where are we at - topic overview - eindhoven university of...

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Where are we at - Topic overview 1 Lecture 6A: Security Protocols Lecture 3A: Attacks on Web servers, malware Use Try to achieve Lecture 1A: Security requirements/features Threatens Lecture 1B,2A: Cryptography 3B: Certificates and Trust Lecture 2B: Network threats Threatens Lecture 5A&B Authentication Lecture 7A Privacy Lecture 4A&B Access Rights

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Page 1: Where are we at - Topic overview - Eindhoven University of ...jhartog/CourseSecurity/materials/Slides/13-8-Trust.… · CV(out) 128 128 P1 Y (block) P2 P3 P4 512 X Permutations Round

Where are we at - Topic overview

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Lecture 6A: Security Protocols

Lecture 3A:Attacks onWeb servers,malware

Use

Try to achieve

Lecture 1A:Security requirements/features

Threatens

Lecture 1B,2A: Cryptography3B: Certificates and Trust

Lecture 2B: Network threats

Threatens

Lecture 5A&BAuthentication

Lecture 7APrivacy

Lecture 4A&BAccess Rights

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Certificates & Trust

Hashes, Digital Signature, PKIs, Trust management

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Error correction - Hash - MAC

CRC check or MD5 checksum Common for e.g. ftp sites Does this add security?

28997d14055f15db063eb92e1c8a7ebb gimp-2.8.0.tar.bz2

134396e4399b7e753ffca7ba366c418f gimp-2.8.0-RC1.tar.bz2

Excerpt; short `description’ of document Fixed size output for any size input

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Error correction - Hash - MAC

28997d14055f15db063eb92e1c8a7ebb gimp-2.8.0.tar.bz2

134396e4399b7e753ffca7ba366c418f gimp-2.8.0-RC1.tar.bz2

Excerpt; short `description’ of document Fixed size output for any size input Goals

Integrity: message not altered Authentication: message from X Proof of possession without revealing content now Non-repudiation

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Properties of Hash functions

Pre-image resistant

1-Way `random function’

m with H(m) = h

Collision resistant

m

m’

H(m)=

H(m’)

Practical

Efficiently computablem H(m)

m H(m)

Hard to find:

Second pre-image resistant

m

m’

H(m)=

H(m’)

m’ with H(m’) = H(m)m, m’ with H(m) = H(m’)

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Applications of Hash functions

Message DigestCheck have correct message

Password storage No reverse; how verified? Password recovery?

Message SigningSigning large message is slowSign hash of message instead

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An Example: MD5

message padding: 10..00 length

Message padded so total size is multiple of 512 bits

512 bits

HMD5IV128 128

512 bits

HMD5CVi

128 128

CVi+1

512 bits

HMD5128 128

outputY

Compression Function

64 bits

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Compression functionHMD5

RF(F)

RF(G)

RF(H)

RF(I)

CV(in)

CV(out)128

128

P1

Y (block)

P2

P3

P4

512

X

PermutationsPermutationsPermutationsPermutations Round Function(next slide)

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RF(F) For k=1 to 16 do

A B C D

A B C D

X[k]

T[k]

S[k]

FPermuted Text Block

Array of ConstantsArray of Constants

Chaining Value (CV)Chaining Value (CV)

Modular addition

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Weakness MD5

http://www.win.tue.nl/hashclash/rogue-ca/ video at e.g.

http://dewy.fem.tu-ilmenau.de/CCC/25C3/video_h264_720x576/25c3-3023-en-making_the_theoretical_possible.mp4

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Message Authentication Codes Unable to predict for unseen message Keyed; validation requires same key Authenticity and Integrity Example: Keyed-Hash; uses (symmetric) key

Hmac; masked key pre-pended before hash.

MAC

Key

Message(any length)

Generation&

Validation

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Digital Signatures `Public key version of a MAC’ Signing with a private keyDecryption of Hash of Message

Verification with public key

Decrypt(=Sign)

Digital Signature

Private KeyMessage(any length)

Encrypt

Public Key

Hash

Message(any length)

Hash?=

Generation Validation

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Digital signatures with RSA

Signing Message M:Compute hash h := H(M)Signature s := RSA_D(kA, h)

Private key Alice: kA

Public key Alice: KA

Checking Signature:Compute hash h := H(M)Check: RSA_E(KA, s) == h

Uses fact: RSA_E( KA, RSA_D(kA, x) ) = x

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Key distribution

Alice Bob

Private key

Public key

Signature

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(Wo)man-in-the-middle attack

Alice Bob

Eve

Private key

Public key

Signature

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Certificate Bob’s public key is 1234Bob is a Baker ...

Statement (e.g. Identity, Attribute) signed by principal whom believes it to be true at time of signing

and/or: assumes responsibility, liability, …

Example: X.509 - Statement links a key to attributes

Note: Revocation; Validity period – revocation certificate

EXP DATE: 29-2-2013

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Trust me I’m a doctor

Certificate based Trust Management

Trust based on formal relationships

PoFI 2010 Feb 5th 2010

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Certificate Authority CA

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validate,certify

Root CA

Intermediate CA Intermediate CA Intermediate CA

validate,certify

Intermediate CA Intermediate CA

pub key -attributes

validate,certify

pub key -attributes

pub key -attributes

Validates attributeIdentity, role, e-mail address, Web address, etc. Links them to pub key

E.g. VerisignVerification method?

(Demo Certificates and CA in browser)

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Transitive and full trust Dec12/Jan 13: Turktrust fake certificate discovery

Fake intermediate CA certificates (issued august 11)

Aug11: Hack DigiNotar confirmed Dutch Certificate Authority First hack already in June 2011 Many rogue SSL certificates (Diginotar bankrupt in September 2011)

March11: Comodo partner incidient 9 fake certificates issued (e.g. live/google/yahoo/skype/mozilla) quickly discovered and disseminated.

CA can Issue any certificate.

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Web of Trust Recall First Lab session

Validate key directly New keys signed by known keys

No centralized CAs Each user signs keys they trust User can choose degree of trust in other keys

For communication For signing other keys

Compare S/MIME – CA signed certificates

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Rule based trust management Generalizes tree of CAs

Policy rules Alice:A.r ← B

A.r ← B.r

A.r ← A.cert.r

A.r ← B.r /\ C.r

Meaning:Alice trusts Bob in role r

(Bob is certified for r)Alice trust Bob certifying r

(Bob is a CA for r)Alice trusts anyone in A.cert to certify r

(Everybody in A.cert is CA for r)Alice trusts if both Bob and Charlie trust.

Can also use multiple different roles `r’.

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Certificate, Rule Based Trust Policy: GMS.Dr may read Patient record

Rules to establish DoctorsGMS.Dr ← GMS.Department.DrGMS.Department ← RadiologyRadiology.Dr ← Alice

Alice may read the patient record

Trusted, Certified facts & Delegation

GreenMedicalService

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You can trust me, ask anyone

Reputation based Trust Management

Trust based on opinions/experiences

1.000 satisfiedcustomers and

counting.

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Reputation, Behaviour Based Trust

Policy Dr with good reputation may treat

Reputation based on Past PerformanceFeedback after interaction updates reputationE-bay, Eigentrust, pagerank, centrality measures

Estimate risk based on Reputation

Good reputation valuable Incentive for good behaviour

Fastand

QuiteGood

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TRU

ST100%

Fastand

QuiteGood

Feedback &Recommendations

Certificates

User’s Requirementsdetermine how to mix

Other sources…

Combined Trust Scores

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