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 …

A survey of defense mechanisms against distributed denial of service (DDoS) flooding attacks

ST Zargar, J Joshi, D Tipper - IEEE communications surveys & …, 2013 - ieeexplore.ieee.org
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 …

Network abnormal traffic detection model based on semi-supervised deep reinforcement learning

S Dong, Y Xia, T Peng - IEEE Transactions on Network and …, 2021 - ieeexplore.ieee.org
The rapid development of Internet technology has brought great convenience to our
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 …

Combining OpenFlow and sFlow for an effective and scalable anomaly detection and mitigation mechanism on SDN environments

K Giotis, C Argyropoulos, G Androulidakis… - Computer Networks, 2014 - Elsevier
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 …

Detection and defense of DDoS attack–based on deep learning in OpenFlow‐based SDN

C Li, Y Wu, X Yuan, Z Sun, W Wang… - International Journal …, 2018 - Wiley Online Library
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 …

Lightweight DDoS flooding attack detection using NOX/OpenFlow

R Braga, E Mota, A Passito - IEEE local computer network …, 2010 - ieeexplore.ieee.org
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 …

An entropy-based network anomaly detection method

P Bereziński, B Jasiul, M Szpyrka - Entropy, 2015 - mdpi.com
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 …

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 …

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 …