Artificial Intelligence

Mini-Drone Swarms: Their Issues and Potential in Conflict Situations


Drones are currently used for a wide range of operations, such as border surveillance, general surveillance, reconnaissance, transport, aerial photography, traffic control, earth observation, communications, broadcasting, and armed attacks.

Human Rights and Artificial Intelligence: A Universal Challenge


As artificially intelligent systems benefit citizens around the globe, there remain many ethical questions about the intrusion of AI into every aspect of our private and professional lives. This paper raises awareness of the unprecedented challenge that governments and private industry face in managing these complex systems that include regulators, markets, and special interests. 

Fitting the Artificial Intelligence Approach to Problems in DoD


Emerging and disruptive technologies, due to advances made over the last couple of decades, have become the centrepiece of Department of Defense (DoD) concerns about national security. The technologies are unique because they can both benefit and hinder the DoD from its mission. Artificial Intelligence (AI) is revered in DoD circles as one of the most important of these technologies because of its potential as an absolute ‘gamechanger’ in cybersecurity operations. In this study, the focus is on the DoD fitting the Artificial Intelligence approach to its problems in a time of limited and diminishing resources.

Adversarial Attack’s Impact on Machine Learning Model in Cyber-Physical Systems


Deficiency of correctly implemented and robust defence leaves Internet of Things devices vulnerable to cyber threats, such as adversarial attacks. A perpetrator can utilize adversarial examples when attacking Machine Learning models used in a cloud data platform service. Adversarial examples are malicious inputs to ML-models that provide erroneous model outputs while appearing to be unmodified. This kind of attack can fool the classifier and can prevent ML-models from generalizing well and from learning high-level representation; instead, the ML-model learns superficial dataset regularity. This study focuses on investigating, detecting, and preventing adversarial attacks towards a cloud data platform in the cyber-physical context.

Developing a Cyber Operations Computational Ontology


Cyber operations lack models, methodologies, and mechanisms to describe relevant data and knowledge. This problem is directly reflected when cyber operations are conducted, and their effects assessed, and it can produce dissonance and disturbance in corresponding decision-making processes and communication between different military actors.

Set Your Drones to Stun: Using Cyber-Secure Quadcopters to Disrupt Active Shooters


This paper will examine pairing the autonomous precision-flight capabilities of Micro- Unmanned Aerial Vehicles (UAVs) with the growing capability of Artificial Intelligence (specifically AI based on neuromorphic computing systems) to field cyber-secure, active-shooter response systems to counter the active-shooter threat to civilian ‘soft targets’, such as schools or train stations. This paper proposes a pilot to demonstrate the feasibility of disrupting terrorist attacks with a micro-UAV, armed with less than lethal weapons, for instance, a stun gun, where such a ‘stun-drone’ is part of an emergency-response system that is trustworthy and correctly engages only active shooters.

Journal of Information Warfare

The definitive publication for the best and latest research and analysis on information warfare, information operations, and cyber crime. Available in traditional hard copy or online.












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The definitive publication for the best and latest research and analysis on information warfare, information operations, and cyber crime. Available in traditional hard copy or online.


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