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ITS a BeAR: IT Security for Berkeley Academic Resources Masters Project Presentation iSchool, UC Berkeley May 15th, 2008 Project Team Matt Chew Spence Bindiya Jadhwani Lawan Likitpunpisit Meghalim Sarma Project Advisor Eric Kansa
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ITS a BeAR: IT Security for Berkeley Academic Resources Masters Project Presentation iSchool, UC Berkeley May 15th, 2008 Project Team Matt Chew Spence.

Dec 20, 2015

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Page 1: ITS a BeAR: IT Security for Berkeley Academic Resources Masters Project Presentation iSchool, UC Berkeley May 15th, 2008 Project Team Matt Chew Spence.

ITS a BeAR:IT Security for Berkeley Academic Resources

Masters Project PresentationiSchool, UC Berkeley

May 15th, 2008Project Team

Matt Chew SpenceBindiya Jadhwani

Lawan LikitpunpisitMeghalim Sarma

Project AdvisorEric Kansa

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Agenda Problem Statement Project Background Needs Analysis ITS-a-BeAR: Security Plan Generator System System Walk Through Project Impact Future Work and Recommendations

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Our Clients and Key Stakeholders UC Berkeley Information Services & Technology (IST)

Bill Allison, Senior Manager Chair of the Campus Information Security and Privacy

Committee

Karen Eft, IT Policy ManagerWith advice from:

Chris Hoofnagle, Senior Staff Attorney Samuelson Law, Technology & Public Policy Clinic

Ryan Means, Chief Technical Officer UC Berkeley School of Law

Vice-Chair of the Campus Information Security and Privacy Committee

Jeremy Lapidus, Principal Auditor UC Berkeley Audit & Advisory Services

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Mark Deely – Researcher with Sensitive Data

51 years old, Married with 2 kids

Senior researcher, Anthropology

Work Focus: Studies Latin American ethnography Work based on observations of

people Uses his laptop to store all research

data

Collects and stores personal information

Encrypts data but wonders if that is enough

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Jing Wu – Administrator Managing IT system 33 years old, Single Director of computing

services, Anthropology Responsibilities :

In charge of technical support

Security of department system

Overburdened due to lack of resources for security compliance

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Problem Statement Need to protect sensitive

data at the university Difficulty due to

decentralized nature of campus

Must interpret multiple policies No single catalog of

requirements Limited guidance for

security compliance

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Project Background Information is the

lifeblood Current computers and

networks inherently insecure

Number of laws and policies that should be followed FERPA, HIPAA, GLBA,

SB1386, etc. Enforcement on campus is

effectively voluntary

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Needs Analysis CIO has limited visibility

into true state of campus compliance

Guidance to campus units is not readily available Mandates spread across UC and

campus policies No single list of recommended

practices that meet security requirements

Not easy for technical staff to justify need for controls

No Security Plan Template

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What are Controls? Things you have to do to

protect a system Implemented at various levels  Controls are context

dependent Policy-based controls Risk-based controls Platform-specific-based controls

Policies describe controls at a high level Concrete steps up to the

interpretation of the reader

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Data Classification Overview

We care about :“Restricted, Essential, and Data of

Record”

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Data Classification (Cont.) Restricted Data:

Anything protected by law, policy, or contract Personal Identifiable

Information!

Essential System: Failure to function causes a major failure to university services.

Data of Record: Authoritative copy of data

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The Shift towards Risk-based Analysis Restricted Data Essential Data Data of Record

Existing Classification

Risk-based Classification

LowMedium

High

RestrictedConfidentiality

Data of Record

Integrity

EssentialAvailability

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Roles Administrative Officials

Unit heads, deans, etc Data Proprietors

Data owner Data Custodians

Everyone with privileged access to the system Data Users

People with access to data within an information system

Mark Deely

Jing Wu

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IT Security Control Catalog

Various Policies UC-Wide Campus-Wide

Standards NIST SP series

Data Classification Risk Based

Controls Roles Procedures

We created a single catalog that maps:

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Security Plan Template

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ITS a BeAR! Security Plan Generator A proof-of concept 5-steps, easy-to-use

web-based system Auto generation of

appropriate controls Recommends

procedures on how to implement controls

Generates a security plan at the end

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High-Level User Interaction

Step 1 Step 2 Step 3

Basic Information Data Classification

Detail Hardware Profile

All user information captured at Step 1 – Step 4

Security Plan Generator

Extract Appropriate controls based on Data classification

Implementation choice and details

Step 4

Step 5

User

Final Security Plan

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Detailed Flow Diagram

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Walk Through – Step 1

System Name is Captured

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Step 1: Basic InformationRoles and System Contacts Identified

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Step 2: Information Sensitivity Level

Provides Definitions

Sensitivity Level is identifiedSystem Type

identified

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Step 3: Purpose of the System

User Types identified

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Step 4: List of Controls are Generated

Controls Generated

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Step 4: List of Controls are Generated

Implementation Choice

Recommended Procedures

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Step 5: Final Security Plan

Security Plan Security Plan ready to print!ready to print!

Save, Submit, Print

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Benefits Users no longer need to

interpret complex policies Guidance provided on

implementing controls Less duplication of work! Assists IT audit process Better compliance Less embarrassment and

cost to campus

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Project Impact Created common catalog for

university IT security compliance Potentially shared across all UC

campuses Re-defines the IT Security

Plan submission and approval process

Re-use of information across different organizations (CPHS and RDM)

On the way to implementation!

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Future Work Integration with Campus IT Services

Auditor Interface

Incremental Entering of Information

Customized Guidance Reports For Units

Management Reporting

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Recommendations to the CIO Office Provide Security as a Service Insert Security into Mandatory

Processes Process Improvements

Create Standard Risk Assessment Methodology

Have More Granular Data Classifications Improve Periodic Review of Controls Consolidate Security Log Auditing

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Project Feedback!

Can we share this with other UC campuses?

- Karen Eft -

Great Recommendations! Very impressive!

A clear approach and a good synthesis of available resources.

- Shel Waggener -

It’s practical. We can implement it incrementally!

- Bill Allison -

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Acknowledgements IST IT Policy Team Ryan Means Jeremy Lapidus

iSchool FacultyEric Kansa Erik WildeBob Glushko Doug Tygar

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Questions & Answers