A novel intelligent approach for <scp>man‐in‐the‐middle</scp> attacks detection over internet of things environments based on message queuing telemetry transport

Michelena, Álvaro; Aveleira‐Mata, José; Jove, Esteban; Bayón-Gutiérrez, Martí­n; Nováis, Paulo; Fontenla-Romero, Óscar; Calvo-Rolle, José Luís; Aláiz‐Moretón, Héctor

doi:10.1111/exsy.13263

Cited by 10 publications

(3 citation statements)

References 52 publications

(56 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…By intercepting and relaying the messages back to the intending receiver, the attacker makes the sender and the receiver believe they are directly communicating with each other. It is a sort of eavesdropping where the attacker connects with the victim's network to relay incoming and outgoing messages which could be altered by the attacker before relaying back to the receiver [3]. Man-in-the-browser is the most common MITM attack where the attacker could inject malicious proxy malware into the victim's device through browser infection.…”

Section: Man In the Middle (Mitm) Attackmentioning

confidence: 99%

An Investigation into the Performances of the State-of-the-art Machine Learning Approaches for Various Cyber-attack Detection: A Survey

Ige,

Kiekintveld,

Piplai

2024

Preprint

View full text Add to dashboard Cite

To secure computers and information systems from attackers taking advantage of vulnerabilities in the system to commit cybercrime, several methods have been proposed for real-time detection of vulnerabilities to improve security around information systems. Of all the proposed methods, machine learning had been the most effective method in securing a system with capabilities ranging from early detection of software vulnerabilities to real-time detection of ongoing compromise in a system. As there are different types of cyberattacks, each of the existing state-of-the-art machine learning models depends on different algorithms for training which also impact their suitability for detection of a particular type of cyberattack. In this research, we analyzed each of the current state-of-theart machine learning models for different types of cyberattack detection from the past 10 years with a major emphasis on the most recent works for comparative study to identify the knowledge gap where work is still needed to be done with regard to detection of each category of cyberattack

show abstract

Section: Man In the Middle (Mitm) Attackmentioning

confidence: 99%

An Investigation into the Performances of the State-of-the-art Machine Learning Approaches for Various Cyber-attack Detection: A Survey

Ige,

Kiekintveld,

Piplai

2024

Preprint

View full text Add to dashboard Cite

show abstract

“…The public key is used for encryption, while the private key, held exclusively by the receiver, is used for decryption. Notable ciphers for Asymmetric Encryption encompass RSA, Diffie-Hellman, and defence against potential threats like Man-in-the-Middle attacks [95], [96].…”

Section: Secure Shell (Ssh)mentioning

confidence: 99%

Performance, privacy, and security issues of TCP/IP at the application layer: A comprehensive survey

Timothy Murkomen

2024

GSC Adv. Res. Rev.

View full text Add to dashboard Cite

TCP/IP is the backbone of modern network communication, connecting devices across the world. TCP/IP at its core is a suite of protocols that enables the transmission of data between computers, facilitating the foundation of the interconnected global network. At the Application Layer of TCP/IP is where the interaction between software applications and the network occurs. The user-centric protocols such as HTTP, SMTP, FTP, POP3, IMAP and DNS facilitate various tasks at this layer such as web browsing, email communication, and file transfer. This comprehensive survey conducted an exploration of the performance, security and privacy issues at the application layer of the TCP/IP. It initiated by providing a background of TCP/IP model, it’s architecture and the core characteristics, with major focus on the application layer. This paper aimed to discuss the state-of-the-art of performance, privacy and security concerns in TCP/IP application layer. It also proposed future research areas to equip researchers, practitioners, policy makers and the decision makers with tangible knowledge, offering guidance in navigating the performance, privacy and security concerns in TCP/IP Application Layer. It aimed to discuss the current performance, privacy and security research gaps at the Application Layer of the TCP/IP Model. The findings of this research sheds light on the performance, privacy and security issues while suggesting the countermeasures to strengthen and optimize the overall performance, security and privacy of TCP/IP model at the application layer. The paper finally suggests future directions and research areas at the TCP/IP application layer.

show abstract

“…Aveleira‐Mata et al (2023) discuss how to detect man‐in‐the‐middle attacks in MQTT IoT environments using supervised machine learning models. The approach uses an MQTT dataset with man‐in‐the‐middle attacks compiled by the authors.…”

Section: Summary Of Contributionsmentioning

confidence: 99%

Recent trends and advances in machine learning challenges and applications for industry 4.0

Rodriguez‐Fernandez,

Camacho

2023

Expert Systems

View full text Add to dashboard Cite

This editorial summarizes and analyzes 17 articles selected for a special issue on machine learning advances for Industry 4.0 applications. The diverse articles cover fault detection, deep learning optimisation, IoT networking, vehicle control, recommendation systems and domain knowledge integration. Key methods represented include neural networks, deep learning, reinforcement learning and explainable AI. Real‐world industrial case studies showcase machine learning's versatility in enabling intelligent automation, control, and decision‐making across manufacturing, healthcare, transportation and other sectors. While highlighting theoretical innovations, the contributions also demonstrate machine learning's transformative potential for intelligent, connected, self‐optimising next generation production systems. This editorial concisely overviews the latest trends represented in this special issue.

show abstract

A novel intelligent approach for man‐in‐the‐middle attacks detection over internet of things environments based on message queuing telemetry transport

Cited by 10 publications

References 52 publications

An Investigation into the Performances of the State-of-the-art Machine Learning Approaches for Various Cyber-attack Detection: A Survey

An Investigation into the Performances of the State-of-the-art Machine Learning Approaches for Various Cyber-attack Detection: A Survey

Performance, privacy, and security issues of TCP/IP at the application layer: A comprehensive survey

Recent trends and advances in machine learning challenges and applications for industry 4.0

Contact Info

Product

Resources

About