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Security problems with the Internet architecture.



Internet had been designed with following features in

mind:



■ scaling

■ heterogeneity

■ complexity at edges (end-to-end problem)

■ autonomy/flexibility



Security as a feature was not in the list. Why?



■ reasonable security mechanism would oppose

fundamental design principles/objectives



Some six hundred RFCs all avoid this issue. Vendors

would rather pack “new features” into their products

than mitigate potential security problems in them.



How big is the problem? Consult Honeynet project

(http://project.honeynet.org ). They found:



■ a random computer on Internet is scanned

roughly dozen times per day



■ expected life-expectancy of a RedHat6.2

server before being hacked is 72 hours

■ windows98 machine with standard file-sharing

was hacked 5 times in 4 days.



Should we care? These machines are often hacked by

a single hacker in a DDoS form (Distributed Denial

of Service)







Attacker



Control

Traffic

Master





Slave Slave Slave Slave





Victim





Architecture of bandwidth attack



Taxonomy of attacks:



A. DoS/DDoS attacks: Denial of Service and

Distributed DoS exhaust the resources of target

host (or to exhaust bandwidth of a particular

link). In Feb 2000, Yahoo, CNN, Amazon.com,

eBay, ..

A1. DoS/DDoS attacks are often launched by

flooding (as jamming a telephone line). Exhausts

resources of a server or its link bandwidth as by

this address spoofing & ping combination





 Perpetrator gains control of slave machines.

 Assume ping commands like

ping(source,destination)

 Master instructs slavei to attack a target by

sending requests ping(target, slavei )



Other example. Smurf amplifier networks.



 Perpetrator sends a

ping(target, network@broadcast_mode)



It is assumed that target machine is on the network

identified in the 2nd argument. Here the router

broadcasting it is limited by packet processing rate,

and not by bandwidth. Target address would be

flooded with simultaneous ping reports from all

hosts. Here Cisco routers come into focus.

What can be done to stop this?



 Configure your operating system to prevent

the machine from responding to ICMP

packets sent to IP broadcast addresses



 Routers must turn-off forwarding directed

broadcasts at all other ports.



Other DDoS attacks: Trinoo, TFN, Stacheldraht, etc.

Trinoo:



■ A Trojan program that affects Windows systems

through DDoS attacks. It copies a file service.exe to

Windows\System directory and it would be active all

the time once it is executed.



■ Anyone running Trinoo client program anywhere

can sneak into the computer without being noticed.





Intrusion-detection Issue



An intruder at time t is X ( t ) working to destabilize

the target system S ( t ). Typically, its activity is one

like the following:



 port flooding

 port probing

 port walking

 online password cracking attempt



 Local anomaly in the network where

Intrusion 

Intrusion occurs.



Therefore, perhaps

Null Hypothesis, H 0 :

 intrusion event

Detection of anomalous event 



Type II error: The null hypothesis H 0 is accepted

when no intrusion took place. False positive.



Inverse problem. Null hypothesis is not accepted and

an intrusion took place. Type I error.



The challenge: Intruder’s attack signature is not yet

established. How do you detect the intruder?



Our only observables at the system level are

information like these



% netstat –s

RAWIP

rawipInDatagrams = 23 rawipInErrors = 0

rawipInCksumErrs = 0 rawipOutDatagrams = 21

rawipOutErrors = 0



UDP

udpInDatagrams = 16132 udpInErrors = 0

udpOutDatagrams = 16163 udpOutErrors = 0



TCP

tcpRtoAlgorithm = 4 tcpRtoMin = 400

tcpRtoMax = 60000 tcpMaxConn = -1

tcpActiveOpens =158905 tcpPassiveOpens =293710

tcpAttemptFails = 56 tcpEstabResets = 5971

tcpCurrEstab = 17 tcpOutSegs = 11019883

tcpOutDataSegs =7924143 tcpOutDataBytes =1691751489

tcpRetransSegs = 83957 tcpRetransBytes =100068036

tcpOutAck =3095286 tcpOutAckDelayed =320811





They could be available via SNMP agent that

samples a host, or a router, or a switch to get the

standard MIB observables. Only from these

observations one must infer whether or not an

intrusion event had been launched at a time t .



Assumption. If X ( t ) = intrusion-event at time t,

S ( t , ) = intruded system at time t and at a stable

equilibrium  such that





0

t tt





The system may move from one stable equilibrium

to another one by normal change in traffic patterns.



If X(t ) then either it would force S ( t , ) to move to

S ( t' , ) where  is another equilibrium state, or it

would move to S ( t' , ) where  is a transition state

or a state of unstable equilibrium.

X(t)









S ( t , e ) S ( t  t , f )

S ( t' ,  )



System movements on

phase space.





In our case, we assume that every X ( t ) pushes a

system to an unstable state  . After the system

spends some time in it, it would settle into some

stabe equilibrium state.



The system can be seen equivalent to a queuing

system as shown below:



To hosts To Network









Server Network









From Network





From hosts

Node interface to a

Network









Things to monitor:

■ ifOutOctets (Octet outflow volume at the interface)

■ ifInOctets (Octet inflow volume at the interface)

■ ifInDiscards (number of inbound packets dropped due to

buffer overflow) At the server buffer



Observables is  ( t )  (ifOutOctets, ifInOctets, ifInDiscards)

Or, in general, it is posted in a parametric form like



 ( t )  (  0 ( t ), 1 ( t ),... i ( t ))





d d n

from which we infer (  ( t ), ,..., n )  S ( t )

dt t dt

The equilibrium states are solutions of the equation



d

0

dt

implying  a constant



This can also be seen equivalent to



  cons tant  N ( 0 , 2 )



where   2 is the variance of  . We assume that at

equilibrium, the profile of any component in  looks

like

1.96 







1.96 









Zero-mean plane

Sample distribution relative to

mean



In this context, intrusion event is defined to be



Defn. 1: A system S is intruded at a time within the

interval t0  t and t0 (the current time) if the state

vector at time t0  ( t0 )    |   | . The tolerance factor

 would be set by system administrator.





Defn. 2: In the vector form, if



k  K  k ( t 0 )   k  |  k   k |   ( t0 )    |   |

where  k is the k th variable monitored, the system has

an intruder at time t0 .



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