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Unsupervised Learning for Feature Selection: A Proposed Solution for Botnet Detection in 5G Networks
IEEE Transactions on Industrial Informatics, 2023The world has seen exponential growth in deploying Internet of Things (IoT) devices. In recent years, connected IoT devices have surpassed the number of connected non-IoT devices.
Moemedi Lefoane +3 more
semanticscholar +1 more source
Botnet‐based IoT network traffic analysis using deep learning
Security and Privacy, 2023IoT networks are increasingly being connected to a wide range of devices, and the number of devices connected has significantly increased in recent years.
Nongthombam Joychandra Singh +3 more
semanticscholar +1 more source
Proceedings of the Fifth International Conference on Security of Information and Networks, 2012
Many different approaches have been used to target Internet security throughout time. It is now easy to realize the attackers' motivational shifts from the early days of lonely, proud-based, virus development to the recent eras of cooperative Internet cyber criminality where high profit and damage became a reality.
Luís Mendonça, Henrique Santos
openaire +1 more source
Many different approaches have been used to target Internet security throughout time. It is now easy to realize the attackers' motivational shifts from the early days of lonely, proud-based, virus development to the recent eras of cooperative Internet cyber criminality where high profit and damage became a reality.
Luís Mendonça, Henrique Santos
openaire +1 more source
Towards Detection of Zero-Day Botnet Attack in IoT Networks Using Federated Learning
ICC 2023 - IEEE International Conference on Communications, 2023Automated Internet of Things (IoT) devices generate a considerable amount of data continuously. However, an IoT network can be vulnerable to botnet attacks, where a group of IoT devices can be infected by malware and form a botnet.
Jielun Zhang +4 more
semanticscholar +1 more source
IoT Botnet Detection Based on Anomalies of Multiscale Time Series Dynamics
IEEE Transactions on Knowledge and Data Engineering, 2023In this work, we propose a solution for detecting botnet attacks on the Internet of Things (IoT) by identifying anomalies in the temporal dynamics of their devices.
J. Borges +4 more
semanticscholar +1 more source
IEEE Internet of Things Journal
Detecting botnets is an essential task to ensure the security of Internet of Things (IoT) systems. Machine learning (ML)-based approaches have been widely used for this purpose, but the lack of interpretability and transparency of the models often limits
Rajesh Kalakoti +2 more
semanticscholar +1 more source
Detecting botnets is an essential task to ensure the security of Internet of Things (IoT) systems. Machine learning (ML)-based approaches have been widely used for this purpose, but the lack of interpretability and transparency of the models often limits
Rajesh Kalakoti +2 more
semanticscholar +1 more source
Botnet attack detection in Internet of Things devices over cloud environment via machine learning
Concurrency and Computation, 2021With the arrival of the Internet of Things (IoT) many devices such as sensors, nowadays can communicate with each other and share data easily. However, the IoT paradigm is prone to security concerns as many attackers try to hit the network and make it ...
Muhammad Waqas +8 more
semanticscholar +1 more source
Cyber-Physical Attack Launched From EVSE Botnet
IEEE Transactions on Power SystemsWith the development of electric vehicles, millions of electric vehicle service equipment (EVSE) are integrated into the power grid. These EVSEs are weakly protected from cyber-attacks.
Fanrong Wei, Xiangning Lin
semanticscholar +1 more source
Detecting Botnet Spam Activity by Analyzing Network Traffic Using Two-Stack Decision Tree Algorithms
2023 International Conference of Computer Science and Information Technology (ICOSNIKOM), 2023Botnets are a type of malware that threatens network security. One of the frequently encountered botnet threats is SPAM. Many studies focus on building detection models to classify botnet and non-botnet activities in network flows.
Muhammad Aidiel Rachman Putra +3 more
semanticscholar +1 more source