Deep reinforcement learning for cyber security
The scale of Internet-connected systems has increased considerably, and these systems are
being exposed to cyberattacks more than ever. The complexity and dynamics of …
being exposed to cyberattacks more than ever. The complexity and dynamics of …
A survey on indexing techniques for big data: taxonomy and performance evaluation
The explosive growth in volume, velocity, and diversity of data produced by mobile devices
and cloud applications has contributed to the abundance of data or 'big data.'Available …
and cloud applications has contributed to the abundance of data or 'big data.'Available …
Multi-agent systems: A survey
Multi-agent systems (MASs) have received tremendous attention from scholars in different
disciplines, including computer science and civil engineering, as a means to solve complex …
disciplines, including computer science and civil engineering, as a means to solve complex …
A deep learning based DDoS detection system in software-defined networking (SDN)
Distributed Denial of Service (DDoS) is one of the most prevalent attacks that an
organizational network infrastructure comes across nowadays. We propose a deep learning …
organizational network infrastructure comes across nowadays. We propose a deep learning …
Evaluation of machine learning classifiers for mobile malware detection
Mobile devices have become a significant part of people's lives, leading to an increasing
number of users involved with such technology. The rising number of users invites hackers …
number of users involved with such technology. The rising number of users invites hackers …
A secure adaptive control for cooperative driving of autonomous connected vehicles in the presence of heterogeneous communication delays and cyberattacks
The development of autonomous connected vehicles, moving as a platoon formation, is a
hot topic in the intelligent transportation system (ITS) research field. It is on the road and …
hot topic in the intelligent transportation system (ITS) research field. It is on the road and …
A game theory approach for cooperative control to improve data quality and false data detection in WSN
R Casado‐Vara, F Prieto‐Castrillo… - … Journal of Robust …, 2018 - Wiley Online Library
New solutions are required for the management of heterogeneous distributed sensor
networks in order to address the problem of data quality and false data detection in wireless …
networks in order to address the problem of data quality and false data detection in wireless …
Benchmarking datasets for anomaly-based network intrusion detection: KDD CUP 99 alternatives
A Divekar, M Parekh, V Savla… - 2018 IEEE 3rd …, 2018 - ieeexplore.ieee.org
Machine Learning has been steadily gaining traction for its use in Anomaly-based Network
Intrusion Detection Systems (A-NIDS). Research into this domain is frequently performed …
Intrusion Detection Systems (A-NIDS). Research into this domain is frequently performed …
Internet of things for smart farming and frost intelligent control in greenhouses
A Castañeda-Miranda, VM Castaño-Meneses - Computers and Electronics …, 2020 - Elsevier
This paper is aimed at continuation of frost intelligent control from the smart farming
perspective that is proposed by Castañeda and Castaño (2017) through Internet of things …
perspective that is proposed by Castañeda and Castaño (2017) through Internet of things …
Applications of artificial intelligence techniques to combating cyber crimes: A review
With the advances in information technology (IT) criminals are using cyberspace to commit
numerous cyber crimes. Cyber infrastructures are highly vulnerable to intrusions and other …
numerous cyber crimes. Cyber infrastructures are highly vulnerable to intrusions and other …