Top 100 Electronics,China Electric Tools

This is a guest blog post. Views expressed in this post are original thoughts posted by Graeme Hackland, IT/IS Director at Lotus F1 Team.

It seems that Software Defined Networks (SDN) is the next big thing in the networking space because EVERY vendor is talking about it! Some have chosen to go down the proprietary route, and some like Juniper Networks with their Contrail solutions have a simple, open and much more agile approach.

At a basic level we know that SDN will give us a boost in network performance, it makes sense – layering the network such that the data layer is separate from the control layer is clearly a good thing. In addition it’s really important that this approach helps to simplify network design (clearly the benefit of SDN is eroded if it becomes much more complex) and easier to administer.

However, it’s how SDN enables the move to cloud computing that really interests me.

At the Lotus F1 Team, we’re working with our technical partners to build a private cloud, we’re re-architecting our applications for the cloud and then we’ll pick and choose what we put in the public cloud – SDN is an enabler for this strategy. I have a vision of provisioning IT Services in this elastic cloud model, between public and private on a weekly basis (it shouldn’t be a once or twice a year activity). If you consider the “mobile data centre” that we currently have to take to each Grand Prix track around the world, there is a period of time when that data centre is inaccessible – i.e. while it is in transit. I’d like to switch seamlessly between the trackside private cloud and the public cloud to avoid this “dead time”. We’re seeing rapid data growth at the track, both the telemetry data (which will grow 8x due to the new electronic control unit’s greater capacity) and the “big data” from multiple sources used to make strategy decisions that will lead to better car performance (and ultimately a challenge of the FIA Formula 1 World Championships).

Juniper Networks approach to SDN will help me to drive down costs, increase network performance and most important does not compromise network security.

I know that SDN may not be appropriate for all SMEs; after all there is an economy of scale at play, especially in these early years of adoption, so I’d welcome the thoughts of any readers as to what they think the future of networking will look like and where they feel the tipping point for SDN is.

View the original article here

 
Wente Zheng (L) & Dr. Mo-Yuen Chow (R)

Dr. Mo-Yuen Chow, Professor of Electrical and Computer Engineering at North Carolina State University and Wente Zheng, a Ph.D. student, have developed a software algorithm that detects and isolates cyber-attacks on networked control systems - which are used to coordinate transportation, power and other infrastructure across the United States.

Networked control systems are essentially pathways that connect and coordinate activities between computers and physical devices. For example, the systems that connect temperature sensors, heating systems and user controls in modern buildings are networked control systems.

But, on a much larger scale, these systems are also becoming increasingly important to national infrastructure, such as transportation and power. And, because they often rely on wireless or Internet connections, these systems are vulnerable to cyber-attacks. "Flame" and "Stuxnet" are examples of costly, high-profile attacks on networked control systems in recent years.

As networked control systems have grown increasingly large and complex, system designers have moved away from having system devices - or "agents" - coordinate their activities through a single, centralized computer hub, or brain. Instead, designers have created "distributed network control systems" (D-NCSs) that allow all of the system agents to work together, like a bunch of mini-brains, to coordinate their activities. This allows the systems to operate more efficiently. And now these distributed systems can also operate more securely.

NC State researchers have developed a software algorithm that can detect when an individual agent in a D-NCS has been compromised by a cyber-attack. The algorithm then isolates the compromised agent, protecting the rest of the system and allowing it to continue functioning normally. This gives D-NCSs resilience and security advantages over systems that rely on a central computer hub, because the centralized design means the entire system would be compromised if the central computer is hacked.

"In addition, our security algorithm can be incorporated directly into the code used to operate existing distributed control systems, with minor modifications," says Dr. Chow, co-author of a paper on the work. "It would not require a complete overhaul of existing systems."

"We have demonstrated that the system works, and are now moving forward with additional testing under various cyber-attack scenarios to optimize the algorithm's detection rate and system performance," says Wente Zeng, lead author of the paper.

The paper, "Convergence and Recovery Analysis of the Secure Distributed Control Methodology for D-NCS," will be presented at the IEEE International Symposium on Industrial Electronics, May 28-31, in Taipei, Taiwan. The research was funded by the National Science Foundation.

"Convergence and Recovery Analysis of the Secure Distributed Control Methodology for D-NCS"

Authors: Wente Zeng and Mo-Yuen Chow, North Carolina State University

Presented: May 28-31, IEEE International Symposium on Industrial Electronics, Taipei, Taiwan

Abstract: Distributed control algorithms (e.g., consensus algorithm) are vulnerable to the misbehaving agent compromised by the cyber-attacks in Distributed Networked Control Systems (D-NCS). In this paper we continue our work on the proposed secure distributed control methodology that is capable of performing a secure consensus computation in D-NCS in the presence of misbehaving agents. The methodology is introduced first and proved to be effective through the convergence analysis. We then extend our secure distributed control methodology to the leaderless consensus network by introducing and adding two recovery schemes into the current secure distributed control framework to guarantee the accurate convergence in the presence of misbehaving agents. All phases in our method are distributed in the sense that at each step of the detection, mitigation, identification, update and recovery, every agent only uses local and one-hop neighbors' information.  The simulation results are presented to demonstrate the effectiveness of the proposed methods.

Credit: Matt Shipman | NCSU News Services

View the original article here