14,073 research outputs found
Autonomic computing architecture for SCADA cyber security
Cognitive computing relates to intelligent computing platforms that are based on the disciplines of artificial intelligence, machine learning, and other innovative technologies. These technologies can be used to design systems that mimic the human brain to learn about their environment and can autonomously predict an impending anomalous situation. IBM first used the term ‘Autonomic Computing’ in 2001 to combat the looming complexity crisis (Ganek and Corbi, 2003). The concept has been inspired by the human biological autonomic system. An autonomic system is self-healing, self-regulating, self-optimising and self-protecting (Ganek and Corbi, 2003). Therefore, the system should be able to protect itself against both malicious attacks and unintended mistakes by the operator
Developing Experimental Models for NASA Missions with ASSL
NASA's new age of space exploration augurs great promise for deep space
exploration missions whereby spacecraft should be independent, autonomous, and
smart. Nowadays NASA increasingly relies on the concepts of autonomic
computing, exploiting these to increase the survivability of remote missions,
particularly when human tending is not feasible. Autonomic computing has been
recognized as a promising approach to the development of self-managing
spacecraft systems that employ onboard intelligence and rely less on control
links. The Autonomic System Specification Language (ASSL) is a framework for
formally specifying and generating autonomic systems. As part of long-term
research targeted at the development of models for space exploration missions
that rely on principles of autonomic computing, we have employed ASSL to
develop formal models and generate functional prototypes for NASA missions.
This helps to validate features and perform experiments through simulation.
Here, we discuss our work on developing such missions with ASSL.Comment: 7 pages, 4 figures, Workshop on Formal Methods for Aerospace (FMA'09
Autonomic computing meets SCADA security
© 2017 IEEE. National assets such as transportation networks, large manufacturing, business and health facilities, power generation, and distribution networks are critical infrastructures. The cyber threats to these infrastructures have increasingly become more sophisticated, extensive and numerous. Cyber security conventional measures have proved useful in the past but increasing sophistication of attacks dictates the need for newer measures. The autonomic computing paradigm mimics the autonomic nervous system and is promising to meet the latest challenges in the cyber threat landscape. This paper provides a brief review of autonomic computing applications for SCADA systems and proposes architecture for cyber security
Autonomous Fault Detection in Self-Healing Systems using Restricted Boltzmann Machines
Autonomously detecting and recovering from faults is one approach for
reducing the operational complexity and costs associated with managing
computing environments. We present a novel methodology for autonomously
generating investigation leads that help identify systems faults, and extends
our previous work in this area by leveraging Restricted Boltzmann Machines
(RBMs) and contrastive divergence learning to analyse changes in historical
feature data. This allows us to heuristically identify the root cause of a
fault, and demonstrate an improvement to the state of the art by showing
feature data can be predicted heuristically beyond a single instance to include
entire sequences of information.Comment: Published and presented in the 11th IEEE International Conference and
Workshops on Engineering of Autonomic and Autonomous Systems (EASe 2014
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