5,373 research outputs found
Multi-Layer Cyber-Physical Security and Resilience for Smart Grid
The smart grid is a large-scale complex system that integrates communication
technologies with the physical layer operation of the energy systems. Security
and resilience mechanisms by design are important to provide guarantee
operations for the system. This chapter provides a layered perspective of the
smart grid security and discusses game and decision theory as a tool to model
the interactions among system components and the interaction between attackers
and the system. We discuss game-theoretic applications and challenges in the
design of cross-layer robust and resilient controller, secure network routing
protocol at the data communication and networking layers, and the challenges of
the information security at the management layer of the grid. The chapter will
discuss the future directions of using game-theoretic tools in addressing
multi-layer security issues in the smart grid.Comment: 16 page
A contrasting look at self-organization in the Internet and next-generation communication networks
This article examines contrasting notions of self-organization in the Internet and next-generation communication networks, by reviewing in some detail recent evidence regarding several of the more popular attempts to explain prominent features of Internet structure and behavior as "emergent phenomena." In these examples, what might appear to the nonexpert as "emergent self-organization" in the Internet actually results from well conceived (albeit perhaps ad hoc) design, with explanations that are mathematically rigorous, in agreement with engineering reality, and fully consistent with network measurements. These examples serve as concrete starting points from which networking researchers can assess whether or not explanations involving self-organization are relevant or appropriate in the context of next-generation communication networks, while also highlighting the main differences between approaches to self-organization that are rooted in engineering design vs. those inspired by statistical physics
Implementation of Model Based Networked Predictive Control System
Networked control systems are made up of several computer nodes
communicating over a communication channel, cooperating to control a
plant. The stability of the plant depends on the end to end delay from
sensor to the actuator. Although computational delays within the
computer nodes can be made bounded, delays through the
communication network are generally unpredictable. A method which
aims to protect the stability of the plant under communication delays
and data loss, Model Based Predictive Networked Control System
(MBPNCS), has previously been proposed by the authors. This paper aims
to demonstrate the implementation of this type of networked control
system on a non-real-time communication network; Ethernet.
In this paper, we first briefly describe the MBPNCS method, then
discuss the implementation, detailing the properties of the operating
system, communications and hardware, and later give the results on the
performance of the Model Based Predictive Networked Control System
implementation controlling a DC motor.
This work was supported in part by the Scientific and Technological Re
search Council of Turkey, project code 106E155
Optimal redundancy against disjoint vulnerabilities in networks
Redundancy is commonly used to guarantee continued functionality in networked
systems. However, often many nodes are vulnerable to the same failure or
adversary. A "backup" path is not sufficient if both paths depend on nodes
which share a vulnerability.For example, if two nodes of the Internet cannot be
connected without using routers belonging to a given untrusted entity, then all
of their communication-regardless of the specific paths utilized-will be
intercepted by the controlling entity.In this and many other cases, the
vulnerabilities affecting the network are disjoint: each node has exactly one
vulnerability but the same vulnerability can affect many nodes. To discover
optimal redundancy in this scenario, we describe each vulnerability as a color
and develop a "color-avoiding percolation" which uncovers a hidden
color-avoiding connectivity. We present algorithms for color-avoiding
percolation of general networks and an analytic theory for random graphs with
uniformly distributed colors including critical phenomena. We demonstrate our
theory by uncovering the hidden color-avoiding connectivity of the Internet. We
find that less well-connected countries are more likely able to communicate
securely through optimally redundant paths than highly connected countries like
the US. Our results reveal a new layer of hidden structure in complex systems
and can enhance security and robustness through optimal redundancy in a wide
range of systems including biological, economic and communications networks.Comment: 15 page
Understanding Communication Patterns in MOOCs: Combining Data Mining and qualitative methods
Massive Open Online Courses (MOOCs) offer unprecedented opportunities to
learn at scale. Within a few years, the phenomenon of crowd-based learning has
gained enormous popularity with millions of learners across the globe
participating in courses ranging from Popular Music to Astrophysics. They have
captured the imaginations of many, attracting significant media attention -
with The New York Times naming 2012 "The Year of the MOOC." For those engaged
in learning analytics and educational data mining, MOOCs have provided an
exciting opportunity to develop innovative methodologies that harness big data
in education.Comment: Preprint of a chapter to appear in "Data Mining and Learning
Analytics: Applications in Educational Research
Heuristics of node selection criteria to assess robustness of world airport network
The world airport network (WAN) is one of the networked infrastructures that shape today's economic and social activity, so its resilience against incidents affecting the WAN is an important problem. In this paper, the robustness of air route networks is extended by defining and testing several heuristics to define selection criteria to detect the critical nodes of the WAN. In addition to heuristics based on genetic algorithms and simulated annealing, custom heuristics based on node damage and node betweenness are defined. The most effective heuristic is a multi-attack heuristic combining both custom heuristics. Results obtained are of importance not only for advance in the understanding of the structure of complex networks, but also for critical node detection.Peer ReviewedPostprint (author's final draft
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