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Data preprocessing for anomaly based network intrusion detection: A review
JJ Davis, AJ Clark - computers & security, 2011 - Elsevier
Data preprocessing is widely recognized as an important stage in anomaly detection. This
paper reviews the data preprocessing techniques used by anomaly-based network intrusion …
paper reviews the data preprocessing techniques used by anomaly-based network intrusion …
[BOK][B] The state of the art in intrusion prevention and detection
ASK Pathan - 2014 - api.taylorfrancis.com
Most of the security threats in various communications networks are posed by the illegitimate
entities that enter or intrude within the network perimeter, which could commonly be termed …
entities that enter or intrude within the network perimeter, which could commonly be termed …
Flow-based anomaly detection in high-speed links using modified GSA-optimized neural network
Ever growing Internet causes the availability of information. However, it also provides a
suitable space for malicious activities, so security is crucial in this virtual environment. The …
suitable space for malicious activities, so security is crucial in this virtual environment. The …
NTLFlowLyzer: Towards generating an intrusion detection dataset and intruders behavior profiling through network and transport layers traffic analysis and pattern …
Network security remains a critical concern in modern computing systems due to the
constant emergence of threats and attacks. This paper introduces a comprehensive …
constant emergence of threats and attacks. This paper introduces a comprehensive …
Deep IP flow inspection to detect beyond network anomalies
Taking into account the accelerated rate of network growth, the occurrence of anomalies
becomes inevitable. A single anomaly can affect the network performance so it is crucial to …
becomes inevitable. A single anomaly can affect the network performance so it is crucial to …
[HTML][HTML] A novel privacy preserving user identification approach for network traffic
The prevalence of the Internet and cloud-based applications, alongside the technological
evolution of smartphones, tablets and smartwatches, has resulted in users relying upon …
evolution of smartphones, tablets and smartwatches, has resulted in users relying upon …
[HTML][HTML] An ensemble of text convolutional neural networks and multi-head attention layers for classifying threats in network packets
H Kim, Y Yoon - Electronics, 2023 - mdpi.com
Using traditional methods based on detection rules written by human security experts
presents significant challenges for the accurate detection of network threats, which are …
presents significant challenges for the accurate detection of network threats, which are …
Towards an efficient DDoS detection scheme for software-defined networks
NAS Lima, MP Fernandez - IEEE Latin America Transactions, 2018 - ieeexplore.ieee.org
Software-Defined Networks (SDN) are becoming a trending network technology in the
modern Internet by splitting control and data planes and using a central controller. An SDN …
modern Internet by splitting control and data planes and using a central controller. An SDN …
Real-time DDoS attack detection for Cisco IOS using NetFlow
D van der Steeg, R Hofstede… - 2015 IFIP/IEEE …, 2015 - ieeexplore.ieee.org
Flow-based DDoS attack detection is typically performed by analysis applications that are
installed on or close to a flow collector. Although this approach allows for easy deployment …
installed on or close to a flow collector. Although this approach allows for easy deployment …
Data mining approach for detection of DDoS attacks utilizing SSL/TLS protocol
Denial of Service attacks remain one of the most serious threats to the Internet nowadays. In
this study, we propose an algorithm for detection of Denial of Service attacks that utilize …
this study, we propose an algorithm for detection of Denial of Service attacks that utilize …