Intrusion Detection systems are important tools in preventing malicious traffic from
penetrating into networks and systems. Recently, Intrusion Detection Systems are rapidly …

Malicious data manipulation reduces the effectiveness of machine learning techniques,
which rely on accurate knowledge of the input data. Motivated by real-world applications in …

Intrusion Detection Systems (IDS) are essential components in preventing malicious traffic
from penetrating networks and systems. Recently, these systems have been enhancing their …

Motivated by the real-world application of traffic classification at the network edge, we study
the problem of robust decentralized online learning against malicious data generators that …

Malicious data manipulation reduces the effectiveness of machine learning techniques,
which rely on accurate knowledge of the input data. Motivated by real-world applications in …

Evaluating a communication protocol's design in terms of compliance and security is a very
complex and time-consuming task. It requires the configuration of suitable test environments …

Because attacks are becoming more frequent and more complex, intrusion detection
systems (IDSes) need significant improvements to be able to detect new attacks and variants …

網路流量一直是許多研究人員關注的課題, 機器學習的出現更能夠幫助網路管理者快速感知和
抵禦網路流量攻擊. 由於可以作為測試用的真實網路環境下出現之異常流量相當稀缺且難以取得 …

IP fragmentation is still prevalent on the Internet. Defragmented traffic is a prerequisite for
many network processing algorithms. This work focuses on the size and organization of a …