# Signature-Based Security Analysis and Detection of IoT Threats in Advanced Message Queuing Protocol
###### Abstract  
The Advanced Message Queuing Protocol (AMQP) is a widely used communication standard in IoT systems due to its robust and reliable message delivery capabilities. However, its increasing adoption has made it a target for various cyber threats, including Distributed Denial of Service (DDoS), Man-in-the-Middle (MitM), and brute force attacks. This study presents a comprehensive analysis of AMQP-specific vulnerabilities and introduces a statistical model for the detection and classification of malicious activities in IoT networks. Leveraging a custom-designed IoT testbed, realistic attack scenarios were simulated, and a dataset encompassing normal, malicious, and mixed traffic was generated. Unique attack signatures were identified and validated through repeated experiments, forming the foundation of a signature-based detection mechanism tailored for AMQP networks. The proposed model demonstrated high accuracy in detecting and classifying attack-specific traffic while maintaining a low false positive rate for benign traffic. Notable results include effective detection of RST packets in DDoS scenarios, precise classification of MitM attack patterns, and identification of brute force attempts on AMQP systems. This research highlights the efficacy of signature-based approaches in enhancing IoT security and offers a benchmark for future machine learning-driven detection systems. By addressing AMQP-specific challenges, the study contributes to the development of resilient and secure IoT ecosystems. AMQP; IoT; traffic; signature; cyberattacks +
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endangering patient safety. Additionally, unsecured AMQP deployments are susceptible to Denial-of-Service (DoS) attacks, which can overload IoT devices and disrupt network functionality. As IoT adoption grows, ensuring AMQP security is critical to maintaining data integrity, availability, and confidentiality across connected systems. Despite its advantages, AMQP introduces significant security challenges. IoT devices utilizing AMQP are increasingly targeted by cyberattacks due to inherent vulnerabilities in the protocol. These vulnerabilities have led to various documented attacks, including the following:  
* Distributed Denial of Service (DDoS): Overwhelming a system with traffic from compromised devices, causing service disruptions (e.g., CVE-2021-22116) [2]. * Man-in-the-Middle (MitM): Intercepting communications between devices to eavesdrop or manipulate data (e.g., CVE-2019-3845, CVE-2018-11087) [3]. * Brute Force: Systematic attempts to guess login credentials, leading to unauthorized access (e.g., CVE-2023-24448) [4]. These attacks pose serious threats to the reliability and security of IoT systems, undermining their functionality and trustworthiness. However, research into AMQP-specific vulnerabilities remains limited. Current studies often generalize IoT security issues or focus on other protocols, such as MQTT or CoAP, leaving AMQP underexplored. This has resulted in several gaps in the literature:  
* Limited Focus on AMQP-Specific Threats: Existing research predominantly addresses broader IoT security challenges, with insufficient emphasis on the unique vulnerabilities of AMQP [5]. * Outdated and Narrow Datasets: Most datasets do not reflect recent attack methodologies or encompass the full range of AMQP-specific vulnerabilities. Some datasets focus on older attack types, such as IP sweeping and smurfing [6; 7]. * Theoretical Models Over Practical Scenarios: Many studies rely on analytical approaches, failing to account for the complexity of real-world IoT environments [5]. * Inadequate Cross-Protocol Considerations: Research often isolates protocols, ignoring interactions between AMQP and other IoT protocols that could introduce new vulnerabilities [8].