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Full-Text Articles in Physical Sciences and Mathematics
Bringing Defensive Artificial Intelligence Capabilities To Mobile Devices, Kevin Chong, Ahmed Ibrahim
Bringing Defensive Artificial Intelligence Capabilities To Mobile Devices, Kevin Chong, Ahmed Ibrahim
Australian Information Security Management Conference
Traditional firewalls are losing their effectiveness against new and evolving threats today. Artificial intelligence (AI) driven firewalls are gaining popularity due to their ability to defend against threats that are not fully known. However, a firewall can only protect devices in the same network it is deployed in, leaving mobile devices unprotected once they leave the network. To comprehensively protect a mobile device, capabilities of an AI-driven firewall can enhance the defensive capabilities of the device. This paper proposes porting AI technologies to mobile devices for defence against today’s ever-evolving threats. A defensive AI technique providing firewall-like capability is being …
On The Spatial Modelling Of Mixed And Constrained Geospatial Data, Hassan Talebi
On The Spatial Modelling Of Mixed And Constrained Geospatial Data, Hassan Talebi
Theses: Doctorates and Masters
Spatial uncertainty modelling and prediction of a set of regionalized dependent variables from various sample spaces (e.g. continuous and categorical) is a common challenge for geoscience modellers and many geoscience applications such as evaluation of mineral resources, characterization of oil reservoirs or hydrology of groundwater. To consider the complex statistical and spatial relationships, categorical data such as rock types, soil types, alteration units, and continental crustal blocks should be modelled jointly with other continuous attributes (e.g. porosity, permeability, seismic velocity, mineral and geochemical compositions or pollutant concentration). These multivariate geospatial data normally have complex statistical and spatial relationships which should …