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Self-healing networks 2001 IPA Spring Days on When the going gets tough, the tough get going Security L.Spaanenburg. Groningen University, Department of Computing Science. P.O. Box 800, 9700 AV, Groningen. Mail: ben @cs.rug.nl , http://www.cs.rug.nl/~ben

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Self healing networks l.jpg

Self-healing networks

2001 IPA Spring Days

on

When the going gets tough, the tough get going

Security

L.Spaanenburg. Groningen University, Department of Computing Science. P.O. Box 800, 9700 AV, Groningen.

Mail: [email protected], http://www.cs.rug.nl/~ben


Motivation l.jpg

Security involves the guaranteed access

to all resources at all times with top quality

Threats: - from outside

- from inside

Here: internal diseases only

Motivation

What is security?

IPA Spring Days - Security


Agenda l.jpg

The nature of the net

Disasters with central control

The nature of self-healing

In-line monitoring

A hardware / software perspective

Research view

Agenda

What we need and what we can’t

IPA Spring Days - Security


The weak spot l.jpg

A network is billions of tightly connected distributed heterogeneous components

Things happen on a wide time/spatial scale with massive interaction

A local disturbance can spread widely in zero time

Relationships and interdependencies are too complex for mathematical theories

The weak spot

It is the small dog that bites!

IPA Spring Days - Security


User s perspective on networks l.jpg
User’s perspective on networks heterogeneous components

An integrated Power Information Communication technology

IPA Spring Days - Security


Telephone network l.jpg
Telephone network heterogeneous components

A network can be a tree with central control

long distance

1st-order

exchange

medium distance

2nd-order

exchange

short distance

local

exchange

connection

IPA Spring Days - Security


Data network l.jpg
Data Network heterogeneous components

Connectionless communication by broadcast

Host

Router

Subnet

LAN

IPA Spring Days - Security


Means of communication l.jpg

Synchronous heterogeneous components

PDH: Plesiochronous Digital Hierarchy

SDH: Synchronous Digital Hierarchy

ISDN: Integrated Services Digital Network

Asynchronous

FDDI: Fiber Distributed Data Interface

FR: Frame Relay

ATM: Asynchronous Transfer Mode

Means of Communication

Sigh, there are some many ways to communicate

IPA Spring Days - Security


Sources of abnormality l.jpg

Attacks from the outside world heterogeneous components(service attack)

Hick-ups in the network communication

Failures on the network nodes

It’s a detection problem!

Sources of Abnormality

What goes wrong, will go wrong

IPA Spring Days - Security


The keeler allston disaster l.jpg

On 10 August 1996, the Keeler-Allston 500 kV power line tripped creating voltage depression and the McNary Dam went to maximum

The Ross-Lexington 230 kV line also tripped and pushed the McNary Dam over the edge

The McNary Dam sets off oscillations that went to 500 MW within 1.5 minutes

The North-South Pacific INTER-tie isolated 11 US states and 2 Canadian provinces

The Keeler-Allston disaster

The network is vulnerable for local abnormalities

IPA Spring Days - Security


The 1998 galactic page out l.jpg

In May 1998, the Galaxy-IV satellite was disabled by unknown causes

US National Public Radio and 40M pagers went out, airline flights delayed and data networks had to be manually reconfigured

Many geo-stationary satellites are 800 – 1400 km; 13 (60-), 35 (70-), 69 (80-) and 250 (90-)

10 million pieces of debris > 1 mm

The 1998 Galactic page out

The weak belly of the Earth

IPA Spring Days - Security


Other fault cascades l.jpg

Finagle’s Law causes

“Anything that can go wrong, will”

Antibiotics cause resistance (DDT)

Code replication also works for errors

Other fault cascades

Cause/effect relations occur frequently

IPA Spring Days - Security


Self healing in history l.jpg

1993 AT&T announced the self-healing causes wireless network

1998 SUN bought the RedCape Policy Framework for self-healing software

1998 HP released the sefl-healing version of OpenView Network Node Manager

2001 Concord Com. Announced self-healing for the home

Self-healing in history

The name has been used before

IPA Spring Days - Security


Self healing ingredients l.jpg

Application causeshandling the communication

Presentation message formatting

Session controls traffic between parties

Transport converts packets into framesv.v.

Network controls frame routing

Data Link frames of bit sequences

Physical relays physical quantities

Self-Healing ingredients

Self-healing = Detection + Diagnosis + Self-Repair

Network

Test

Node

Test

Recon-

figure

IPA Spring Days - Security


An initiative in self healing l.jpg

The CIN/SI is funded by the Electronic Power Research Institute and the US Dept. of Defense as part of the Government-Industry Collaborative University Research program

28 universities in 6 consortia started Spring 1999 to spent $30 M in 5 years

The approach is multi-agent technology

An Initiative in Self-Healing

The Complex Interactive Networks/Systems Initiative

IPA Spring Days - Security


Cin si consortia l.jpg

[CalTech] CIN Mathematical Foundation Institute and the US Dept. of Defense as part of the Government-Industry Collaborative University Research program

[CMU] Context-dependent Agents

[Cornell] Failure Minimization

[Harvard] Modeling and Diagnosis

[Purdue] Intelligent Management

[Washington] Defense to Attacks

CIN/SI consortia

The different aspects of self-healing

IPA Spring Days - Security


Key issues l.jpg

Pre-programming misses the target by lack of context dependence

No damage would have occurred if the load on the McNary Dam would have decreased by 0.4% during the next 30 minutes

Local agents making real-time decision would have eliminated the Keeler-Allson disaster.

Key issues

Central control comes too late by definition

IPA Spring Days - Security


Basic agent types l.jpg

Agents are called cognitive or rational when equipped with clear rules and algorithms

Agents are called reactive when their functioning depends on the interrogation of the environment

Both type of agents are required on the decision-

making layers handling respectively reaction,

coordination and deliberation

Basic agent types

What are agents?

IPA Spring Days - Security


Cin si architecture 1 l.jpg
CIN/SI architecture (1) clear rules and algorithms

Operational control of the power plant

Triggering events

Plans/Decisions

Events/alarm

Filtering Agents

Model update

Agents

Command

Agents

Controls

Events/

alarms

Faults Isolation

Agents

Frequency Stability

Agents

Protection

Agents

Generation

Agents

Power System

IPA Spring Days - Security


Cin si architecture 2 l.jpg
CIN/SI architecture (2) clear rules and algorithms

Strategic management of the power grid

Hidden Failure

Monitoring Agents

Reconfiguration

Agents

Vulnerability Assessment

Agents

Restoration

Agents

Events Identification

Agents

Planning

Agents

Triggering events

Plans/Decisions

Events/alarm

Filtering Agents

Model update

Agents

Command

Agents

IPA Spring Days - Security


Monitoring the process l.jpg
Monitoring the process clear rules and algorithms

Strategic decisions on tactic control

Monitor

Control

Process

Actuator

Sensor

IPA Spring Days - Security


The network emphasis l.jpg

Agent clear rules and algorithms

Agent

Agent

Agent

Agent

Agent

The network emphasis

The network glues the agents together

Network

IPA Spring Days - Security


Defect looses all l.jpg

But what we need is: clear rules and algorithms

Mutual observation between nodes

Group decision of testing agents

Implied reconfiguration of the network

How can we facilitate

testing with agent properties?

Defect looses all

Majority voting is a centralized consensus scheme

IPA Spring Days - Security


Agent characteristics l.jpg
Agent characteristics clear rules and algorithms

What is security?

mouse

messages

...

other agents

messages

move

change appearance

speak

effec

tors

sen

sors

Behaviour

  • Independent, Reactive,Proactive, Social

IPA Spring Days - Security


Built in block observation l.jpg
Built-in Block Observation clear rules and algorithms

Testing complex systems requires autonomy

generator

process

verifier

IPA Spring Days - Security


Linear feedback shift register l.jpg

When data flows over identical nodes, clear rules and algorithms

the typical function can be characterized

by the feedback polynomial

Linear Feedback Shift-register

Generation of ordered bit strings by EXORs

IPA Spring Days - Security


Friedmann model l.jpg
Friedmann model clear rules and algorithms

The aim is for a locally compacted set of patterns

Process

I

O

Q

IPA Spring Days - Security


A basic function l.jpg

A simple low-pass filter clear rules and algorithms

Takes a data sampling routine,multiplying adder and final function 1/N.

A basic function

Proto-typical software on a small PIC controller

IPA Spring Days - Security


A neuron l.jpg

A simple neuron clear rules and algorithms

Is similar to the low-pass filter except for the incoming data. Operates from the same input data ring-buffer.

A neuron

Intelligence can be built from filtering

IPA Spring Days - Security


A neural network l.jpg

A feed-forward network clear rules and algorithms

Differs only in the layer-by-layer switching of the I/O-blocks

A neural network

Where there is one neuron, there can be more

IPA Spring Days - Security


Non linear feedback sr l.jpg

When data flows over identical nodes, clear rules and algorithms

the typical function can be characterized

by the globally recurrent neural network

Non-Linear Feedback SR

Generation of ordered patterns by Correlators

IPA Spring Days - Security


Neural observation l.jpg

Analog correlation is about finding the functional similarity

Digital correlation is the same except for the effect of crisping

Random access storage is always larger than storage of an ordered function

The neurally approximated function allowes for a dense salvage of ordered I/O-pairs

Neural Observation

Analog correlation looks like digital EXOR

IPA Spring Days - Security


Data flow architecture l.jpg

When data flows over identical nodes, similaritythe typical function can be characterized

Built-In Logic Block Observation

The BIFBO can also be shared with neighboring nodes

Built-In Function Block Observation

The local test does not differentiate between hardware and software

Data-Flow Architecture

Data discrepancy is low-level abnormal behavior

IPA Spring Days - Security


Question 1 l.jpg

If you can not test it, then it’s not worth to design it. similarity

Hierarchical design needs a hierarchical test.

Abstraction gives a condensed view on reality.

Abstraction provides for scalability.

Question 1

Is there an abstractional test?

IPA Spring Days - Security


Question 2 l.jpg

Interaction is good, conflicts are less similarity

If resources have a state, access should be bounded by state

Conflicting services pose basically a scheduling problem

It’s hard to schedule over an arbitrary network

Question 2

Is feature interaction really a static problem?

IPA Spring Days - Security


Question 3 l.jpg

Design should be scalable; test is no exception. similarity

Detection can do without diagnosis;Diagnosis can not go without detection.

Testing can be based on area (coverage) or on frontier (sensitivity)

The boundary between software and hardware is still moving

Question 3

Do neural networks provide for a built-in test?

IPA Spring Days - Security


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