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A holistic review of network anomaly detection systems: A comprehensive survey
Abstract Network Anomaly Detection Systems (NADSs) are gaining a more important role in
most network defense systems for detecting and preventing potential threats. The paper …
most network defense systems for detecting and preventing potential threats. The paper …
Distributed denial of service (DDoS) resilience in cloud: Review and conceptual cloud DDoS mitigation framework
Despite the increasing popularity of cloud services, ensuring the security and availability of
data, resources and services remains an ongoing research challenge. Distributed denial of …
data, resources and services remains an ongoing research challenge. Distributed denial of …
Deep abstraction and weighted feature selection for Wi-Fi impersonation detection
The recent advances in mobile technologies have resulted in Internet of Things (IoT)-
enabled devices becoming more pervasive and integrated into our daily lives. The security …
enabled devices becoming more pervasive and integrated into our daily lives. The security …
Big data analytics framework for peer-to-peer botnet detection using random forests
Network traffic monitoring and analysis-related research has struggled to scale for massive
amounts of data in real time. Some of the vertical scaling solutions provide good …
amounts of data in real time. Some of the vertical scaling solutions provide good …
Survey of network intrusion detection methods from the perspective of the knowledge discovery in databases process
The identification of network attacks which target information and communication systems
has been a focus of the research community for years. Network intrusion detection is a …
has been a focus of the research community for years. Network intrusion detection is a …
A review on machine learning approaches for network malicious behavior detection in emerging technologies
Network anomaly detection systems (NADSs) play a significant role in every network
defense system as they detect and prevent malicious activities. Therefore, this paper offers …
defense system as they detect and prevent malicious activities. Therefore, this paper offers …
A study on intrusion detection using neural networks trained with evolutionary algorithms
T Dash - Soft Computing, 2017 - Springer
Intrusion detection has been playing a crucial role for making a computer network secure for
any transaction. An intrusion detection system (IDS) detects various types of malicious …
any transaction. An intrusion detection system (IDS) detects various types of malicious …
[PDF][PDF] Deep learning in intrusion detection system: An overview
Identifying unknown attacks is one of the big challenges in network Intrusion Detection
Systems (IDSs) research. In the past decades, researchers adopted various machine …
Systems (IDSs) research. In the past decades, researchers adopted various machine …
Mitigating TCP SYN flooding based EDOS attack in cloud computing environment using binomial distribution in SDN
Cloud Computing provides an auto-scaling feature for dynamic resource utilization to cope
with their customers' requirements and charge as 'pay-per-use'. Attackers get the benefit of …
with their customers' requirements and charge as 'pay-per-use'. Attackers get the benefit of …
Detecting impersonation attack in WiFi networks using deep learning approach
WiFi network traffics will be expected to increase sharply in the coming years, since WiFi
network is commonly used for local area connectivity. Unfortunately, there are difficulties in …
network is commonly used for local area connectivity. Unfortunately, there are difficulties in …