Evaluate Information Risk and Assurance to Defend Information Technology
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Cybersecurity Assurance Control Baselining for Smart Grid Communication Systems
Adegboyega Ogundokun1, Pavol Zavarsky2, Bobby Swar2 1 Scotiabank, Toronto, ON, Canada
2 Information Systems Security and Assurance, Concordia University of Edmonton, Canada [email protected]; {pavol.zavarsky, bobby.swar}@concordia.ca
Abstract—Cybersecurity assurance plays an important role in managing trust in smart grid communication systems. In this paper, cybersecurity assurance controls for smart grid communication networks and devices are delineated from the more technical functional controls to provide insights on recent innovative risk-based approaches to cybersecurity assurance in smart grid systems. The cybersecurity assurance control baselining presented in this paper is based on requirements and guidelines of the new family of IEC 62443 standards on network and systems security of industrial automation and control systems. The paper illustrates how key cybersecurity control baselining and tailoring concepts of the U.S. NIST SP 800-53 can be adopted in smart grid security architecture. The paper outlines the application of IEC 62443 standards-based security zoning and assignment of security levels to the zones in smart grid system architectures. To manage trust in the smart grid system architecture, cybersecurity assurance baselining concepts are applied per security impact levels. Selection and justification of security assurance controls presented in the paper is utilizing the approach common in Security Technical Implementation Guides (STIGs) of the U.S. Defense Information Systems Agency. As shown in the paper, enhanced granularity for managing trust both on the overall system and subsystem levels of smart grid systems can be achieved by implementation of the instructions of the CNSSI 1253 of the U.S. Committee of National Security Systems on security categorization and control selection for national security systems.
Keywords—smart grid, security zone, security level, security baseline, assurance, assurance baseline
I. INTRODUCTION Assurance on trustworthiness of smart grid systems,
subsystems and system components forms an important part of a comprehensive smart grid risk management. From cybersecurity perspective, a level of assurance on trustworthiness can be achieved by implementation of appropriate functional cybersecurity measures, with verifiable capabilities, to meet defined cybersecurity requirements and to provide a basis for trust. Though regulatory standards and guidelines define security requirements for critical infrastructure systems such as electric power smart grid systems, a knowledge gap exists regarding separation of cybersecurity assurance controls from functional cybersecurity controls, and application of the assurance controls in the trust management throughout smart grid systems’ lifecycle phases. This paper intends to contribute to mitigation of the gap. The following sections emphasize that assurance on trustworthiness
of smart grid systems is achieved by implementation of assurance controls on appropriateness of functional cybersecurity measures for addressing and preventing man- made and environmental failures and disruptions.
In cybersecurity protection of critical Industrial Automation and Control Systems (IACSs), cybersecurity capability is based on the defence-in-depth principle. For critical IACSs, the cybersecurity capability is designed and implemented to utilize mutually complementary cybersecurity measures. Example of the approach that utilizes mutually reinforcing cybersecurity measures for protection of Instrumentation and Control systems of critical infrastructure systems is described in detail in Section 4 of [1]. Regarding cybersecurity assurance, legacy- style cybersecurity assessment process utilizes evaluation of security controls in isolation, with the result of the assessment depending on whether a particular cybersecurity control satisfies predetermined requirements. Since an ineffective cybersecurity control or a group of ineffective cybersecurity controls in a defence-in-depth security architecture may not necessarily translate to inadequately protected systems, the legacy-style type of cybersecurity assessment has difficulties in revealing actual security capabilities of the protection system. Compared to the legacy-style assessment of cybersecurity measures in isolation, assessment of the overall defence-in- depth capabilities provides a more precise estimate of the assurance level on capabilities of the implemented cybersecurity controls. Assurance on the overall security capability of the set of cybersecurity controls, in addition to the assurance on the individual controls, is assumed in the following sections of this paper.
To manage risks from cybersecurity threats in industrial automation and control systems and networks, various approaches have been proposed that address both functional and assurance requirements on cybersecurity. For many critical infrastructure systems, a key source of information on cybersecurity measures to consider is the U.S. NIST SP 800-53 Rev.4 [2] which provides a catalog of recommended cybersecurity functional and assurance controls for systems of three possible impact levels. While the NIST SP 800-53 provides a valuable catalog of security controls, the NIST SP 800-82 contains guidance on tailoring the generic NIST SP 800-53 controls for industrial automation and control systems [3]. As an assurance measure, traceability matrix for cybersecurity requirements and their corresponding cybersecurity controls is commonly utilized for high-impact systems [4].
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The following sections of this paper are organized as follows. Section II provides insights on cybersecurity assurance control baselining and tailoring process for smart grid system architecture. Section III shows examples of possible cybersecurity baselining and tailoring process for sample smart grid zones, defined by considering potential business impact in terms of availability, integrity and confidentiality. Finally, Section IV concludes the paper.
II. SMART GRID CYBERSECURITY ARCHITECTURE MODELLING FOR BASELINING OF ASSURANCE CONTROLS
As stated above, cybersecurity assurance baselining and tailoring process can be viewed as an implementation of applicable recommendations of the IEC 62443 series of standards [5],[6],[7],[8],[9] on network and system security of industrial communication networks. In addition to and combined with the IEC 62443 standard recommendations, the guidelines for smart grid cybersecurity of the NISTIR 7628 Rev.1 [10] can serve as a framework for development of risk- based cyber-security strategies for protection of the smart grid. Fig. 1 shows an example of a smart grid business model. The model is adopted from [10] to illustrate categorization of key smart grid communication components into security zones and sub-zones, based on criticality and possible business impacts. Note that while examples of how to segment industrial automation and control system architecture into secure zones are described, for example, in [11], the recommendations on how to determine and allocate relevant cybersecurity requirements to each zone are in the IEC 62443 series of standards. The smart grid business model in Fig. 1 resembles the DBSy InfoSec Business model [12] and shows seven major business domains of the smart grid system architecture. The major domains are grouped into internal and external zones based on relevant cybersecurity requirements.
Regarding cybersecurity modeling, most of the existing cybersecurity modelling approaches, such as the one in [13], assume that system security vulnerabilities to be addressed are known, leading to a false sense of security in case of presence of unknown vulnerabilities. Therefore, to ensure that cybersecurity assurance baselining and tailoring process considers both known and unknown system vulnerabilities, the Domain Based Security (DBSy) modeling methodology [12] of the U.K. HMG IA Standard No. 1 [14] was utilized. Fig. 2 shows an example of the DBSy InfoSec architecture model of the smart grid business model of Fig. 1. The DBSy model in Fig.2 shows high-level conduits between the smart grid business domains and examples of relevant security impact classifications assigned to each of the domains. The internal zones depicted in Fig. 2 include high availability power generation, transmission and distribution systems with certain operational systems included. In cybersecurity risk management, the industrial automation and control systems of the smart grid generally prioritize availability and integrity requirements over the requirements on confidentiality. On the other hand, the external zones and business domains that include smart grid system end users and service providers, with the advanced metering infra-structure networks, consider confidentiality and privacy protection legal requirements as important as requirements on availability and integrity.
The internal and external zones shown in Fig. 1 and Fig. 2 are further divided into sub-zones based on the impact classification summarized in Table I. These sub-zones represent logical grouping of system components from various smart grid domains that have similar levels of criticality to the business and share conduits requiring similar level of protection. For each sub-zone, relevant assurance controls from the NIST SP 800-53 Rev. 4 catalog of controls [2] are linked to the smart grid cybersecurity functional requirements specified in NISTIR 7628 [10].
Fig. 1. A possible smart grid business model with identified internal and external business domains (Adopted from the smart grid model of NISTIR 7628 [10])
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An example of Domain Based Security (DBSy) InfoSec architecture model for the smart grid business model shown in Fig.1
Information security pillars (integrity, availability and confidentiality) have differing prioritization levels for each sub-zone, effectively determining the initial baseline control selection. Utilizing the 3-by-3 matrix approach of the U.S. Committee on National Security Systems Instruction CNSSI 1253 [15] for assigning one of the three possible severity levels - low, medium or high - the identified baseline assurance controls can be defined for addressing possible impacts on the smart grid system availability, integrity and availability.
III. BASELINING OF CYBERSECURITY ASSURANCE CONTROLS FOR SMART GRID SECURITY ZONES
The requirements of the IEC 62443-2-1 [5] on Industrial Automation and Control Systems (IACS) security management system assist in identifying baseline cybersecurity requirements for smart grid systems and in selection of initial baseline security controls. Categorization of the smart grid assets into security zones based on business priority and identification of required baseline controls for information assets in each zone is performed in accordance with the requirements and guidelines of the IEC 62443-3-2 and IEC 62443-3-3 on security levels for zones and conduits [7], [8].
The conduit categories identified in Table I are described in Table II.
Using the approach common in Security Technical Implementation Guides (STIGs) of the U.S. Defense Information Systems Agency [16], justifications for the selected assurance controls on cybersecurity functional controls listed in the Table III below are as follows.
A. Audit and Accountability (AU) assurance control Assurance Control ID and Title: AU-10 Non-Repudiation
Summary: Key smart grid information systems should be configured such that actions or changes made to system components can be directly linked to the individual(s) that made the changes.
Vulnerability Discussion: If non-repudiation controls are not in place, individuals that perpetuate malicious or accidental acts of compromise may later deny these acts with no way to prove their accountability otherwise.
Applicability: High Impact Systems
TABLE I. EXAMPLES OF SMART GRID SECURITY SUB-ZONES AND IMPACT LEVELS
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TABLE II. POSSIBLE DESCRIPTIONS OF SMART GRID CONDUIT CATEGORIES
B. Audit and Accountability (AU) assurance control Assurance Control ID and Title: AU-10 Non-Repudiation
Summary: Key smart grid information systems should be configured such that actions or changes made to system components can be directly linked to the individual(s) that made the changes.
Vulnerability Discussion: If non-repudiation controls are not in place, individuals that perpetuate malicious or accidental acts of compromise may later deny these acts with no way to prove their accountability otherwise.
Applicability: High Impact Systems
C. Identification and Authentication (IA) assurance control Assurance Control ID and Title: IA-1 Identification and Authentication Policy and Procedures
Summary: Smart grid policies should specifically address the unique properties and requirements of both industrial IACS and non-IACS systems.
Vulnerability Discussion: If the IACS policy and procedures do not consider unique properties and requirements of IACS and non-IACS subsystems of the smart grid system, personnel responsible for implementing the policy requirements on the systems may be unclear as to how to effectively perform the implementation, ultimately leading to ineffective cybersecurity controls on the system
Applicability: Low, Moderate and High Impact Systems
D. System and Communications Protection (SC) assurance controls
Assurance Control ID and Title: SC-3 Security Function Isolation
Summary: Design of smart grid IACS communication components should consider separation of security from non- security functions using smart grid domain isolation boundaries.
Vulnerability Discussion: The absence of security function isolation in IACS may result in uncontrolled access to and possible compromise of integrity of key system components that perform these security functions. If exceptions are required such as if the security enhancements create safety and availability risks, compensating controls such as more comprehensive auditing activities, network connectivity limitations and architectural allocation may be considered.
Applicability: High Impact Systems
Assurance Control ID and Title: SC-7(18) Boundary Protection | Fail Secure
Summary: Smart grid communication systems should be configured to fail securely if a boundary protection device located at a managed interface, such as routers, firewalls and application gateways, fails to operate as intended.
TABLE III. EXAMPLE OF BASELINING OF ASSURANCE CONTROLS FOR SMART GRID SYSTEMS WITH POSSIBLE HIGH IMPACTS OF CYBERSECURITY INCIDENTS ON SYSTEMS’ AVAILABILITY AND INTEGRITY (SEE ZONES A, B, C IN TABLE I). NOTE: THE IDS OF REQUIREMENTS AND ASSURANCE CONTROLS IN THE TABLE
CORRESPOND TO THE NOTATION USED IN THE NISTIR 7628 [10]
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Vulnerability Discussion: If boundary protection devices fail into unsecure states, then it is possible for unauthorized external information to enter these devices and for internal information to be released without authorization.
Applicability: High Impact Systems
Assurance Control ID and Title: SC-7(21) Boundary Protection | Isolation of Information System Components
Summary: Organizations operating smart grid communication systems should implement security mechanisms that can segregate information systems per the various business functions that they perform.
Vulnerability Discussion: Lack of these protection mechanisms weakens the protection of individual smart grid IACS components and limits the effectiveness of information flow control between system components, ultimately exposing them to potential cyberattacks and errors.
Applicability: High Impact Systems
E. System and Information Integrity (SI) assurance controls Assurance Control ID and Title: SI-7(1) Software, Firmware, and Information Integrity | Integrity Checks
Summary: The smart grid systems should perform software, firmware and integrity checks during boot-up, transition states and periodically as stipulated in organizational policies.
Vulnerability Discussion: Lack of the integrity checks may result in vulnerabilities to which organizational IACS are susceptible, ultimately exposing them to potential harm.
Applicability: Moderate and High Impact Systems
Assurance Control ID and Title: SI-7(2) Software, Firmware, and Information Integrity | Automated Notifications of Integrity Violations
Summary: Automated tools such as security incident and event monitoring tools should be implemented in smart grid network environments to ensure that relevant personnel are notified if discrepancies are uncovered during integrity verification processes.
Applicability: High Impact Systems
Assurance Control ID and Title: SI-7(5) Software, Firmware, and Information Integrity | Automated Response to Integrity Violations
Summary: IACS should perform automatic shutdowns, restarts or trigger necessary safeguards as defined by the organization in the possible event that information integrity is compromised.
Vulnerability Discussion: The repercussions of not having this assurance control in place include possibility of cyber-attacks spreading to other systems with the IACS network(s) if even one system is compromised.
Applicability: High Impact Systems
Assurance Control ID and Title: SI-7(14) Software, Firmware, and Information Integrity | Binary or Machine Executable Code
Summary: Organizations responsible for smart grid operations should discourage the use of code that has limited or no warranty for which the source code has not been provided.
Vulnerability Discussion: If a vulnerability or bug exists within the code, the organization may be unable to investigate the root cause of the issue and ultimately be handicapped when trying to devise relevant countermeasures. This is more impactful if the source code vendor is not available to conduct the necessary reviews and repairs.
Applicability: High Impact Systems
Assurance Control ID and Title: SI-7(15) Software, Firmware, and Information Integrity | Code Authentication
Summary: Organizations should implement cryptographic mechanisms that require authentication of specified software components prior to installation.
Vulnerability Discussion: Absence of cryptographic authentication mechanisms such as digital signing of software and firmware components may impede ability of information systems to prevent intrusion from malicious code.
Applicability: High Impact Systems
Assurance Control ID and Title: SI-7(16) Software, Firmware, and Information Integrity | Time Limit on Process Execution without Supervision
Summary: Key smart grid communication processes should be supervised in accordance with organization's security policy.
Vulnerability Discussion: If supervision of key processes is not regularly conducted, it may result in oversight if an anomaly occurs, such as when normal execution times are exceeded.
Applicability: High Impact Systems
Results of cybersecurity assurance control baselining and tailoring process illustrated in Table III indicate that certain cybersecurity assurance controls can address more than one cybersecurity functional control for smart grid communication networks and systems.
Instruction of the Committee on National Security Systems CNSSI 1253 titled “Security Categorization and Control Selection for National Security Systems” [12] provides security control template of a 3-by-3 matrix for tailoring of selected baselines to smart grid zones [12]. The 3-by-3 matrix contains three levels of impact (low, moderate and high) for the three major aspects of information security (confidentiality, integrity and availability). Compared to the standard categorization of information systems based on the U.S. FIPS 199 [17], the 3-by- 3 matrix approach facilitates an enhanced level of granularity of assurance controls for acceptable assurance levels of protection of availability, integrity and confidentiality of smart grid systems against man-made and environmental threats. For industrial automation and control systems, impacts of possible cybersecurity incidents on availability and integrity are in general higher than impacts on confidentiality. Table IV shows an example of assurance controls that correspond to cybersecurity functional requirements for high impact smart grid systems identified in Table III.
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TABLE IV. EXAMPLE OF ASSURANCE CONTROLS SELECTED FOR SMART GRID SYSTEMS WITH POSSIBLE HIGH IMPACTS OF CYBERSECURITY INCIDENTS ON SYSTEMS’ AVAILABILITY AND INTEGRITY AND LOW IMPACTS ON CONFIDENTIALITY
IV. CONCLUSION While functional cybersecurity controls for industrial
automation and control systems are relatively well understood, this paper provides a practical guidance on cybersecurity assurance on functional security controls for protection of smart grid communication systems. The assurance controls, if properly designed and implemented, contribute to overall trustworthiness of smart grid systems. The new family of IEC 62443 standards on security of industrial automation and controls systems, NIST SP 800-82 guidelines on industrial control systems security and NISTIR 7628 guidelines for smart grid security were utilized to categorize key smart grid communication systems per severity and business impact levels. The model of the IEC 62443 series of cybersecurity standards that utilize the concept of security zones and conduits, similar to the Domain Based Security (DBSy) modeling and modeling of the U.K. HMG IS1 standard, assists in addressing communications network security threats in smart grid systems. The smart grid communication system categorization was used in conjunction with industry standard guidelines of the NIST SP 800-53 Rev 4, CNSS Instruction 1253, NUREG/CR-7141 and HMG IA 1 to conduct an initial cybersecurity assurance baseline control selection as well as specific tailoring per smart grid communication system category. Using the approach, security zones and their corresponding security levels can be identified based on the potential impact of compromise of the considered system. For justification of the assurance controls for the cybersecurity functional controls of the smart grid systems, the approach common in Security Technical Implementation Guides (STIGs) of the U.S. Defense Information Systems Agency was utilized. The insights provided in the paper are intended to assist cybersecurity assurance professionals in delineating functional cybersecurity controls from corresponding assurance controls in managing trust in smart grid system architecture.
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