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

On the Minimization of Handover Decision Instability in Wireless Local Area Networks

This paper addresses handover decision instability which impacts negatively on both user perception and network performances. To this aim, a new technique called The HandOver Decision STAbility Technique (HODSTAT) is proposed for horizontal handover in Wireless Local Area Networks (WLAN) based on IEEE 802.11standard. HODSTAT is based on a hysteresis margin analysis that, combined with a utilitybased function, evaluates the need for the handover and determines if the handover is needed or avoided. Indeed, if a Mobile Terminal (MT) only transiently hands over to a better network, the gain from using this new network may be diminished by the handover overhead and short usage duration. The approach that we adopt throughout this article aims at reducing the minimum handover occurrence that leads to the interruption of network connectivity (this is due to the nature of handover in WLAN which is a break before make which causes additional delay and packet loss). To this end, MT rather performs a handover only if the connectivity of the current network is threatened or if the performance of a neighboring network is really better comparing the current one with a hysteresis margin. This hysteresis should make a tradeoff between handover occurrence and the necessity to change the current network of attachment. Our extensive simulation results show that our proposed algorithm outperforms other decision stability approaches for handover decision algorithm.Comment: 13 Pages, IJWM

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

QoE-centric management of multimedia networks through cooperative control loops

The Internet has evolved from a service to transport simple text files into a platform for transporting a variety of complex multimedia services. The initial centralized management systems were not designed and are therefore not able to perform efficient management of Quality of Experience (QoE) for these complex services. Deploying an autonomic management system resolves these complexity issues and allows efficient resource allocation based on the service type, end-user requirements and device characteristics. However, existing autonomic management systems only allow limited cooperation between different autonomic elements (AE), which limits their capabilities to provide end-to-end QoE assurance. This research will therefore design cooperative AEs, optimize their organization and provide cooperative allocation algorithms to optimize end-to-end QoE

Academic Panel: Can Self-Managed Systems be trusted?

Trust can be defined as to have confidence or faith in; a form of reliance or certainty based on past experience; to allow without fear; believe; hope: expect and wish; and extend credit to. The issue of trust in computing has always been a hot topic, especially notable with the proliferation of services over the Internet, which has brought the issue of trust and security right into the ordinary home. Autonomic computing brings its own complexity to this. With systems that self-manage, the internal decision making process is less transparent and the ‘intelligence’ possibly evolving and becoming less tractable. Such systems may be used from anything from environment monitoring to looking after Granny in the home and thus the issue of trust is imperative. To this end, we have organised this panel to examine some of the key aspects of trust. The first section discusses the issues of self-management when applied across organizational boundaries. The second section explores predictability in self-managed systems. The third part examines how trust is manifest in electronic service communities. The final discussion demonstrates how trust can be integrated into an autonomic system as the core intelligence with which to base adaptivity choices upon

MIPv6 Experimental Evaluation using Overlay Networks

The commercial deployment of Mobile IPv6 has been hastened by the concepts of Integrated Wireless Networks and Overlay Networks, which are present in the notion of the forthcoming generation of wireless communications. Individual wireless access networks show limitations that can be overcome through the integration of different technologies into a single unified platform (i.e., 4G systems). This paper summarises practical experiments performed to evaluate the impact of inter-networking (i.e. vertical handovers) on the Network and Transport layers. Based on our observations, we propose and evaluate a number of inter-technology handover optimisation techniques, e.g., Router Advertisements frequency values, Binding Update simulcasting, Router Advertisement caching, and Soft Handovers. The paper concludes with the description of a policy-based mobility support middleware (PROTON) that hides 4G networking complexities from mobile users, provides informed handover-related decisions, and enables the application of different vertical handover methods and optimisations according to context.Publicad