Nuggets tagged risk - [remove filter]

Jan. 6, 2016 (1 year, 7 months ago)

P2CySeMoL: Predictive, Probabilistic Cyber Security Modelling Language

This paper presents an attack graph tool that can be used to estimate the cyber security of enterprise architectures. The principal current approach for this purpose uses attack graphs; applying formal reasoning and graphical modelling to present possible attack paths corresponding to a certain architecture. According to a recent survey there are more than 30 different types of attack graph approaches but there are still many important aspects that current approaches do not manage. P2CySeMoL includes theory on how attacks and defences relate quantitatively; users model their assets and how these are connected in order to enable calculations. It has been validated on both a component level and a system level using literature, domain experts, surveys, observations, experiments and case studies.

March 13, 2014 (3 years, 5 months ago)

A data-reachability model for elucidating privacy and security risks related to the use of online social networks

Personal and private data extracted piecemeal from diverse datasets can be linked and correlated to infer a more complete set of persoanl information about an individual. This obviousl is s threat to privacy in the current environment where many snippets of personal information are left as a trail inout internet behaviours or through our 'real-world' lives. Even anonymous data can be de-anonymised in this way. In order to successfully control the release of personal information in a way that maintains privacy it would be valuable to know the risks of privacy exposure when additional snippets of information are released. This work aims to assess the worst case risk of all potential data extraction attacks so as to give an indication to social media users of privacy risks and allow them to take sensible precautions with their personal data.

July 24, 2011 (6 years ago)

Predicting political hotspots: global model forecasts civil unrest

The model, named the Predictive Societal Indicators of Radicalism Model of Domestic Political Violence Forecast, predicts which countries will likely experience an escalation in domestic political violence against their governments within the next five years. It was developed at Kansas State University for Milcord, an Open Innovation company that builds knowledge management solutions for federal agencies. To date the model has apparently successfully predicted civil unrest in Peru, Ireland, Ecuador, Italy and most recently, Tunisia. Iran is currently at the top of the list.