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Identifying Risks and Assessing Vulnerabilities Analytics for Smart Grid Cybersecurity This work was funded by the Cooperative Agreement between the Masdar Institute of Science and Technology (Masdar Institute), Abu Dhabi, UAE and the Massachusetts Institute of Technology (MIT), Cambridge, MA, USA - 02/MI/MIT/CP/11/07633/GEN/G/00. Nazli Choucri Professor of Political Science Gaurav Agarwal SM - Engineering and Management ’10 Boston Global Citizenship Forum

Analytics for Smart Grid Cyber security

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Identifying Risks and Assessing Vulnerabilities

Analytics for Smart Grid Cybersecurity

This work was funded by the Cooperative Agreement between the Masdar Institute of Science and Technology (Masdar Institute), Abu Dhabi, UAE

and the Massachusetts Institute of Technology (MIT), Cambridge, MA, USA - 02/MI/MIT/CP/11/07633/GEN/G/00.

Nazli Choucri

Professor of Political Science

Gaurav Agarwal

SM - Engineering and Management ’10

Boston Global Citizenship Forum

Page 2

Source: United States Government Accountability Office, “Electricity grid

modernization, GAO-11-117, January 2011.

Analytics for Smart Grid Cybersecurity: Identifying Risks and Assessing Vulnerabilities

N Choucri and G Agarwal, September 22

Smart Grid of Power Systems

Highlights of Smart Grid Cybersecurity Risk Management Practice

Enterprise Risk

Management Practice

Cybersecurity Risk

Management Practice

Other Risk

Management Practice

NIST Supply Chain RMP

DoE RMP

Compliance to Technical

Standards

Compliance to Federal

Regulations

Implementation of

Capability Maturity Models

DoE C2M2 Guide

DoE C2M2

NIST Cybersecurity

Framework

White House Executive

Order: 13636

NIST 7628 Guidelines

NIST 800:53

NIST 1108R3

CIM/61850 for DGM

SGIP Framework

mapping to Guidelines

US CERT Cyber Resilience Review

ICS CERT Cyber Security Evaluation Tool

Primary Documents

Supporting

Documents

Other Documents

Focus on

Smart Grid

Advancing Cybersecurity and Sustainability for Critical Infrastructure: Ecosystem

of Cybersecurity Risk Management Practices – Situating NIST Initiatives and

Expanding Capabilities. • April 17, 2016

Page 3

Smart Grid Cyber

Security Focus

RMP stands for Risk Management Practice

Page 4

Smart Grid Elements – in numbers

Domains : 7

Actors (Nodes) : 47

Logical Interfaces (Edges) : 130

Security Requirements Types: 180

Vulnerabilities Classes: 53

Spatial distance between nodes is importance and

distance to other nodes.

Node represents an actor.

Node color based on domain.

Node size based on eigenvector centrality of node in the network.

Edge represents a logical interface (or connection) between two actors.

Interface strength – illustrated by thickness of connection

Impact scale and scope, defined in system-wide terms – represented by edge color.

Network View of NIST Guidelines from Design Structure Matrix (DSM)

Analytics for Smart Grid Cybersecurity: Identifying Risks and Assessing Vulnerabilities

N Choucri and G Agarwal September 22, 2016

Page 5

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Impact Levels

Analytics for Smart Grid Cybersecurity: Identifying Risks and Assessing Vulnerabilities •

N Choucri and G Agarwal, September 22,, 2016

These images: (1) provide greater transparency, (2) identify high threat areas,

(3) support selection of priority actions, and (4) help align resources to goals

Risk Identification and Assessment based on NIST Guidelines 7628 R1