Robotics cyber security: Vulnerabilities, attacks, countermeasures, and recommendations

JPA Yaacoub, HN Noura, O Salman… - International Journal of …, 2022 - Springer
The recent digital revolution led robots to become integrated more than ever into different
domains such as agricultural, medical, industrial, military, police (law enforcement), and …

Machine learning and blockchain technologies for cybersecurity in connected vehicles

J Ahmad, MU Zia, IH Naqvi, JN Chattha… - … : Data Mining and …, 2024 - Wiley Online Library
Future connected and autonomous vehicles (CAVs) must be secured against cyberattacks
for their everyday functions on the road so that safety of passengers and vehicles can be …

A survey of intrusion detection systems based on ensemble and hybrid classifiers

AA Aburomman, MBI Reaz - Computers & security, 2017 - Elsevier
Due to the frequency of malicious network activities and network policy violations, intrusion
detection systems (IDSs) have emerged as a group of methods that combats the …

Unsupervised clustering approach for network anomaly detection

I Syarif, A Prugel-Bennett, G Wills - … , NDT 2012, Dubai, UAE, April 24-26 …, 2012 - Springer
This paper describes the advantages of using the anomaly detection approach over the
misuse detection technique in detecting unknown network intrusions or attacks. It also …

A new feature selection IDS based on genetic algorithm and SVM

H Gharaee, H Hosseinvand - 2016 8th International …, 2016 - ieeexplore.ieee.org
Intrusion detection systems (IDS) are the main components of network security. IDSs monitor
events of a system in a network, analyze the behavior in order to detect intrusions. One of …

Application of bagging, boosting and stacking to intrusion detection

I Syarif, E Zaluska, A Prugel-Bennett, G Wills - Machine Learning and Data …, 2012 - Springer
This paper investigates the possibility of using ensemble algorithms to improve the
performance of network intrusion detection systems. We use an ensemble of three different …

MLEsIDSs: machine learning-based ensembles for intrusion detection systems—a review

G Kumar, K Thakur, MR Ayyagari - The Journal of Supercomputing, 2020 - Springer
Network security plays an essential role in secure communication and avoids financial loss
and crippled services due to network intrusions. Intruders generally exploit the flaws of …

An ensemble based approach for effective intrusion detection using majority voting

AM Bamhdi, I Abrar, F Masoodi - … Computing Electronics and …, 2021 - telkomnika.uad.ac.id
Abstract Of late, Network Security Research is taking center stage given the vulnerability of
computing ecosystem with networking systems increasingly falling to hackers. On the …

Network intrusion detection method based on PCA and Bayes algorithm

B Zhang, Z Liu, Y Jia, J Ren… - Security and …, 2018 - Wiley Online Library
Intrusion detection refers to monitoring network data information, quickly detecting intrusion
behavior, can avoid the harm caused by intrusion to a certain extent. Traditional intrusion …

Implementation of network intrusion detection system using variant of decision tree algorithm

NG Relan, DR Patil - 2015 International Conference on …, 2015 - ieeexplore.ieee.org
As the need of internet is increasing day by day, the significance of security is also
increasing. The enormous usage of internet has greatly affected the security of the system …