Software defined networking architecture, security and energy efficiency: A survey
DB Rawat, SR Reddy - IEEE Communications Surveys & …, 2016 - ieeexplore.ieee.org
Software-defined networking (SDN) is an emerging paradigm, which breaks the vertical
integration in traditional networks to provide the flexibility to program the network through …
integration in traditional networks to provide the flexibility to program the network through …
A survey of defense mechanisms against distributed denial of service (DDoS) flooding attacks
Distributed Denial of Service (DDoS) flooding attacks are one of the biggest concerns for
security professionals. DDoS flooding attacks are typically explicit attempts to disrupt …
security professionals. DDoS flooding attacks are typically explicit attempts to disrupt …
Network abnormal traffic detection model based on semi-supervised deep reinforcement learning
The rapid development of Internet technology has brought great convenience to our
production life, and the ensuing security problems have become increasingly prominent …
production life, and the ensuing security problems have become increasingly prominent …
System for monitoring and managing datacenters
N Yadav, AR Singh, S Gandham, EC Scheib… - US Patent …, 2018 - Google Patents
An example method includes detecting, using sensors, packets throughout a datacenter.
The sensors can then send packet logs to various collectors which can then identify and …
The sensors can then send packet logs to various collectors which can then identify and …
Combining OpenFlow and sFlow for an effective and scalable anomaly detection and mitigation mechanism on SDN environments
Abstract Software Defined Networks (SDNs) based on the OpenFlow (OF) protocol export
control-plane programmability of switched substrates. As a result, rich functionality in traffic …
control-plane programmability of switched substrates. As a result, rich functionality in traffic …
Detection and defense of DDoS attack–based on deep learning in OpenFlow‐based SDN
Distributed denial of service (DDoS) is a special form of denial of service attack. In this
paper, a DDoS detection model and defense system based on deep learning in Software …
paper, a DDoS detection model and defense system based on deep learning in Software …
Lightweight DDoS flooding attack detection using NOX/OpenFlow
Distributed denial-of-service (DDoS) attacks became one of the main Internet security
problems over the last decade, threatening public web servers in particular. Although the …
problems over the last decade, threatening public web servers in particular. Although the …
An entropy-based network anomaly detection method
Data mining is an interdisciplinary subfield of computer science involving methods at the
intersection of artificial intelligence, machine learning and statistics. One of the data mining …
intersection of artificial intelligence, machine learning and statistics. One of the data mining …
MDL-based clustering for application dependency mapping
EC Scheib, A Parandehgheibi, O Madani… - US Patent …, 2019 - Google Patents
Application dependency mapping (ADM) can be automated in a network. The network can
determine an optimum number of clusters for the network using the minimum description …
determine an optimum number of clusters for the network using the minimum description …
Mining anomalies using traffic feature distributions
A Lakhina, M Crovella, C Diot - ACM SIGCOMM computer …, 2005 - dl.acm.org
The increasing practicality of large-scale flow capture makes it possible to conceive of traffic
analysis methods that detect and identify a large and diverse set of anomalies. However the …
analysis methods that detect and identify a large and diverse set of anomalies. However the …