An Outlook of Digital Twins in Offensive Military Cyber Operations

Maathuis, Clara

doi:10.34190/eciair.4.1.765

Cited by 7 publications

(7 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Further, it can be extended with multiple data sources and multiple clusters of effects while evaluating it using different types of military operations carried out in different domains using both real and synthetical data. In this way, this research paves the way to build explainable, responsible, and trustable intelligent solutions (Chockalingam & Maathuis, 2022;Maathuis, 2022a;Maathuis, 2022b) for supporting planning, execution, and assessment of (digitally prepared) military operations.…”

Section: Discussionmentioning

confidence: 99%

Tackling Uncertainty Through Probabilistic Modelling of Proportionality in Military Operations

Maathuis

Chockalingam

2023

eccws

View full text Add to dashboard Cite

Just as every neuron in a biological neural network is a reinforcement learning agent, thus a component of a large and advanced structure is de facto a model, the two main components forming the principle of proportionality in military operations can be seen and are as a matter of fact two different entities and models. These are collateral damage depicting the unintentional effects affecting civilians and civilian objects, and military advantage symbolizing the intentional effects contributing to achieving the military objectives defined for military operation conducted. These two entities are complex processes relying on available information, projection on time to the moment of target engagement through estimation and are strongly dependent of common-sense reasoning and decision making. As a deduction, these two components and the proportionality decision result are processes surrounded by various sources and types of uncertainty. However, the existing academic and practitioner efforts in understanding the meaning, dimensions, and implications of the proportionality principle are considering military-legal and ethical lenses, and less technical ones. Accordingly, this research calls for a movement from the existing vision of interpreting proportionality in a possibilistic way to a probabilistic way. Henceforth, this research aims to build two probabilistic Machine Learning models based on Bayesian Belief Networks for assessing proportionality in military operations. The first model embeds a binary classification approach assessing if the engagement is proportional or disproportional, and the second model that extends this perspective based on previous research to perform multi-class classification for assessing degrees of proportionality. To accomplish this objective, this research follows the Design Science Research methodology and conducts an extensive literature for building and demonstrating the model proposed. Finally, this research intends to contribute to designing and developing explainable and responsible intelligent solutions that support human-based military targeting decision-making processes involved when building and conducting military operations.

show abstract

Section: Discussionmentioning

confidence: 99%

Tackling Uncertainty Through Probabilistic Modelling of Proportionality in Military Operations

Maathuis

Chockalingam

2023

eccws

View full text Add to dashboard Cite

show abstract

“…In terms of the model development, we adapt and extend the Responsible Digital Security Behaviour model proposed by Maathuis & Chockalingam (2022a) to combat social media manipulation. Consequently, the model proposed represents to the best of our knowledge the first modelling effort in this direction while stressing the necessity of further building explainable and responsible AI-based models for tackling societal challenges (Maathuis, 2022a;Maathuis, 2022b). Consequently, the following research activities are taken:…”

Section: Methodsmentioning

confidence: 99%

Modelling Responsible Digital Security Behaviour for Countering Social Media Manipulation

Maathuis

Chockalingam

2023

ECSM

View full text Add to dashboard Cite

While the digital environment, and in particular social media, surrounds not only human’s identity and its societal functions projection, e.g., institutional and financial aspects, it also captures both individual and collective thoughts regarding former, ongoing, and future concepts, trends, and incidents placed in the physical world, in the digital environment, or in both which could impact both individual and collective consciousness, behaviour, and attitude towards different dimensions of reality. Accordingly, an initial attempt to define and model responsible digital security behaviour was made and ongoing discourses and AI-based solutions for tackling and containing social manipulation mechanisms exist in this domain. Noteworthily is that dedicated attention to understanding and modelling responsible digital security behaviour in social media for tackling and/or countering social media manipulation, e.g., disinformation and misinformation, still lacks. To this end, this research aims (i) to capture the factors influencing user behaviour towards tackling and/or countering social media manipulation, (ii) to build a Machine Learning model that assesses user’s responsibility in relation to tackling and/or countering social media manipulation mechanisms, and (iii) propose a set of socio-technical recommendations for building resilience to such mechanisms. To accomplish these research objectives, a Design Science Research methodological approach is taken by designing, developing, and evaluating the model proposed through exemplification. Finally, this research aims to enhance digital security awareness and resilience to social media manipulation of users and policy decision-makers to manage and further extend in a responsible and safe way the digital environment.

show abstract

“…AI design, development, and use which represents the technical layer that encompasses the AI life cycle phases used in a military Cyber Operation including the following core elements (Maathuis, 2022b):…”

Section: Figure1: the Hcai Triad And Frameworkmentioning

confidence: 99%

Human-Centered AI in Military Cyber Operations

Maathuis

2024

iccws

View full text Add to dashboard Cite

Military Cyber Operations are an integral part of modern warfare and national security strategies as they crossed the science fiction realm, represent a real operational battlefield, and developed into an option in military toolboxes. Seeing ongoing technological advancements that allow the creation and use of complex mechanisms and technologies, the increasing digitalization of critical infrastructure, the growing abundance of data collected, generated, and exchanged between multiple parties, and the rise of stakeholders engaging in building and/or executing military Cyber Operations together with the increased number of such operations being conducted all over the globe reflects important lessons that need to be learned: the core element of such operations are humans: they build, acquire, execute, and assess them while also being impacted entities by them, e.g., through (psychological or physical) injury or death, or damage or destructions of human infrastructure. Moreover, the key process governing all the life cycle phases of military Cyber Operations is human decision-making or humanly assisted/augmented decision-making relying on advanced intelligent methods built with AI. Nevertheless, building and conducting military Cyber Operations should be done in a legal, responsible, and effective way implying a deep understanding of the context and adversary, proper target and cyber weapon selection, development, and use, and a clear overview of potential effects produced. These represent important aspects that should be properly defined and tackled in this domain. Hence, this research aims to introduce the Human-Centred AI concept and approach in the military cyber domain to illustrate ways to prioritize human involvement and interaction, human understanding, effective decision-making, and ethical considerations when building and conducting military Cyber Operations. To this end, an extensive literature review is conducted in the military, cyber, and AI domains together with instantiation on military Cyber Operations.

show abstract

An Outlook of Digital Twins in Offensive Military Cyber Operations

Cited by 7 publications

References 26 publications

Tackling Uncertainty Through Probabilistic Modelling of Proportionality in Military Operations

Tackling Uncertainty Through Probabilistic Modelling of Proportionality in Military Operations

Modelling Responsible Digital Security Behaviour for Countering Social Media Manipulation

Human-Centered AI in Military Cyber Operations

Contact Info

Product

Resources

About