Technical background on the

“ Blueprints and Use Cases” - ICDS 2014

Dr. George Vaněček, Jr.(FICO, San Jose, CA, USA)

Deepak Vij, Ishita Majumdar, Naveen Dhar(FutureWei Technologies, Santa Clara, CA, USA)

The Eighth International Conference on Digital SocietiesICDS 2014, Barcelona Spain

Trust?

Trust is one of humanity’s most explicit and intrinsic social cognitions, yet within the digital world its mostly static, over simplified and generally not negotiable!?

Trust is the extent to which a trustor is willing to depend on something or someone (a trustee) in a given situation, even though negative consequences are possible.

! ?

The Untrustworthy Internet?

“Billions of people around the world do not trust the Internet”,

- claims European Commission vice-president Neelie Kroes.

“The future of internet was based on trust…Trust can never again be taken for granted.”

- March 2014, BBC

• 98% of Americans distrust the Internet• 56% fear on-line information is outdated• 53% feel the information is self-promotional• 45% feel unfamiliar with the sources

- Harris Interactive MRF, 2012

Human/Computer Co-evolution

People per

Com

puter

Computers Today

adapte

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rom

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Matt

ern

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50B+ interconnectedsensors, actuators, and intelligent, autonomous,and individualized devices, supported by massive cloud services.

Simple ComplexTrust

Many People per One Computer

One Computer for One Person

Many Computers for Everyone

Rising Problem for EnterprisesPeople and organizations will need to adopt a more flexible access policy to remain competitive yet open.

A company wants to enable employee and guest access from anywhere at anytime, but also meet compliance reviews and protect company data.

An employee wants access to corporate data and services anytime, anywhere (multiple employers or public sites) on any devices while protecting his/her privacy.

! !

By 2014, 80% of mobile professionals will use at least two personal devices to access corporate systems and data.

A device needs to know who and what to trust when, where, and why.

?

Internet and IoT Security Models need to adopt to new Trust Management Systems

Most of today’s security infrastructure is static and perimeter-centric with policies that are restrictive and insular.

This is no longer sufficient in an environment that is highly dynamic, multi-sourced and virtualized, and where consumer-oriented IT is increasingly used in lieu of enterprise-owed, provisioned systems.

Trust Management System Overview

A Logical Trust Network maintains entities and trust relationships between those entities

Trust values for a trustee are determined from the combined scores of a trustor’s

1. Evidence: trust values based on directly scoring of tracked evidence

2. Reputation: trust value based on indirect recommendations.

The Logical Trust Network is redundantly distributed over a topology of

1. Trust Agents: decentralized set of peers in a P2P topology

2. Trust Brokers: a centralized 3rd-party set of trust brokers

Where an entity and its adjacent relationship may appear differently in more than one agent or broker.

Current vs. Trust-based Interactions

Users

Public Devices

Personal Devices

Organizations

Service and Content Providers

Trust Relationship

TrustIndex

Inferred Trust

Relationship

Client Server

Req.

Resp.

Trust? Trustee

Req.

Truster

Logical TrustNetwork

IdP

Authentication and AuthorizationBased on Membership

Auth

?

?

yes

yes

Resp.

Auth

IdP

Today

Logical Trust Network

A digraph of nodes (i.e., entities) and directed edges (e.g., relationships), where

An entity is any person, place or thing with a distinct existence that needs to trust or be trusted by other entities.

Users

Public Devices

Personal Devices

Organizations

Service and Content Providers

Trust Relationship

TrustIndex

Inferred Trust

Relationship

Entities need not have unique identities; in their absence, their identities may be probabilistically resolved from their attributes.

Entities are contextually structured, and relationships are granularly scored…

Trust needs to differentiate an entity by its context(s) that change with time

Father

Consultant Employee

Teacher

Tourist

MotoHobbyist

Volunteer

EntityCijk

• Entity i

• Context j

• Version k

t

Entity Contexts change/are-created over Time by Events

Entity’s Current Contexts

Versioning from C000 to C001

Contextual Events CauseContext Evolution, e.g.,

Branching from C000 to C010

Describing Entities and their Contexts A context is a set of unique attributes

{(n0,v0,r0), …}An attribute is a tuple of n-name, v-value, r-unique attribute identifier,e.g., (“Name.Last”, “Smith”, “org:w3c:etc:context:…:name”) Attributes represent entities characteristics, configurations,

scenarios, locations, times, roles, etc.

Contexts are immutable. They may change or split. Their changes represent subsequent contexts in the entity’s context tree.

Entities are defined as the collection of their contexts at any given time t, e.g., e0t = (C011, C020, C030).

Situations differentiate contexts…

Situations identify Contexts

Father

ConsultantEmployee

Teacher

TouristHobbyist Volunteer

TrustorContexts

Walking in a park with daughter

Riding with a group of motorcycle club

members

Working on a patent with coworkers

Situations are represented by attribute sets

Mapping function mapssituations to contexts

Trust Relationships Connect Contexts

Edges in the Logical Trust Network represent direct trust relationships.

Indirect and derived relationships may be temporarily cached for auditing and verification but typically not persisted permanently.

Trustor contexts needs evidence (e.g., mutable performance profile) to prove trustworthiness

Trust Relationships

A trust relationship R is defined as a set of

scoring attributes

R(Ci, Cj) = {a0, …, am}

from Context Ci of Entity i to the Context Cj of

Entity j where a scoring attribute

an = (n, α, r, sn)

holds a score value 0≤α≤1 defined by a scoring

function over the jth evidence Dj

Sn(Dj) = α

An example is(“gradRatio”, 0.87, “org:shool:…:gradRatio”,

graduated/enrolled)

Ci

Cj Dj

Trustor

Trustee

R(Ci, Cj )

Closer look at the Logical Trust NetworkT

ime

Entity

Conte

xt

Now

TrustBroker

Truster

Trustee

Entity

CurrentContexts

Relationship

Evidence

Scores

Situation

ContextDetermination

Trust Belief Policy

A believe policy B is defined as a set of belief attributes qn

that reference score attributes asB = { qn | qn = (n, β) }

where n is the name of a score attribute, and β is a score threshold 0 ≤ β ≤ 1 and

∨qn c B, an c Re.g., (“GradRatio”, 0.85)

I trust until trust is broken

I distrust until trust is earned

Boolean Trust for an Explicit Relationship

Trust questions must be answered as “yes” or “no”.

Given a trust relationship R and a belief policy B, R represents trust based on direct evidence only if

Combining evidence-based trust with jth reputation, Uj, yields

Other trust determination functions can be formulated from the Logical Trust Network model…

Score

Expected score threshold

Open Problems

• Do we need a new identity ecosystem for all people, places

and things to manage trust on the Internet?

E.g., National Strategy for Trusted Identities in Cyberspace

(NSTIC) • Need algorithms to maintain and create entities’ contexts• How do trust brokers collect evidence?• Need tools for trustors to maintain their beliefs and

relationships.• Need to define a general and extensible taxonomy for attribute

names?• How do we define and share scoring functions?• How do we secure the Logical Trust Network?• How do we protect entity’s privacy while allowing sharing?

Summary

I. A generalized trust management system is needed to

address current aging security and privacy issues.

II. The evolution of IT into ICT and hybrid enterprise/public

services needs trust.

III. The digital world can no longer ignore trust.

IV. Its time for the computer science and security

communities to formalize and deploy a trust system in the

future Internet.

Thank youGeorgeVanecek@fico.com