Journal of Network and Computer Applications最新文献_第3页

CASLO: Joint scaling and deployment for microservices leveraging context-aware SLO assignment CASLO：利用上下文感知的SLO分配来联合扩展和部署微服务

IF 8 2区计算机科学 Q1 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE

Journal of Network and Computer Applications

Pub Date : 2026-03-01 Epub Date: 2025-12-19 DOI: 10.1016/j.jnca.2025.104417

Shuang Zeng, Haitao Zhang, Zezhong Yan

Service Level Objective (SLO) assignment involves distributing an application’s end-to-end latency SLO among its microservices, guiding each microservice’s resource allocation based on its assigned sub-SLO. However, existing SLO assignment methods primarily focus on horizontal scaling, overlooking the significant impact of varying resource usage contexts across nodes and container configurations on microservice latency characteristics. Moreover, these methods fail to consider how scaling decisions affect node resource usage. This oversight creates discrepancies between decision-time and runtime latency characteristics, which can lead to SLO violations or resource wastage. This paper proposes CASLO, a joint scaling and deployment method based on context-aware SLO assignment that aims to meet application SLOs with minimal resource usage. It characterizes microservice latency by categorizing influencing factors into node and container contexts, which enables the model to capture dynamic performance under varying conditions. Building on this characterization, CASLO employs Particle Swarm Optimization (PSO) to iteratively estimate each microservice’s tolerance to contextual resource conditions. For each tolerance, it determines the resource usage of each node post-scaling and deployment, addressing discrepancies of latency characteristics between decision-time and runtime and distinguishing latency characteristics across nodes. Based on the determined resource context, CASLO assigns SLOs to each microservice, dynamically configuring container resources to derive scaling and deployment decisions. Resource usage is then calculated to provide feedback to PSO for iterative optimization. Compared to state-of-the-art methods, CASLO achieves 32% reduction in resource usage and decreases the frequency of SLO violations by 61%.

服务水平目标（SLO）分配涉及在微服务之间分配应用程序的端到端延迟SLO，并根据分配的子SLO指导每个微服务的资源分配。然而，现有的SLO分配方法主要关注水平扩展，忽略了跨节点和容器配置的不同资源使用上下文对微服务延迟特征的重大影响。此外，这些方法没有考虑缩放决策对节点资源使用的影响。这种疏忽造成了决策时间和运行时延迟特征之间的差异，这可能导致违反SLO或资源浪费。本文提出了一种基于上下文感知SLO分配的联合扩展和部署方法CASLO，旨在以最小的资源使用满足应用程序的SLO。它通过将影响因素分类为节点和容器上下文来表征微服务延迟，从而使模型能够捕获不同条件下的动态性能。在此特征的基础上，CASLO使用粒子群优化（PSO）来迭代估计每个微服务对上下文资源条件的容忍度。对于每个容差，它确定每个节点在扩展和部署后的资源使用情况，解决决策时间和运行时之间延迟特征的差异，并区分节点之间的延迟特征。基于确定的资源上下文，CASLO将slo分配给每个微服务，动态配置容器资源以得出扩展和部署决策。然后计算资源使用情况，向粒子群算法提供反馈，进行迭代优化。与最先进的方法相比，CASLO减少了32%的资源使用，并将违反SLO的频率降低了61%。

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引用次数: 0

DACS: Distributed adjustable computation scheme in highly scalable data center networks based on multi-protection routing DACS：基于多保护路由的高可扩展数据中心网络分布式可调计算方案

IF 8 2区计算机科学 Q1 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE

Journal of Network and Computer Applications

Pub Date : 2026-03-01 Epub Date: 2025-12-24 DOI: 10.1016/j.jnca.2025.104425

Wanling Lin , Jou-Ming Chang , Xiao-Yan Li

In data center networks (DCNs), many value-added services involving multiple tenants and distributed sites can be naturally modeled as multi-party communication (MPC) processes, where participants exchange information across infrastructures to support collaborative computation. For MPC, it usually ensures that the private data of the multiple parties involved in the collaborative computation are safe, the computational results maintain acceptable accuracy, and all participants are in the same fair position in a distributed environment. This article considers an unexplored application based on MPC called the distributed adjustable computation scheme (DACS), which allows computation to be invoked when the collected data reaches a specified threshold in the communication. We developed a distributed algorithm using secure multi-protection routing to enable DACS. The proposed algorithm guarantees that each private data can be successfully delivered to the desired recipient even if any faulty component (including server or link) exists in the network. Also, no other than the destination can receive the complete private data. We implement DACS on highly scalable data center networks. Through simulation, experimental results show that DACS is highly reliable and achieves high security efficiency.

在数据中心网络（dcn）中，许多涉及多个租户和分布式站点的增值服务可以自然地建模为多方通信（MPC）过程，其中参与者跨基础设施交换信息以支持协作计算。对于MPC来说，通常要保证参与协同计算的多方的私有数据是安全的，计算结果保持可接受的准确性，并且在分布式环境中所有参与者都处于同样公平的地位。本文考虑一种未开发的基于MPC的应用程序，称为分布式可调计算方案（DACS），它允许在收集的数据达到通信中的指定阈值时调用计算。我们开发了一种使用安全多保护路由的分布式算法来实现DACS。该算法保证了即使网络中存在任何故障组件（包括服务器或链路），每个私有数据也能成功地传递到期望的接收方。此外，只有目的地才能接收到完整的私有数据。我们在高度可扩展的数据中心网络上实现DACS。仿真实验结果表明，DACS具有较高的可靠性和安全效率。

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引用次数: 0

The DPC-LSTM-MD scheme for detecting selective forwarding attack under variable environment in event-driven wireless sensor networks 事件驱动无线传感器网络中可变环境下选择性转发攻击检测的DPC-LSTM-MD方案

IF 8 2区计算机科学 Q1 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE

Journal of Network and Computer Applications

Pub Date : 2026-03-01 Epub Date: 2025-12-29 DOI: 10.1016/j.jnca.2025.104411

Yilun Ma, Yuanming Wu

In an event-driven wireless sensor network (EWSN), events occur randomly, prompting sensor nodes within the event area to detect and transmit data packets to a sink via router nodes (RNs) through multi-hop communication. Some RNs, referred to as malicious nodes, may launch selective forwarding attacks by selectively dropping part or all of the received packets. Additionally, harsh environmental conditions can degrade channel quality, sometimes forcing RNs to abandon forwarding data packets. Under these conditions, it becomes challenging to distinguish malicious nodes from normal nodes solely based on their packet forwarding rates. To address this issue, we propose the DPC-LSTM-MD scheme to detect selective forwarding attacks. This approach utilizes the time series of nodes’ packet forwarding behaviors as a dataset. The Density Peaks Clustering (DPC) method is employed to extract features representative of normal node behavior. Subsequently, a Long Short-Term Memory (LSTM) network predicts the single round forwarding rate (SFR) of nodes in the next time series interval. Based on the prediction error, we apply the minimum density (MD) method combined with the 3-sigma rule to identify and isolate malicious nodes. Our results demonstrate that the DPC-LSTM-MD scheme achieves a low false detection rate (FDR) of 2% and a low missed detection rate (MDR) of 3%, significantly improving network throughput.

在事件驱动的无线传感器网络（EWSN）中，事件是随机发生的，事件区域内的传感器节点通过多跳通信的方式检测数据包，并通过路由器节点（RNs）将数据包发送到sink。有些rn被称为恶意节点，可能会选择性地丢弃部分或全部接收到的报文，从而发起选择性转发攻击。此外，恶劣的环境条件会降低信道质量，有时会迫使RNs放弃转发数据包。在这种情况下，仅根据报文转发速率来区分恶意节点和正常节点变得很有挑战性。为了解决这个问题，我们提出了DPC-LSTM-MD方案来检测选择性转发攻击。该方法利用节点数据包转发行为的时间序列作为数据集。采用密度峰聚类（DPC）方法提取正常节点行为的特征。随后，LSTM （Long - short - Memory）网络预测下一个时间序列间隔内节点的单轮转发速率（SFR）。基于预测误差，我们采用最小密度（MD）方法结合3-sigma规则来识别和隔离恶意节点。我们的研究结果表明，DPC-LSTM-MD方案实现了2%的低误检率（FDR）和3%的低漏检率（MDR），显著提高了网络吞吐量。

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引用次数: 0

Tree fringe and ridge subgraph-based critical vertex shielding for network resilience improvement 基于树条纹和脊子图的关键顶点屏蔽提高网络弹性

IF 8.7 2区计算机科学 Q1 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE

Journal of Network and Computer Applications

Pub Date : 2026-02-21 DOI: 10.1016/j.jnca.2026.104454

Weidong Li, Wentao Chen, Xuehai Zhang, Chisheng Wang, Jinlong Duan, Shewei Wang, Changwei Miao

引用次数: 0

A digital twin-based reputation assessment model for JointCloud computing 基于数字孪生的联合云计算信誉评估模型

IF 8 2区计算机科学 Q1 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE

Journal of Network and Computer Applications

Pub Date : 2026-02-01 Epub Date: 2025-11-24 DOI: 10.1016/j.jnca.2025.104395

Yadi Wu , Lina Wang , Rongwei Yu , Xiuwen Huang , Jiatong Liu

JointCloud Computing (JCC) supports a collaborative model of multiple cloud service providers to provide users with robust performance and adequate services. Reputation is an important aspect for the stable development of the JCC system, affecting the cooperation among service providers and users’ choice of services. Most of the existing reputation assessment solutions only consider a single factor of user feedback or service quality, and cannot provide an accurate reputation assessment for the complex system of JCC. In addition, JointCloud services are provided by multiple service providers in cooperation, and existing solutions do not consider this service characteristic, making it difficult to accurately measure the reputation of the service. In order to provide a comprehensive reputation assessment for JCC, we proposed a reputation assessment model based on digital twins. A reputation calculation module is embedded in the digital twin, and a hybrid subjective–objective-based reputation assessment method and a split-integration-based reputation assessment method are designed for different JointCloud subjects to achieve a comprehensive and accurate reputation assessment. We conducted a series of experiments to evaluate the performance of the proposed reputation evaluation model and present the experimental results. The proposed method achieves a reputation assessment bias of 0.0112, which reduces the average bias by 0.2184 compared to existing researches. In real-world scenarios, the proposed model incurs a communication overhead of 93.7735 ms, with a digital twin data acquisition frequency of 36.4273 ms. The evaluation results show that our reputation evaluation model is feasible in terms of performance and accuracy.

联合云计算（JCC）支持多个云服务提供商的协作模型，为用户提供强大的性能和充分的服务。信誉是JCC系统稳定发展的重要方面，影响着服务提供商之间的合作和用户对服务的选择。现有的声誉评估方案大多只考虑用户反馈或服务质量这一单一因素，无法为JCC复杂的系统提供准确的声誉评估。此外，JointCloud的服务是由多个服务提供商合作提供的，现有的解决方案没有考虑到这一服务特性，因此很难准确衡量服务的声誉。为了给JCC提供一个全面的声誉评估，我们提出了一个基于数字孪生的声誉评估模型。在数字孪生中嵌入声誉计算模块，针对不同的JointCloud主体设计基于主客观混合的声誉评估方法和基于分裂集成的声誉评估方法，实现全面、准确的声誉评估。我们进行了一系列实验来评估所提出的声誉评估模型的性能，并给出了实验结果。该方法的声誉评估偏差为0.0112，比现有研究的平均偏差降低了0.2184。在实际场景中，该模型的通信开销为93.7735 ms，数字孪生数据采集频率为36.4273 ms。评价结果表明，所建立的信誉评价模型在性能和准确性上是可行的。

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引用次数: 0

A robust eclipse attack detection framework for Ethereum networks 一个健壮的eclipse攻击检测框架用于以太坊网络

IF 8 2区计算机科学 Q1 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE

Journal of Network and Computer Applications

Pub Date : 2026-02-01 Epub Date: 2025-12-19 DOI: 10.1016/j.jnca.2025.104416

Zubaida Rehman , Iqbal Gondal , Hai Dong , Mengmeng Ge , Mark A. Gregory , Ikram ul Haq

Eclipse attacks, which isolate victim nodes by monopolizing their peer connections, remain a critical threat to Ethereum’s consensus mechanism. To address this, we present a principled framework for detecting Eclipse attacks in Ethereum peer-to-peer networks, grounded in a formal adversarial model. Existing defenses are either ad-hoc or lack provable guarantees, leaving open questions about their reliability under adaptive adversaries. Our work aims to bridge this gap by formally defining eclipse attack detection as a security property. We specify soundness, completeness, and robustness theorems under bounded adversarial drift, and derive formal guarantees within false positive and false negative bounds, resilience to adversarial manipulation, and multi-node compositional reliability. We then instantiate a lightweight detection framework that maps packet-level traffic features to predictions using ensemble classifiers (Random Forest, XGBoost). The system was validated using a controlled Ethereum testbed and extended with CTGAN-generated synthetic traces to emulate networks of up to 100 nodes. Empirical evaluation shows that our framework achieves up to 96% F1-score with sub-second inference latency, well within Ethereum’s 12-second Proof-of-Stake validator time slots. These findings demonstrate that lightweight statistical features, when coupled with formal analysis, enable accurate, efficient, and scalable detection of network-level partitioning attacks. Our work establishes a deployable and theoretically grounded defense foundation for securing modern blockchain systems against eclipse adversaries.

Eclipse攻击通过垄断受害节点的对等连接来隔离受害节点，这仍然是对以太坊共识机制的严重威胁。为了解决这个问题，我们提出了一个原则性框架，用于检测以太坊点对点网络中的Eclipse攻击，该框架以正式的对抗模型为基础。现有的防御要么是临时的，要么缺乏可证明的保证，这使得它们在自适应对手下的可靠性问题悬而未决。我们的工作旨在通过将eclipse攻击检测正式定义为一种安全属性来弥合这一差距。我们指定了有界对抗漂移下的稳健性、完备性和鲁棒性定理，并推导了假正和假负边界内的形式保证、对抗操作的弹性和多节点组成可靠性。然后，我们实例化了一个轻量级检测框架，该框架使用集成分类器（Random Forest, XGBoost）将数据包级流量特征映射到预测。该系统使用受控的以太坊测试平台进行了验证，并使用ctgan生成的合成轨迹进行了扩展，以模拟多达100个节点的网络。经验评估表明，我们的框架在亚秒级推理延迟下达到了96%的f1得分，完全在以太坊12秒的权益证明验证器时间段内。这些发现表明，轻量级统计特性与形式化分析相结合，能够准确、高效和可扩展地检测网络级分区攻击。我们的工作为保护现代区块链系统免受eclipse对手的攻击建立了一个可部署的和理论上的防御基础。

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引用次数: 0

BlackoutADR: Exploiting adaptive data rate vulnerabilities in LoRaWAN-based FANETs BlackoutADR：利用基于lorawan的fanet中的自适应数据速率漏洞

IF 8 2区计算机科学 Q1 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE

Journal of Network and Computer Applications

Pub Date : 2026-02-01 Epub Date: 2025-12-08 DOI: 10.1016/j.jnca.2025.104409

Khaoula Hidawi , Sabrine Ennaji , Elena Ferrari

This paper introduces BlackoutADR, a novel adversarial attack exploiting LoRaWAN’s Adaptive Data Rate (ADR) mechanism in cellular-connected UAV networks, with applicability to other IoT systems as well. By subtly manipulating Received Signal Strength Indicator (RSSI) and Signal-to-Noise Ratio (SNR), BlackoutADR increases UAV transmission power, causing 45% faster battery depletion within 100 s of simulation time and disrupting network operations. Using NS-3 simulations with a 20-UAV FANET, we evaluate its evasion of multiple ML-based IDSs (CNN, LSTM, BiLSTM, FNN, LoRaWAN-specific). Results show BlackoutADR remains undetected due to its subtle manipulations evading even dynamic thresholds, outperforming traditional jamming attacks. To address the identified vulnerability, we outline reactive measures, including dynamic threshold-based IDSs, secure ADR mechanisms, and recommendations for drone manufacturers.

本文介绍了BlackoutADR，这是一种利用LoRaWAN自适应数据速率（ADR）机制在蜂窝连接无人机网络中的新型对抗性攻击，也适用于其他物联网系统。通过巧妙地操纵接收信号强度指标（RSSI）和信噪比（SNR）， BlackoutADR增加了无人机的发射功率，在模拟时间的100秒内导致45%的电池耗尽并中断网络运行。利用NS-3模拟20架无人机FANET，我们评估了它对多个基于ml的ids （CNN， LSTM, BiLSTM， FNN， lorawan特定）的规避。结果表明，BlackoutADR仍然未被发现，因为它的微妙操纵甚至逃避了动态阈值，优于传统的干扰攻击。为了解决已识别的漏洞，我们概述了反应性措施，包括基于动态阈值的ids，安全ADR机制以及对无人机制造商的建议。

引用次数: 0

Network-assisted relay selection in mmWave D2D communication under presence of dynamic obstacles with unknown orientation 存在未知方向动态障碍物的毫米波D2D通信中网络辅助中继选择

IF 8 2区计算机科学 Q1 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE

Journal of Network and Computer Applications

Pub Date : 2026-02-01 Epub Date: 2025-12-15 DOI: 10.1016/j.jnca.2025.104394

Durgesh Singh , Sasthi C. Ghosh

Millimeter wave (mmWave) D2D communication is highly vulnerable to blockages from dynamic obstacles leading to severe packet loss and deterioration in quality of service. User equipments (UEs) acting as relays are chosen to divert the communication path in case of blockage. However, relays themselves are vulnerable to be blocked due to their and obstacles’ motion. Thus mobility parameters of dynamic obstacles must be captured effectively, but it is challenging as they might not be connected to the network. Additionally, instantaneous change in their orientation in motion is difficult to measure which might vary abruptly compared to their speed which can be sensed with high accuracy. A probabilistic model is developed considering the obstacle’s orientation in motion is unknown. Later the geometrical structure of the problem is analyzed and then exploited to devise a novel technique to derive closed form blockage expression for a given pair of UE. The proposed technique can be applied across exhaustive scenarios of motion of a given UE pair which may get blocked due to dynamic obstacles. Through extensive simulations, we have observed that our proposed approach outperforms both classical received signal strength (RSS) based approach and two recent state of the art approaches. We have also validated our results against an oracle which has complete speed and orientation information regarding UEs and obstacles.

毫米波（mmWave） D2D通信极易受到动态障碍物阻塞的影响，导致严重的丢包和服务质量下降。选择用户设备作为继电器，在通信受阻时改道。然而，由于继电器和障碍物的运动，继电器本身很容易被阻塞。因此，必须有效地捕获动态障碍物的移动参数，但由于它们可能没有连接到网络中，因此具有挑战性。此外，它们在运动中方向的瞬时变化很难测量，与它们的速度相比，它们可能会突然变化，而速度可以高精度地感知。建立了考虑障碍物运动方向未知的概率模型。然后对问题的几何结构进行了分析，并在此基础上提出了一种求解给定UE对封闭形式阻塞表达式的新方法。所提出的技术可以应用于可能由于动态障碍物而受阻的给定UE对运动的穷举场景。通过大量的模拟，我们观察到我们提出的方法优于经典的基于接收信号强度（RSS）的方法和两种最新的技术方法。我们还针对一个oracle验证了我们的结果，该oracle具有关于ue和障碍物的完整速度和方向信息。

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引用次数: 0

PE-Chain: An efficient hierarchical sharding architecture for dynamically participating node models PE-Chain：用于动态参与节点模型的高效分层分片架构

IF 8 2区计算机科学 Q1 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE

Journal of Network and Computer Applications

Pub Date : 2026-02-01 Epub Date: 2025-12-19 DOI: 10.1016/j.jnca.2025.104415

Junfeng Tian , Yujian Wu , Jin Tian , Liuling Qi

Sharding is a widely adopted technique for enhancing blockchain scalability by partitioning the network into multiple sub-shards, thereby distributing the workload. However, traditional dynamic sharding schemes often suffer from delayed adjustments to the shard count, hindering rapid convergence to an optimal workload distribution in practical deployments and limiting overall scalability. Furthermore, the dynamic participation of nodes is frequently overlooked. To address these challenges, this paper proposes PolyembryonyChain (PE-Chain), a novel and efficient hierarchical sharding architecture designed for environments with dynamically participating nodes, with the goal of achieving elastic scalability. Its core innovations are twofold. First, it introduces a dynamic threshold sharding algorithm that adaptively adjusts the number of shards and optimizes the network topology to enable elastic expansion. Second, it incorporates a validator assignment and reconfiguration scheme, specifically tailored for dynamic hierarchical environments, to ensure system security. A comprehensive security analysis and simulation results demonstrate that PE-Chain significantly outperforms state-of-the-art baselines, achieving approximately 28% higher throughput while maintaining low latency, which underscores its superior scalability and practical value.

分片是一种广泛采用的技术，通过将网络划分为多个子分片来增强区块链的可伸缩性，从而分配工作负载。然而，传统的动态分片方案往往会延迟调整分片数，从而阻碍了在实际部署中快速收敛到最佳工作负载分布，并限制了整体可扩展性。此外，节点的动态参与常常被忽略。为了解决这些挑战，本文提出了PolyembryonyChain (PE-Chain)，这是一种新颖高效的分层分片架构，专为具有动态参与节点的环境而设计，目标是实现弹性可扩展性。它的核心创新是双重的。首先，引入动态阈值分片算法，自适应调整分片数量，优化网络拓扑结构，实现弹性扩展。其次，它结合了验证器分配和重新配置方案，专门为动态分层环境量身定制，以确保系统安全性。综合安全分析和仿真结果表明，PE-Chain显着优于最先进的基线，在保持低延迟的同时实现了约28%的高吞吐量，这凸显了其优越的可扩展性和实用价值。

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引用次数: 0

ARProof: A cross-protocol approach to detect and mitigate ARP-spoofing attacks in smart home networks ARProof：一种在智能家庭网络中检测和减轻arp欺骗攻击的跨协议方法

IF 8 2区计算机科学 Q1 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE

Journal of Network and Computer Applications

Pub Date : 2026-02-01 Epub Date: 2025-11-24 DOI: 10.1016/j.jnca.2025.104396

Md Mizanur Rahman , Faycal Bouhafs , Sayed Amir Hoseini , Frank den Hartog

Smart homes are increasingly vulnerable to cyberattacks that lead to network instability, causing homeowners to lodge complaints with their Broadband Service Providers (BSPs). Therefore, effective and timely detection of cyberattacks is crucial for both customers and BSPs. Address Resolution Protocol (ARP) spoofing is one of the most common attacks that can facilitate larger and more severe follow-up attacks. Unfortunately, there are currently no methods that can effectively detect and mitigate ARP spoofing in smart homes from a BSP’s perspective. Current Machine Learning (ML)-based methods often rely on a single dataset from a controlled lab environment designed to mimic a single home, assuming that the results will generalize to all smart homes. Our findings indicate that this assumption is flawed. They are also unsuitable for smart homes from a BSP’s perspective, as they require custom applications, introduce additional overhead, and often rely on the injection of probing traffic into the network. To address these issues, we developed an algorithm that can detect ARP spoofing in smart home networks, regardless of the network structure or connected devices. It uses a cross-protocol strategy by correlating ARP packets with Dynamic Host Configuration Protocol (DHCP) messages to validate address bindings. We evaluated our method using four public datasets and two real-world testbeds, achieving 100% detection accuracy in all scenarios. In addition, the algorithm requires only little computational overhead, confirming its suitability for use by BSPs to detect and mitigate ARP spoofing attacks in smart homes.

智能家居越来越容易受到网络攻击，导致网络不稳定，导致房主向他们的宽带服务提供商（bsp）投诉。因此，有效、及时地检测网络攻击对客户和bsp都至关重要。ARP （Address Resolution Protocol）欺骗是一种最常见的攻击方式，它可以引发更大规模、更严重的后续攻击。不幸的是，从BSP的角度来看，目前还没有方法可以有效地检测和减轻智能家居中的ARP欺骗。当前基于机器学习（ML）的方法通常依赖于来自受控实验室环境的单个数据集，该环境旨在模拟单个家庭，并假设结果将推广到所有智能家庭。我们的发现表明，这种假设是有缺陷的。从BSP的角度来看，它们也不适合智能家居，因为它们需要定制应用程序，引入额外的开销，并且通常依赖于向网络注入探测流量。为了解决这些问题，我们开发了一种算法，可以检测智能家庭网络中的ARP欺骗，无论网络结构或连接的设备如何。它使用跨协议策略，通过将ARP报文与DHCP （Dynamic Host Configuration Protocol）消息关联来验证地址绑定。我们使用四个公共数据集和两个真实世界的测试平台来评估我们的方法，在所有场景下都实现了100%的检测准确率。此外，该算法只需要很少的计算开销，证实了bsp使用它来检测和减轻智能家居中的ARP欺骗攻击的适用性。

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引用次数: 0