Explainable AI methods in cyber risk management

Transparent, explainable, and accountable AI for robotics

Recent governmental statements from the United States (USA) (1, 2), the European Union (EU) (3), and China (4) identify artificial intelligence (AI) and robotics as economic and policy priorities. Despite this enthusiasm, chal lenges remain. Systems can make unfair and discriminatory decisions, replicate or develop biases, and behave in inscrutable and unexpected ways in highly sensitive enviro...

Enterprise Cyber Risk Management

Logic meets Probability: Towards Explainable AI Systems for Uncertain Worlds

Logical AI is concerned with formal languages to represent and reason with qualitative specifications; statistical AI is concerned with learning quantitative specifications from data. To combine the strengths of these two camps, there has been exciting recent progress on unifying logic and probability. We review the many guises for this union, while emphasizing the need for a formal language to...

Data Storage Management using AI Methods

Data management and monitoring is an important issue in scientific computation. Scientists want to access their data as quickly as possible. Some experiments need to store a lot of data which have to be secure. By saying this we mean that this data can not disappear or be damaged also the data storage should be as cheap as possible. In this paper we present an approach to the automation of moni...

Cyber Risk Exposure and Prospects for Cyber Insurance

This study draws attention to the ubiquitous and borderless nature of cybercrime. It examines the prospect of introducing customized cyber insurance policy in the Nigerian market. As secondary data was not available, the study conducted a survey by administering three sets of questionnaire to purposively selected top executives in four Trade Groups that rely heavily on Internet transactions for...