This paper studies the synthesis of control
policies for an agent that has to satisfy a temporal logic
specification in a partially observable environment, in
the presence of an adversary. The interaction of the
agent (defender) with the adversary is modeled as a partially
observable stochastic game. The goal is to generate
a defender policy to maximize satisfaction of a given
temporal logic specification under any adversary policy.
The search for policies is limited to the space of finite
Colonel John Boyd’s Observe/Orient/Decide/Act Loop (“OODA loop”) is a widely adopted decision-making analytical framework.
We combine the OODA loop with the NSA Methodology for Adversary Obstruction to create a new cyber‑defense model.
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Differentially Private Average Consensus: Obstructions, Trade-Offs, and Optimal Algorithm Design
This paper studies the multi-agent average consensus problem under the requirement of differential privacy of the agents’ initial states against an adversary that has access to all the messages. We first establish that a differentially private consensus algorithm cannot guarantee convergence of the agents’ states to the exact average in distribution, which in turn implies the same impossibility for other stronger notions of convergence.
Submitted by Jorge Cortes on October 13th, 2017
You are invited to participate in The Fourth International Conference On Digital Enterprise and Information Systems (DEIS2017) that will be held in Jakarta, Indonesia, on July 19 - 20, 2017. The event will be held over two days, with presentations delivered by researchers from the international community, including presentations from keynote speakers and state-of-the-art lectures.
Situational Awareness provides a user centric approach to security and privacy. The human factor is often recognised as the weakest link in security, therefore situational perception and risk awareness play a leading role in the adoption and implementation of security mechanisms. In this study we assess the understanding of security and privacy of users in possession of wearable devices. The findings demonstrate privacy complacency, as the majority of users trust the application and the wearable device manufacturer.
Submitted by xavier bellekens on November 17th, 2016