Spam Prevention using Spam Prevention using Access Code (AC) - - PowerPoint PPT Presentation

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Spam Prevention using Spam Prevention using Access Code (AC) - - PowerPoint PPT Presentation

Spam Prevention using Spam Prevention using Access Code (AC) Access Code (AC) Akhtar H Khalil, David J. Parish Akhtar H Khalil, David J. Parish a.h.khalil@lboro.ac.uk , , d.j.parish@lboro.ac.uk d.j.parish@lboro.ac.uk a.h.khalil@lboro.ac.uk


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Spam Prevention using Spam Prevention using Access Code (AC) Access Code (AC)

Akhtar H Khalil, David J. Parish Akhtar H Khalil, David J. Parish

a.h.khalil@lboro.ac.uk a.h.khalil@lboro.ac.uk , , d.j.parish@lboro.ac.uk d.j.parish@lboro.ac.uk

High Speed Networks Group High Speed Networks Group

MSN 2008, MSN 2008, Coseners Coseners July 10 July 10-

  • 11, 2008

11, 2008

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Introduction Introduction

  • Spam

Spam

  • Unsolicited message (Informally)

Unsolicited message (Informally)

  • No single technical definition

No single technical definition

  • SPIT (Spam over Internet Telephony)

SPIT (Spam over Internet Telephony)

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SLIDE 3

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Problems Caused Problems Caused

Worldwide financial losses caused by Worldwide financial losses caused by spam in 2005 were $50 billion [Ferris spam in 2005 were $50 billion [Ferris Research Analyzer] Research Analyzer] Impacts on business communication Exposure to Malware, Spyware, Adware Loss of Corporate Assets The Legal Risk of Spam Spam exceeds 4 times legitimate messages [Johnston and Piscitello, Understanding Voice

  • ver IP Security]
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SLIDE 4

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Impacts of the SOA Anti Impacts of the SOA Anti-

  • spam measures

spam measures

No effective solution against address spoofing, dictionary attacks, sybil attacks etc May prevent legitimate messages Example: Members of the British parliament did not receive messages related to “Sexual Offences Bill” under discussion. Assumed to be porn, these messages were filtered by Anti-spam filters.

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SLIDE 5

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“ “There is no panacea for the There is no panacea for the spam problem, as all spam problem, as all approaches come with some approaches come with some drawbacks drawbacks” ”

( (Rainer Baumann, Rainer Baumann, St St´ ´ephane ephane Cavin Cavin and Stefan and Stefan Schmid Schmid, , "Voice over IP "Voice over IP -

  • security and SPAM," page 10,September

security and SPAM," page 10,September 8, 2006 8, 2006) )

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SLIDE 6

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Access Code Mechanism Access Code Mechanism

  • Two Main Entities

Two Main Entities

  • User ID (ID)

User ID (ID)

  • Access Code (AC)

Access Code (AC) User ID: User ID:

  • Unique

Unique

  • Can be accessed by

Can be accessed by anyone anyone Fig: Basic operation

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SLIDE 7

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Access Code (AC) Access Code (AC)

  • A 5 digit changeable number

A 5 digit changeable number

  • Accessible by legitimate clients

Accessible by legitimate clients

  • Impossible or so

Impossible or so unpleasent unpleasent for a for a spammer to access it that he skips spammer to access it that he skips and goes away and goes away

  • Changing AC will not affect the

Changing AC will not affect the legitimate clients legitimate clients

  • Required by legitimate clients only

Required by legitimate clients only at the first time at the first time

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SLIDE 8

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Spammer Vs Legitimate Spammer Vs Legitimate Client Client

  • A legitimate client has some

A legitimate client has some knowledge about the recipient knowledge about the recipient

  • Transmission Cost of spam is

Transmission Cost of spam is almost zero almost zero

  • Spams are sent to thousands of

Spams are sent to thousands of users within a short time users within a short time

  • It is typically impossible to call a

It is typically impossible to call a spammer back spammer back

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SLIDE 9

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Data Base of a User on the Data Base of a User on the Server Server

Contains three types of lists: Contains three types of lists:

  • Trusted Persons List (TPL)

Trusted Persons List (TPL)

  • Blocked Persons List (BPL)

Blocked Persons List (BPL)

  • New Persons List (NPL)

New Persons List (NPL)

Fig: Data Base of a User on the Server

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SLIDE 10

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Call from an Unknown Call from an Unknown Legitimate Client Legitimate Client

TPL

Shah

BPL NPL

ID

  • Fig. An unknown person wants to make a call

Khalil

  • Prof. Parish
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Caller Server Recipient

ID

Waiting for reply

AC?

Qs/As Session

AC AC

Accepted

Update the Database

  • Fig. Accessing AC from the server

Links 12, 13, 15, 16, 18, 19, 24

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Spammer who Accesses the AC Spammer who Accesses the AC

TPL

Shah Khalil

BPL NPL

Eve

ID Eve

  • Prof. Parish
  • Fig. Eve successfully accesses the AC
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Eve Gives Up and Goes Away Eve Gives Up and Goes Away

TPL

Shah Khalil

BPL

Eve

NPL

  • Fig. Data Base of Prof. Parish after receiving spit
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Analysis Analysis

  • Charging Mechanism

Charging Mechanism

  • Free tokens to each user

Free tokens to each user

  • Enough for legitimate clients

Enough for legitimate clients

  • For obtaining AC from the server one

For obtaining AC from the server one token is subtracted token is subtracted

  • If sender is not added to BPL list then

If sender is not added to BPL list then the token is returned the token is returned

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SLIDE 15

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Dealing With Address Spoofing Dealing With Address Spoofing

Two cases of Address Spoofing Two cases of Address Spoofing

  • Spoofed Address not in the TPL

Spoofed Address not in the TPL

TPL

Shah Khalil

BPL

Eve

NPL

PN Mark

  • Prof. Parish

Fig: Server functions as for unknown persons

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SLIDE 16

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TPL

Khalil Shah

BPL

Eve

NPL

PN Khalil

TPL

Jin Wang

BPL

Mev

NPL TPL

Kostas Yaqoob

BPL

Eve

NPL

  • Prof. Parish

Akhtar John

Spoofed Address is in the TPL Spoofed Address is in the TPL

  • Knowledge about the TPL list of the recipient

Knowledge about the TPL list of the recipient

  • Time factor

Time factor

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Conclusion Conclusion

  • The only Anti

The only Anti-

  • spam mechanism that

spam mechanism that prevents all types of spam attacks prevents all types of spam attacks

  • The only technique that prevents spam in

The only technique that prevents spam in all its forms (spam email, spit, all its forms (spam email, spit, spim spim etc). etc). The most suitable for converged networks The most suitable for converged networks

  • No introduction problem of new

No introduction problem of new callers/users callers/users

  • Does not show any false positive or false

Does not show any false positive or false negative negative

  • Provides the desired degree of

Provides the desired degree of convenience to legitimate clients convenience to legitimate clients

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QUESTIONS QUESTIONS AND AND ANSWER ANSWERS S