Las redes neuronales convolucionales se han ganado un puesto reconocible en el estudio
del aprendizaje profundo por los avances en cuanto a la clasificación de patrones ya que …

Abstract Intrusion Exposure Solutions in wireless can be categorized into Outlier Intrusion
Detection and Exploitation Intrusion Detection. Outlier Intrusion Detection consider the …

Many new devices, such as phones and tablets as well as traditional computer systems, rely
on wireless connections to the Internet and are susceptible to attacks. Two important types of …

침입탐지 시스템의 네트워크 트래픽 데이터를 사용하여 공격 유형을 분류하기 위한 다양한
시도가 있어왔다. 최근에 많은 연구자들은 새로운 공격 유형을 탐지하기 위하여 서명 …

Intrusion detection systems are used to monitor the network for anomalies to prevent hostile
attacks on the entire network. Many firms are now having NIDS problems, which causes …

In computer security, designing a robust intrusion detection system is one of the most
fundamental and important problems. In this paper, we propose a system-call language …

네트워크 기술의 발전에 따라 네트워크 트래픽이 급격히 증가하고 있다. 이와 함께 네트워크를
통한 사이버 위협 역시 나날이 늘어가면서 다양한 형태의 네트워크 공격을 효율적으로 탐지할 …

Anomaly detection has long been studied in computer security for its capability in detecting
unknown new attacks. From these studies, various machine learning models and feature …

Everyday, security experts and analysts must deal with and face the huge increase of cyber
security threats that are propagating very fast on the Internet and threatening the security of …

Gated recurrent neural networks have shown promising results in sequentially embedded
data. They are an improvised version of recurrent neural networks (Hochreiter & …