Mudgerikar, Anand; Bertino, Elisa; Lobo, Jorge; Verma, Dinesh(Institute of Electrical and Electronics Engineers (IEEE), 2021)
Reinforcement Learning (RL) is an effective technique for building ‘smart’ SDN controllers because of its model-free nature and ability to learn policies online without requiring extensive training data. However, as RL ...
Law, Mark; Russo, Alessandra; Bertino, Elisa; Broda, Krysia; Lobo, Jorge(Association for the Advancement of Artificial Intelligence (AAAI), 2020)
Inductive Logic Programming (ILP) systems aim to find a set of logical rules, called a hypothesis, that explain a set of examples. In cases where many such hypotheses exist, ILP systems often bias towards shorter solutions, ...
Lobo, Jorge; Bertino, Elisa; Russo, Alessandra(ACM Association for Computer Machinery, 2020)
There has been over the past decade a rapid change towards computational environments that are comprised of large and diverse sets of devices, many of them mobile, which can connect in flexible and context-dependent ways. ...
Law, Mark; Russo, Alessandra; Bertino, Elisa; Broda, Krysia; Lobo, Jorge(Association for the Advancement of Artificial Intelligence (AAAI), 2019)
In this paper we introduce an extension of context-free grammars called answer set grammars (ASGs). These grammars allow annotations on production rules, written in the language of Answer Set Programming (ASP), which can ...
We present a method for computing the best provisioning of security resources for Internet of Things (IoT) scenarios characterized by a high degree of mobility. The security infrastructure is specifed by a security resource ...
