Welcome!

SDN Journal Authors: Liz McMillan, Yeshim Deniz, Elizabeth White, Pat Romanski, TJ Randall

News Feed Item

Research and Markets: The Network Security Implications of Software Defined Networks (SDN)

Research and Markets (http://www.researchandmarkets.com/research/3d46sb/the_network) has announced the addition of the "The Network Security Implications of Software Defined Networks (SDN)" report to their offering.

Software Defined Networking (SDN) is among the buzzwords of the day. SDN is a new approach to network architecture that will generate dividends to network operators.

Communications Service Providers (CSPs) have set their sights on SDN and network function virtualization (NFV) as the vehicles for achieving an unprecedented, and now increasingly necessary, level of automation and programmability.

The ramifications of implementing a new network architecture are enormous. The purpose of this report is to understand the impact of SDN on network security.

Key Topics Covered:

Introduction

What is SDN?

NFV and SDN

Why SDN?

A Note about Definitions

SDN Impact on Security

Potential Danger Points with Implementing Security in an SDN Network

Communication Protocols between Network Security Services

OpenFlow and Security

Security with SDN is a Different Approach

Innovative Approaches to SDN Security

The Last Word

About

For more information visit http://www.researchandmarkets.com/research/3d46sb/the_network

About Research and Markets

Research and Markets is the world's leading source for international market research reports and market data. We provide you with the latest data on international and regional markets, key industries, the top companies, new products and the latest trends.

More Stories By Business Wire

Copyright © 2009 Business Wire. All rights reserved. Republication or redistribution of Business Wire content is expressly prohibited without the prior written consent of Business Wire. Business Wire shall not be liable for any errors or delays in the content, or for any actions taken in reliance thereon.

CloudEXPO Stories
When building large, cloud-based applications that operate at a high scale, it's important to maintain a high availability and resilience to failures. In order to do that, you must be tolerant of failures, even in light of failures in other areas of your application. "Fly two mistakes high" is an old adage in the radio control airplane hobby. It means, fly high enough so that if you make a mistake, you can continue flying with room to still make mistakes. In his session at 18th Cloud Expo, Lee Atchison, Principal Cloud Architect and Advocate at New Relic, discussed how this same philosophy can be applied to highly scaled applications, and can dramatically increase your resilience to failure.
DevOpsSummit New York 2018, colocated with CloudEXPO | DXWorldEXPO New York 2018 will be held November 11-13, 2018, in New York City. Digital Transformation (DX) is a major focus with the introduction of DXWorldEXPO within the program. Successful transformation requires a laser focus on being data-driven and on using all the tools available that enable transformation if they plan to survive over the long term.
With more than 30 Kubernetes solutions in the marketplace, it's tempting to think Kubernetes and the vendor ecosystem has solved the problem of operationalizing containers at scale or of automatically managing the elasticity of the underlying infrastructure that these solutions need to be truly scalable. Far from it. There are at least six major pain points that companies experience when they try to deploy and run Kubernetes in their complex environments. In this presentation, the speaker will detail these pain points and explain how cloud can address them.
Machine learning provides predictive models which a business can apply in countless ways to better understand its customers and operations. Since machine learning was first developed with flat, tabular data in mind, it is still not widely understood: when does it make sense to use graph databases and machine learning in combination? This talk tackles the question from two ends: classifying predictive analytics methods and assessing graph database attributes. It also examines the ongoing lifecycle for machine learning in production. From this analysis it builds a framework for seeing where machine learning on a graph can be advantageous.'
Daniel Jones is CTO of EngineerBetter, helping enterprises deliver value faster. Previously he was an IT consultant, indie video games developer, head of web development in the finance sector, and an award-winning martial artist. Continuous Delivery makes it possible to exploit findings of cognitive psychology and neuroscience to increase the productivity and happiness of our teams.