Network intrusion detection for IoT security based on learning techniques
Pervasive growth of Internet of Things (IoT) is visible across the globe. The 2016 Dyn
cyberattack exposed the critical fault-lines among smart networks. Security of IoT has …
cyberattack exposed the critical fault-lines among smart networks. Security of IoT has …
Unsupervised machine learning for networking: Techniques, applications and research challenges
While machine learning and artificial intelligence have long been applied in networking
research, the bulk of such works has focused on supervised learning. Recently, there has …
research, the bulk of such works has focused on supervised learning. Recently, there has …
Anomaly traffic detection based on communication-efficient federated learning in space-air-ground integration network
In this paper, we study the architectures of space-air-ground integration network (SAGIN)
proposed by domestic scientific research institutes, and put forward an collaborative federal …
proposed by domestic scientific research institutes, and put forward an collaborative federal …
Anomaly-based intrusion detection from network flow features using variational autoencoder
S Zavrak, M Iskefiyeli - IEEE Access, 2020 - ieeexplore.ieee.org
The rapid increase in network traffic has recently led to the importance of flow-based
intrusion detection systems processing a small amount of traffic data. Furthermore, anomaly …
intrusion detection systems processing a small amount of traffic data. Furthermore, anomaly …
A consolidated decision tree-based intrusion detection system for binary and multiclass imbalanced datasets
The widespread acceptance and increase of the Internet and mobile technologies have
revolutionized our existence. On the other hand, the world is witnessing and suffering due to …
revolutionized our existence. On the other hand, the world is witnessing and suffering due to …
A deep auto-encoder based approach for intrusion detection system
F Farahnakian, J Heikkonen - 2018 20th International …, 2018 - ieeexplore.ieee.org
One of the most challenging problems facing network operators today is network attacks
identification due to extensive number of vulnerabilities in computer systems and creativity of …
identification due to extensive number of vulnerabilities in computer systems and creativity of …
From intrusion detection to attacker attribution: A comprehensive survey of unsupervised methods
Over the last five years there has been an increase in the frequency and diversity of network
attacks. This holds true, as more and more organizations admit compromises on a daily …
attacks. This holds true, as more and more organizations admit compromises on a daily …
Flow-based intrusion detection: Techniques and challenges
MF Umer, M Sher, Y Bi - Computers & Security, 2017 - Elsevier
Flow-based intrusion detection is an innovative way of detecting intrusions in high-speed
networks. Flow-based intrusion detection only inspects the packet header and does not …
networks. Flow-based intrusion detection only inspects the packet header and does not …
A multi-level intrusion detection system for wireless sensor networks based on immune theory
VT Alaparthy, SD Morgera - IEEE Access, 2018 - ieeexplore.ieee.org
The human body has been, and will continue to be, a source of inspiration for researchers
across various disciplines owing to its robustness and myriad of functions. While some of …
across various disciplines owing to its robustness and myriad of functions. While some of …
Artificial Immune Systems approaches to secure the internet of things: A systematic review of the literature and recommendations for future research
Abstract As the Internet of Things (IoT) recently attains tremendous popularity, this promising
technology leads to a variety of security challenges. The traditional solutions do not fit the …
technology leads to a variety of security challenges. The traditional solutions do not fit the …