Degrees incorporating this pedagocial element :
Description
Security of Network and Applications (18h + 8h labs)
The objective of this class is to introduce security principles, on the theoretical, organizational and technical aspects. The points which are more specifically developed are: detection errors, firewall technics, network architecture, cryptology and VPN, antivirus strategy. Are also discussed how to implement a security strategy, and some elements for the definition of a security policy. Some elements about safe networks, or networks for safety or critical applications, are also studied.
Lesson 
Topic  

1 
Introduction to networks, error detection and correction  

Bases of network, theoretical elements of error correction and detection, application in the case of parity, CRC, checksum.  

DEPENDABILITY  SECURITY 

2 
Dependability  security  risk analysis  

Concepts, application to networks and information systems, simple application examples.  

TECHNOLOGY FOR SECURITY 

3 
Attack strategies  

The phases of an attack, types of attacks.  
4 
Technologies for security:  

Network infrastructure, filtering, security protocols, VPN.  

METHODOLOGIES 

5 
Cryptography  

Theories on symmetric and asymmetric cryptography, DES, RSA, application to encryption, hash calculation, signature, certificates.  
6 
Virology  

Bases of virology. application to encryption, hash calculation, signature, certificates.  

LABS on NETWORK AND SECURITY 

Lab 1 
Firewalls and wireless networks  
Lab 2 
Communication security and encryption 
Field buses and Zigbee (10.5 h + 15h labs)
Distributed Algorithms and Network Systems (13.5 h + 6h labs)
Objectives Distributed algorithms aim at obtaining a global goal by exploiting a large number of simple devices (``agents''), and their local interactions. These algorithms can be for the purposes of estimation in a wireless sensor network, or control e.g. of a selforganized robotic fleet. This introductory class will first review the necessary tools from graph theory and Markov chains, and then present consensus: a prototypical example of distributed algorithm, as well as a building block for more complex algorithms. Theory will be accompanied by implementation on a realworld sensor network: FIT/IoT LAB.Class schedule
 Introduction: network systems
 Graphs: fundamentals of algebraic graph theory
 Markov chains: convergence to invariant measure, PerronFrobenius theorem
 Consensus (timeinvariant graph)
 Consensus (gossip: randomly varying graph)
 Consensusbased algorithms: using consensus as a building block of other algorithms (e.g., localisation from relative measurements, leastsquares regression, gradient descent minimization, distributed Kalman filter, counting nodes in an anonymous network)
 Labs (3): implementation of distributed algorithms on real sensor network, remotely using FIT/IoT LAB. Programming language: C.
Bibliography
Security of Network and Applications
 S. GhernaoutiHélié, "Sécurité informatique et réseaux", Dunod, 2005.
 J. Steinberg & T. Speed, "SSL VPN, Understanding, evaluating and planning secure, webbased remote access", 2005.
 F. Halsall, "Computer networking and the internet", Addison Welseley, 2005.
Distributed Algorithms and Network Systems
 F. Bullo, J. Cortes, and S. Martinez, Distributed Control of Robotic Networks, Princeton, 2009. Available online.
 M. Mesbahi and M. Egerstedt, Graph Theoretic Methods in Multiagent Networks, Princeton University Press, 2010.
 D.A. Levin, Y. Peres, and E.L. Wilmer, Markov chains and mixing times, American Mathematical Society, 2010.
 F. Garin, L. Schenato, A survey on distributed estimation and control applications using linear consensus algorithms, in "Networked Control Systems", A. Bemporad, M. Heemels, M. Johansson eds, Springer Lecture Notes in Control and Information Sciences, vol. 406, Chapter 3, pp. 75107, Springer, 2011.
In brief
Period : Semester 9Credits : 6
Number of hours
 Practical work (TP) : 22h
 Lectures (CM) : 31.5h
Location(s) : Grenoble
Language(s) : English