Because of the popularity of the Internet of Things (IoT), the rapid expansion of computer
networks, and the vast number of important applications, cyber security has lately garnered …

互联网的不断发展与广泛使用给网络用户带来了极大的方便, 但同时也使得网络安全形势变得越
来越严峻. 传统的基于签名的入侵检测方法难以应对日益增多的加密攻击检测和零日攻击检测 …

A Comprehensive Tutorial and Survey of Applications of Deep Learning for Cyber Security
Page 1 P osted on 5 Jan 2020 — CC-BY 4.0 — h ttps://doi.org/10.36227/tech rxiv.11473377.v1 …

As attack techniques become more sophisticated, detecting new and advanced cyberattacks
with traditional intrusion detection techniques based on signature and anomaly is becoming …

The optimisation and validation of a classifiers performance when applied to real world
problems is not always effectively shown. In much of the literature describing the application …

Nowadays, with the great success of deep learning technology, using deep learning method
to solve information security issues has become a study hot spot. Although some literal …

With the wide adoption of the internet and its applications in recent years, many antagonists
have been exploiting information exchange for malicious activities. Intrusion detection and …

Time series prediction is one of the major tasks in the field of data mining. The approaches
of time series prediction can be divided into statistical techniques and computational …

Аннотация В статье рассмотрены архитектура и структура наиболее эффективных в
задачах классификации сетевого трафика искусственных нейронных сетей (ИНС) …

Intrusion detection mechanism is an important way to protect user data privacy. In the
traditional network intrusion detection model, once security policies and rules are …