A critical review of intrusion detection systems in the internet of things: techniques, deployment strategy, validation strategy, attacks, public datasets and challenges
A Khraisat, A Alazab - Cybersecurity, 2021 - Springer
Abstract The Internet of Things (IoT) has been rapidly evolving towards making a greater
impact on everyday life to large industrial systems. Unfortunately, this has attracted the …
impact on everyday life to large industrial systems. Unfortunately, this has attracted the …
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 …
Performance analysis of intrusion detection systems using a feature selection method on the UNSW-NB15 dataset
Computer networks intrusion detection systems (IDSs) and intrusion prevention systems
(IPSs) are critical aspects that contribute to the success of an organization. Over the past …
(IPSs) are critical aspects that contribute to the success of an organization. Over the past …
Dual-IDS: A bagging-based gradient boosting decision tree model for network anomaly intrusion detection system
The mission of an intrusion detection system (IDS) is to monitor network activities and
assess whether or not they are malevolent. Specifically, anomaly-based IDS can discover …
assess whether or not they are malevolent. Specifically, anomaly-based IDS can discover …
Performance analysis of machine learning models for intrusion detection system using Gini Impurity-based Weighted Random Forest (GIWRF) feature selection …
To protect the network, resources, and sensitive data, the intrusion detection system (IDS)
has become a fundamental component of organizations that prevents cybercriminal …
has become a fundamental component of organizations that prevents cybercriminal …
Towards the development of realistic botnet dataset in the internet of things for network forensic analytics: Bot-iot dataset
The proliferation of IoT systems, has seen them targeted by malicious third parties. To
address this challenge, realistic protection and investigation countermeasures, such as …
address this challenge, realistic protection and investigation countermeasures, such as …
Building an efficient intrusion detection system based on feature selection and ensemble classifier
Y Zhou, G Cheng, S Jiang, M Dai - Computer networks, 2020 - Elsevier
Intrusion detection system (IDS) is one of extensively used techniques in a network topology
to safeguard the integrity and availability of sensitive assets in the protected systems …
to safeguard the integrity and availability of sensitive assets in the protected systems …
Selection of effective machine learning algorithm and Bot-IoT attacks traffic identification for internet of things in smart city
Identifying cyber attacks traffic is very important for the Internet of things (IoT) security in
smart city. Recently, the research community in the field of IoT Security endeavor hard to …
smart city. Recently, the research community in the field of IoT Security endeavor hard to …
A review of intrusion detection systems using machine and deep learning in internet of things: Challenges, solutions and future directions
The Internet of Things (IoT) is poised to impact several aspects of our lives with its fast
proliferation in many areas such as wearable devices, smart sensors and home appliances …
proliferation in many areas such as wearable devices, smart sensors and home appliances …
MQTTset, a new dataset for machine learning techniques on MQTT
IoT networks are increasingly popular nowadays to monitor critical environments of different
nature, significantly increasing the amount of data exchanged. Due to the huge number of …
nature, significantly increasing the amount of data exchanged. Due to the huge number of …