Simulation-based Analysis of RPL Routing Attacks and Their Impact on IoT Network Performance

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Abstract

The recent expansion of the Internet of Things (IoT) owes a lot to the significant contribution of the 6LoWPAN protocol, which has been extensively employed in low-power and lossy networks. To facilitate communication in 6LoWPAN networks, the Internet Engineering Task Force (IETF) has suggested the usage of the Routing Protocol for Low-Power and Lossy Networks (RPL). Despite its usefulness, the open and restricted nature of the RPL protocol renders it susceptible to both internal and external attacks. Since IoT devices connected through the RPL protocol have limited resources like processing power, battery life, memory, and bandwidth, ensuring their security is of the utmost importance. One of the primary obstacles to IoT networks is RPL routing attacks, which disrupt the network's normal routing activities and structure. This study investigates the impact of five RPL routing attacks, namely Blackhole, Sybil, Selective Forwarding (SF), Sinkhole, DIO suppression, and DIS flooding, on the IoT networks’ performance. The study evaluated the network's performance for normal and five routing attack scenarios using numerous performance metrics including Link throughput, No. of packets generated (control and data), Sensor data throughput, Packet Delivery Ratio (PDR), and Delay in packet delivery. This work conducted simulations using the Tetcos NetSim v12.1 IoT network simulator tool and is the first to analyze IoT network performance under multiple routing assault scenarios with various performance measures. The analysis showed that the performance metrics of PDR, Sensor data throughput, and No. of data packets transmitted decreased significantly in attack scenarios compared to the normal scenario, with an average decreased percentage of 70%, 70%, and 39.4%, respectively. In contrast, the metrics Link throughput, Delay, and No. of control packets transmitted increased in attack scenarios compared to the normal scenario, with average values supplemented by a factor of 35, 255, and 36, respectively. Additionally, the Destination-Oriented Directed Acyclic Graph (DODAG) real-time formation under different scenarios was provided.

基于仿真的 RPL 路由攻击及其对物联网网络性能的影响分析
摘要 近期物联网(IoT)的扩展在很大程度上归功于 6LoWPAN 协议的重大贡献,该协议已被广泛应用于低功耗和有损网络。为促进 6LoWPAN 网络中的通信,互联网工程任务组(IETF)建议使用低功耗和有损网络路由协议(RPL)。尽管 RPL 协议非常有用,但其开放性和限制性使其容易受到内部和外部攻击。由于通过 RPL 协议连接的物联网设备的处理能力、电池寿命、内存和带宽等资源有限,因此确保其安全性至关重要。物联网网络的主要障碍之一是 RPL 路由攻击,它破坏了网络的正常路由活动和结构。本研究调查了五种 RPL 路由攻击(即黑洞、Sybil、选择性转发(SF)、天坑、DIO 抑制和 DIS 泛洪)对物联网网络性能的影响。该研究使用多项性能指标评估了正常情况下和五种路由攻击情况下的网络性能,包括链路吞吐量、生成的数据包数量(控制和数据)、传感器数据吞吐量、数据包交付率(PDR)和数据包交付延迟。这项工作使用 Tetcos NetSim v12.1 物联网网络模拟器工具进行了模拟,首次使用各种性能指标分析了多种路由攻击场景下的物联网网络性能。分析结果表明,与正常场景相比,攻击场景下的PDR、传感器数据吞吐量和数据包传输数量等性能指标明显下降,平均下降比例分别为70%、70%和39.4%。相比之下,在攻击场景中,链路吞吐量、延迟和传输的控制数据包数量等指标比正常场景有所增加,平均值分别增加了 35、255 和 36 倍。此外,还提供了不同场景下以目的地为导向的有向无环图(DODAG)的实时形成情况。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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