Hybrid Chaotic Zebra Optimization Algorithm and Long Short-Term Memory for Cyber Threats Detection

Cyber Threat Detection (CTD) is subject to complicated and rapidly accelerating developments. Poor accuracy, high learning complexity, limited scalability, and a high false positive rate are problems that CTD encounters. Deep Learning defense mechanisms aim to build effective models for threat detec...

Celý popis

Uloženo v:

Podrobná bibliografie
Vydáno v:	IEEE access Ročník 12; s. 93235 - 93260
Hlavní autoři:	Amin, Reham, El-Taweel, Ghada, Ali, Ahmed F., Tahoun, Mohamed
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Piscataway IEEE 2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	Accuracy Algorithms Classification Classification algorithms Complexity Computer security Cyber security Deep learning Effectiveness Feature extraction feature selection Intrusion detection Long short term memory Machine learning Machine learning algorithms Optimization Optimization algorithms Optimization methods Particle swarm optimization Performance evaluation Recall Swarm intelligence Threat assessment zebra optimization algorithm
ISSN:	2169-3536, 2169-3536
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!

Buďte první, kdo okomentuje tento záznam!