障诊断模块使用基于模型的诊断算法检测和隔离故障,并在系统中产生干预措施,消除不确定诊断方案的歧义。通过使用基于物理的数字孪生的并行化和代理模型,我们将故障诊断算法扩展到所需的实时性能。预测模块跟踪故障进展并训练在线退化模型来计算系统组件的剩余使用寿命。此外,我们使用退化模型来评估故障进展对操作需求的影响。重构模块采用基于pddl的规划,赋予语义附件,对系统控制进行调整,使故障对系统运行的影响最小化。我们定义了一个弹性度量,并使用一个燃料系统示例来演示该度量是如何随着我们的框架而改进的。
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引用次数: 0
Techniques for Enhancing Security in Industrial Control Systems 提高工业控制系统安全性的技术
Q3 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Pub Date : 2023-10-30 DOI: 10.1145/3630103
Vijay Varadharajan, Uday Tupakula, Kallol Krishna Karmakar
Increasingly Industrial Control Systems (ICS) systems are being connected to the Internet to minimise the operational costs and provide additional flexibility. These control systems such as the ones used in power grids, manufacturing and utilities operate continually and have long lifespans measured in decades rather than years as in the case of IT systems. Such industrial control systems require uninterrupted and safe operation. However, they can be vulnerable to a variety of attacks, as successful attacks on critical control infrastructures could have devastating consequences to the safety of human lives as well as a nation’s security and prosperity. Furthermore, there can be a range of attacks that can target ICS and it is not easy to secure these systems against all known attacks let alone unknown ones. In this paper, we propose a software enabled security architecture using Software Defined Networking (SDN) and Network Function Virtualisation (NFV) that can enhance the capability to secure industrial control systems. We have designed such an SDN/NFV enabled security architecture and developed a Control System Security Application (CSSA) in SDN Controller for enhancing security in ICS by achieving real time situational awareness and dynamic policy-driven decision making across the network infrastructure. In particular, CSSA can be used for establishing secure path for end-to-end communication between devices and also deal against certain specific attacks namely denial of service attacks, from unpatched vulnerable control system components and securing the communication flows from the legacy devices that do not support any security functionality. We also discuss how CSSA provides reliable paths for safety critical messages in control systems. We discuss the prototype implementation of the proposed architecture and the results obtained from our analysis.
越来越多的工业控制系统(ICS)系统连接到互联网,以最大限度地降低运营成本并提供额外的灵活性。这些控制系统,如电网、制造业和公用事业中使用的控制系统,持续运行,寿命长,以几十年为单位,而不是像IT系统那样以年为单位。这种工业控制系统需要不间断和安全运行。然而,它们可能容易受到各种攻击,因为对关键控制基础设施的成功攻击可能对人类生命安全和国家安全与繁荣造成毁灭性后果。此外,可能会有一系列针对ICS的攻击,要保护这些系统免受所有已知攻击并不容易,更不用说未知攻击了。在本文中,我们提出了一种使用软件定义网络(SDN)和网络功能虚拟化(NFV)的软件支持的安全架构,可以增强保护工业控制系统的能力。我们设计了这样一个支持SDN/NFV的安全架构,并在SDN控制器中开发了一个控制系统安全应用程序(CSSA),通过实现跨网络基础设施的实时态势感知和动态策略驱动决策来增强ICS的安全性。CSSA可用于为设备之间建立端到端通信的安全路径,并可应对某些特定的攻击,即来自未修补的易受攻击的控制系统组件的拒绝服务攻击,以及保护来自不支持任何安全功能的旧设备的通信流。我们还讨论了CSSA如何为控制系统中的安全关键消息提供可靠的路径。我们讨论了所提出的体系结构的原型实现以及从分析中获得的结果。
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引用次数: 0
期刊
ACM Transactions on Cyber-Physical Systems
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