Key establishment (see Definition 1) is part of key management (see Definition 2).

Simply speaking, key management is a set of processes and mechanisms which support key establishment and the maintenance of ongoing keying relationships between parties, including replacing older keys with new keys as necessary [MvV96, Definition 1.64]; see Fig. 1.

Key establishment can be broadly classified into key agreement (see Definition 3) and key transport (see Definition 4).

Key agreement is more popular than key transport, and the de facto standard key agreement protocol is Diffie-Hellman key agreement.

CCSDS has adopted the Licklider Transmission Protocol (LTP) as specified in the IETF RFC 5326 [BFR08b] and the associated security extensions specified in IETF RFC 5327 [BFR08a] to provide reliability and authentication mechanisms on top of an underlying (usually data link) communication service [CCS15b, Sec. 1.1].

Watch the presentation given by one of the discoverers of Meltdown attacks at the 27th USENIX Security Symposium:

Since FLUSH+RELOAD was mentioned, watch the original presentation at USENIX Security ’14:

More information on the Meltdown and Spectre website.

The field of adversarial machine learning (AML) is concerned with the study of attacks on machine learning (ML) algorithms and the design of robust ML algorithms to defend against these attacks [TBH+19, Sec. 1].

ML systems (and by extension AI systems) can fail in many ways, some more obvious than the others.

AML is not about ML systems failing when they make wrong inferences; it is about ML systems being tricked into making wrong inferences.

Consider three basic attack scenarios on ML systems:

In response to the threats of AML, in 2020, MITRE and Microsoft, released the Adversarial ML Threat Matrix in collaboration with Bosch, IBM, NVIDIA, Airbus, University of Toronto, etc.

Subsequently, in 2021, more organisations joined MITRE and Microsoft to release Version 2.0, and renamed the matrix to MITRE ATLAS (Adversarial Threat Landscape for Artificial-Intelligence Systems).

MITRE ATLAS is a knowledge base — modelled after MITRE ATT&CK — of adversary tactics, techniques, and case studies for ML systems based on real-world observations, demonstrations from ML red teams and security groups, and the state of the possible from academic research.

Watch MITRE’s presentation:

References

[Eid21]	B. Eidson, MITRE ATLAS Takes on AI System Theft, MITRE News & Insights, June 2021. Available at https://www.mitre.org/news-insights/impact-story/mitre-atlas-takes-ai-system-theft.
[OV23]	A. Oprea and A. Vassilev, Adversarial machine learning: A taxonomy and terminology of attacks and mitigations, NIST AI 100-2e2023 ipd, March 2023. https://doi.org/10.6028/NIST.AI.100-2e2023.ipd.
[Tab23]	E. Tabassi, Artificial Intelligence Risk Management Framework (AI RMF 1.0), NIST AI 100-1, January 2023. https://doi.org/10.6028/NIST.AI.100-1.
[TBH+19]	E. Tabassi, K. Burns, M. Hadjimichael, A. Molina-Markham, and J. Sexton, A Taxonomy and Terminology of Adversarial Machine Learning, Tech. report, 2019. https://doi.org/10.6028/NIST.IR.8269-draft.

Among the tools that support the ATT&CK framework is MITRE CALDERA™ (source code on GitHub).

• CALDERA is a cyber security platform built on the ATT&CK framework for 1️⃣ automating adversary emulation, 2️⃣ assisting manual red-teaming, and 3️⃣ automating incident response.
• CALDERA consists of two components:
  1. The core system: This includes an asynchronous command-and-control (C2) server with a RESTful API.
  2. Plugins: These are repositories that expand the core framework capabilities. Examples include Pathfinder, a plugin for automating ingestion of network scanning tool output.

A (blurry) demo is available on YouTube:

MITRE’s Common Attack Pattern Enumeration and Classification (CAPEC™) effort provides a publicly available catalogue of common attack patterns to help users understand how adversaries exploit weaknesses in applications and other cyber-enabled capabilities.

Attack patterns are descriptions of the common attributes and approaches employed by adversaries to exploit known weaknesses in cyber-enabled capabilities.

• Attack patterns define the challenges that an adversary may face and how they go about solving it.
• They derive from the concept of design patterns applied in a destructive rather than constructive context and are generated from in-depth analysis of specific real-world exploit examples.
• In contrast to CAPEC, MITRE ATT&CK catalogues individual techniques (more fine-grained) rather than patterns (collection of sequences of techniques).

As of writing, CAPEC stands at version 3.9 and contains 559 attack patterns.

For example, CAPEC-98 is phishing:

CAPEC-98 can be mapped to CWE-451 “User Interface (UI) Misrepresentation of Critical Information”.

MITRE D3FEND is a knowledge base — more precisely a knowledge graph — of cybersecurity countermeasures/techniques, created with the primary goal of helping standardise the vocabulary used to describe defensive cybersecurity functions/technologies.

• It serves as a catalogue of defensive cybersecurity techniques and their relationships to offensive/adversarial techniques.

The D3FEND knowledge graph was designed to map MITRE ATT&CK techniques (or sub-techniques) through digital artefacts to defensive techniques; see Fig. 1.

• Any digital trail left by an adversary, such as Internet search, software exploit and phishing email, is a digital artefact [KS21, Sec. IVE].

Operationally speaking, the D3FEND knowledge graph allows looking up of defence techniques against specific MITRE ATT&CK techniques.

• For example, looking up Data Obfuscation (T1001) returns this knowledge graph.

Watch an overview of the D3FEND knowledge graph from MITRE on YouTube:

MITRE Engage (previously MITRE Shield) is a framework for planning and discussing adversary engagement operations.

• It is meant to empower defenders to engage their adversaries and achieve their cybersecurity goals.

Cyber defense has traditionally focussed on applying defence-in-depth to deny adversaries’ access to an organisation’s critical cyber assets.

Increasingly, actively engaging adversaries proves to be more effective defence [MIT22b].

• For example, making adversaries doubt the value of any data/information they stole drives down the value of their operations and up their operating cost.

While MITRE Engage has not been around for long, the practice of cyber deception has a long history; honeypots for example can be traced back to the 1990s [Spi04, Ch. 3].

MITRE Engage prescribes the 10-Step Process, which was adapted from the process of deception in [RW13, Ch. 19], in Fig. 1:

Operationalise the Methodologies

The foundation of an adversary engagement strategy is the Engage Matrix:

The Matrix serves a shared reference that bridges the gap between defenders and decision makers when discussing and planning denial, deception, and adversary engagement activities.

The Matrix allows us to apply the theoretical 10-Step Process (see Fig. 1) to an actual operation.

The top row identifies the goals: Prepare and Understand, as well as the objectives: Expose, Affect and Elicit.

• The Prepare and Understand Goals focus on the inputs and outputs of an operation.
• While the Matrix is linear like the 10-Step Process, it should be viewed as cyclical.

The second row identifies the approaches, which let us make progress towards our selected goal.

The remainder of the Matrix identifies the activities.

• The same activities often appear under one or more approach or goal/objective, e.g., Lures under Expose ▶ Detect, Affect ▶ Direct and Affect ▶ Disrupt, because activities can be adapted to fit multiple use cases.
• An adversary’s action may expose an unintended weakness of the adversary.
• We can look at each MITRE ATT&CK® technique to examine the weaknesses revealed and identify engagement activities to exploit these weaknesses.
• Fig. 3 shows an example of mapping a MITRE ATT&CK technique to an engagement activity.

Model checking is a method for formally verifying that a model satisfies a specified property [vJ11, p. 1255].

Model checking algorithms typically entail enumerating the program state space to determine if the desired properties hold.

The National Institute of Standards and Technology (NIST) has an essential role in identifying and developing cybersecurity risk frameworks for voluntary use by owners and operators of critical infrastructure (see Definition 1) [NIS18, Executive Summary].

Framework Core

This is a set of cybersecurity activities, desired outcomes and applicable references (industry standards, guidelines and practices) that are common across critical infrastructure sectors [NIS18, Sec. 1.1].

The Framework Core consists of five concurrent and continuous Functions that provide a high-level strategic view of the lifecycle of an organisation’s management of cybersecurity risks:

1. Identify: Develop an organisational understanding to manage cybersecurity risks to systems, people, assets, data and capabilities [NIS18, p. 7].

   Applicable activities include [MMQT21]:

   • identifying critical enterprise processes and assets;
   • documenting information flows (how information is collected, stored, updated and used);
   • maintaining hardware and software inventories;
   • establishing cybersecurity policies specifying roles, responsibilities and procedures in integration with enterprise risk considerations;
   • identifying and assessing vulnerabilities and threats;
   • identifying, prioritising, executing and tracking risk responses.

2. Protect: Develop and implement appropriate safeguards to ensure delivery of critical services [NIS18, p. 7].

   Applicable activities include [MMQT21]:

   • managing access to assets and information;
   • safeguarding sensitive data, including applying authenticated encryption and deleting data that are no longer needed;
   • making regular backups and storing backups offline;
   • deploying firewalls and other security products, with configuration management, to protect devices;
   • keeping device firmware and software updated, while regularly scanning for vulnerabilities;
   • training and regularly retraining users to maintain cybersecurity hygiene.

3. Detect: Develop and implement appropriate activities to identify the occurrence of a cybersecurity event [NIS18, p. 7].

   Applicable activities include [MMQT21]:

   • developing, testing and updating processes and procedures for detecting unauthorised entities and actions in the cyber and physical environments;
   • maintaining logs and monitoring them for anomalies, including unexpected changes to systems or accounts, illegitimate communication channels and data flows.

4. Respond: Develop and implement appropriate activities to take action regarding a detected cybersecurity incident [NIS18, p. 8].

   Applicable activities include [MMQT21]:

   • making, testing and updating response plans, including legal reporting requirements, to ensure each personnel is aware of their responsibilities;
   • coordinating response plans and updates with all key internal and external stakeholders.

5. Recover: Develop and implement appropriate activities to maintain plans for resilience and to restore any capabilities or services that were impaired by a cybersecurity incident [NIS18, p. 8].

   Applicable activities include [MMQT21]:

   • making, testing and updating recovery plans;
   • coordinating recovery plans and updates with all key internal and external stakeholders, paying attention to what, how and when information is shared;
   • managing public relations and company reputation.

Each Function comprises Categories, and each Category comprises Subcategories, and for each Subcategory, Informative References are provided [NIS18, Sec. 2.1].

• A Category is a cybersecurity outcome closely tied to programmatic needs and particular activities.
• A Subcategory is an outcome of technical and/or management activities for supporting achievement of the outcomes in each Category.
• An Informative Reference is a specific part of a standard, guideline and practice common among critical infrastructure sectors that illustrates a method to achieve the outcomes associated with each Subcategory.

Fig. 1 shows Categories, and the Subcategories under the Category “Business Environment”, and furthermore the Informative References for each of these Subcategories.

Implementation Tiers

The four tiers in Table 1 provide context on how an organisation views cybersecurity risks and the processes in place to manage those risks [NIS18, p. 8].

Table 1: Implementation tiers [NIS18, pp. 9-11].

Tier	Risk management process	Integrated risk management program	External participation
1, Partial	Not formalised, ad hoc and reactive.	Limited cybersecurity awareness. Risk management is irregular and case-by-case.	Organisation does not engage with other entities, and lacks awareness of cyber supply chain risks.
2, Risk-informed	Formalised but not organisation-wide. Prioritisation of cybersecurity objectives and activities is directly informed by organisational risks, business requirements, or the threat environment.	Cybersecurity awareness exists at the organisational level, but risk management is not organisation-wide. Irregular risk assessment of assets.	Organisation receives information from other entities and generates some of its own, but may not share information with others. Organisation is aware of cyber supply chain risks, but does not respond formally to the risks.
3, Repeatable	Formalised and regularly updated based on the application of risk management processes to changes in business requirements and the threat landscape.	Risk management is organisation-wide. Organisation accurately and consistently monitors cybersecurity risks of assets. Organisation responds effectively and consistently to changes in risks. Cybersecurity is considered through all lines of operation.	Organisation receives information from other entities and share its original information with others. Organisation is aware of cyber supply chain risks, and usually responds formally to the risks.
4, Adaptive	Formalised and adaptable to experience and forecast. Continuously improved leveraging advanced cybersecurity technologies and practices, to respond to evolving, sophisticated threats in a timely and effective manner.	Risk management is organisation-wide. Decision making is grounded in clear understanding of the relationship between cybersecurity risks and financial risks / organisational objectives. Risk management is integral to organisational culture and is supported by continuous awareness of activities on systems and networks.	Organisation receives, generates and reviews prioritised information to inform continuous risk assessment. Organisation uses real-time information to respond formally and consistently to cyber supply chain risks.

Implementation tiers do not represent maturity levels; they are meant to support organisational decision making about how to manage cybersecurity risks.

Framework Profiles

A Framework Profile (“Profile”) is a representation of the outcomes that a particular system or organisation has selected from the Framework Categories and Subcategories [NIS18, Appendix B].

A Profile specifies the alignment of the Functions, Categories, and Subcategories with the business requirements, risk tolerance, and resources of an organisation [NIS18, Sec. 2.3].

A Profile enables organisations to establish a roadmap for reducing cybersecurity risks, that 1️⃣ is well aligned with organisational and sector goals, 2️⃣ considers legal/regulatory requirements and industry best practices, and 3️⃣ reflects risk management priorities [NIS18, Sec. 2.3].

For example,

• The NIST Interagency Report 8401 [LSB22] specifies a Profile for securing satellite ground segments.
• A Profile for securing hybrid satellite networks is currently under development.
• More examples of Profiles can be found here.

Watch a more detailed explanation of the Cybersecurity Framework presented at RSA Conference 2018: