Results 101 to 110 of about 980 (175)

An effectiveness of deep learning with fox optimizer-based feature selection model for securing cyberattack detection in IoT environments. [PDF]

Sci Rep
Alkhonaini MA.
europepmc   +1 more source

Dataset-centric evaluation of federated intrusion detection models in IoT networks. [PDF]

Sci Rep
Bilal MA, Ul Islam I, Idrees S, Qasim M, Khan MJ, Khan J.   +5 more
europepmc   +1 more source

RETRACTED: Enhancing IoT cybersecurity through lean-based hybrid feature selection and ensemble learning: A visual analytics approach to intrusion detection.

PLoS One
Zada I, Omran E, Jan S, Alfraihi H, Alsalamah S, Alshahrani A, Hayat S, Phi N.   +7 more
europepmc   +1 more source

Mitigating distributed denial of service attacks using attribute subset selection with temporal convolutional networks. [PDF]

Sci Rep
Alamro H, Alghamdi AM, Alshuhail A, Ebad SA, Ghaleb M, Alkhiri H, Mahgoub H, Alamri MZ.   +7 more
europepmc   +1 more source

(H-DIR)²: A Scalable Entropy-Based Framework for Anomaly Detection and Cybersecurity in Cloud IoT Data Centers. [PDF]

Sensors (Basel)
Tosi D, Pazzi R.
europepmc   +1 more source

Modelling of hybrid deep learning framework with recursive feature elimination for distributed denial of service attack detection systems. [PDF]

Sci Rep
Alkhliwi S.
europepmc   +1 more source

Comparative evaluation of approaches & tools for effective security testing of Web applications. [PDF]

PeerJ Comput Sci
Qadir S, Waheed E, Khanum A, Jehan S.
europepmc   +1 more source

An IoT intrusion detection framework based on feature selection and large language models fine-tuning. [PDF]

Sci Rep
Ma H, Zhang W, Zhang D, Chen B.
europepmc   +1 more source

A cost effective machine learning based network intrusion detection system using Raspberry Pi for real time analysis. [PDF]

PLoS One
Wijethilaka RWKS, Yapa K, Siriwardena D.
europepmc   +1 more source

Enhanced cybersecurity threat detection using novel tri-metaheuristic loss functions in generative adversarial networks with adaptive attention preservation for network traffic augmentation. [PDF]

Sci Rep
Khalil HM, Elrefaiy A, Elbaz M, Loey M.
europepmc   +1 more source