GDLS-FS: Scaling Feature Selection for Intrusion Detection with GRASP-FS and Distributed Local Search

Silva, Estêvão F. C.; Naves, Nícolas; Quincozes, Silvio E.; Quincozes, Vagner E.; Kazienko, Juliano F.; Cheikhrouhou, Omar

doi:10.1007/978-3-031-28451-9_18

“…Efficient algorithms capable of handling high-dimensional data while maintaining detection accuracy are essential. Dimensionality reduction and distributed computing are techniques that could be explored further [120]; -Publicly Available Datasets: Existing datasets like MQTTset [133] and MQTT-IoT-IDS2020 [43] provide a basis for ML-based IoT security research. However, these datasets have limitations in their scope and variety, often failing to encompass specialized scenarios such as edge computing security, IoT device heterogeneity, and real-time anomaly detection.…”

Section: Research Opportunitiesmentioning

confidence: 99%

A survey on IoT application layer protocols, security challenges, and the role of explainable AI in IoT (XAIoT)

Quincozes,

Kazienko

et al. 2024

Int. J. Inf. Secur.

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The Internet of Things (IoT) plays a fundamental role in contemporary society, necessitating an in-depth comprehension of its application layer protocols, intertwined technologies, security issues, and effective countermeasures. This survey delivers an exhaustive analysis of these protocols, emphasizing the escalating significance of Explainable Artificial Intelligence in IoT (XAIoT). To elucidate its practical implications, we conducted a case study examining a real-world scenario where XAIoT significantly bolstered IoT security. This case study demonstrated XAIoT's potential to enhance transparency and trustworthiness in IoT systems. Furthermore, the survey critically evaluates existing literature, pinpointing specific opportunities and gaps in the present state of IoT application layer security. For instance, our analysis revealed a pressing need for more robust security protocols and the integration of advanced machine learning techniques for anomaly detection in IoT applications. This survey, designed to provide a comprehensive perspective, seeks to stimulate additional innovation and research in the realm of secure and intelligent IoT applications. In doing so, it contributes to the ongoing dialogue on improving IoT security, offering valuable insights for researchers and practitioners alike.

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Towards feature engineering for intrusion detection in IEC–61850 communication networks

Quincozes,

Passos

et al. 2024

Ann. Telecommun.

1

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A Survey on IoT Application Layer Protocols, Security Challenges, and the Role of Explainable AI in IoT (XAIoT)

Quincozes,

Kazienko

et al. 2023

Preprint

Self Cite

0

View full text Add to dashboard Cite

The Internet of Things (IoT) plays a fundamental role in contemporary society, necessitating an in-depth comprehension of its application layer protocols, intertwined technologies, security issues, and effective countermeasures. This survey delivers an exhaustive analysis of these protocols, emphasizing the escalating significance of Explainable Artificial Intelligence in IoT (XAIoT). To elucidate its practical implications, we conducted a case study examining a real-world scenario where XAIoT significantly bolstered IoT security. This case study demonstrated XAIoT's potential to enhance transparency and trustworthiness in IoT systems. Furthermore, the survey critically evaluates existing literature, pinpointing specific opportunities and gaps in the present state of IoT application layer security. For instance, our analysis revealed a pressing need for more robust security protocols and the integration of advanced machine learning techniques for anomaly detection in IoT applications. This survey, designed to provide a comprehensive perspective, seeks to stimulate additional innovation and research in the realm of secure and intelligent IoT applications. In doing so, it contributes to the ongoing dialogue on improving IoT security, offering valuable insights for researchers and practitioners alike.

show abstract

GDLS-FS: Scaling Feature Selection for Intrusion Detection with GRASP-FS and Distributed Local Search

Cited by 3 publications

References 24 publications

A survey on IoT application layer protocols, security challenges, and the role of explainable AI in IoT (XAIoT)

A survey on IoT application layer protocols, security challenges, and the role of explainable AI in IoT (XAIoT)

Towards feature engineering for intrusion detection in IEC–61850 communication networks

A Survey on IoT Application Layer Protocols, Security Challenges, and the Role of Explainable AI in IoT (XAIoT)

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