The Role of [email protected] in Autonomic Systems:keynote

Autonomic systems manage their own behaviour in accordance with high-level goals. This paper presents a brief outline of challenges related to Autonomic Computing due to uncertainty in the operational environments, and the role that [email protected] play in meeting them. We argue that the existing progress in Autonomic Computing can be further exploited with the support of runtime models. We briefly discuss our ideas related to the need to understand the extent to which the high-level goals of the autonomic system are being satisfied to support decision-making based on runtime evidence and, the need to support self-explanation

Autonomic Parameter Tuning of Anomaly-Based IDSs: an SSH Case Study

Anomaly-based intrusion detection systems classify network traffic instances by comparing them with a model of the normal network behavior. To be effective, such systems are expected to precisely detect intrusions (high true positive rate) while limiting the number of false alarms (low false positive rate). However, there exists a natural trade-off between detecting all anomalies (at the expense of raising alarms too often), and missing anomalies (but not issuing any false alarms). The parameters of a detection system play a central role in this trade-off, since they determine how responsive the system is to an intrusion attempt. Despite the importance of properly tuning the system parameters, the literature has put little emphasis on the topic, and the task of adjusting such parameters is usually left to the expertise of the system manager or expert IT personnel. In this paper, we present an autonomic approach for tuning the parameters of anomaly-based intrusion detection systems in case of SSH traffic. We propose a procedure that aims to automatically tune the system parameters and, by doing so, to optimize the system performance. We validate our approach by testing it on a flow-based probabilistic detection system for the detection of SSH attacks

Autonomic Trust Management in Cloud-based and Highly Dynamic IoT Applications

In this paper, we propose an autonomic trust management framework for cloud based and highly dynamic Internet of Things (IoT) applications and services. IoT is creating a world where physical objects are seamlessly integrated in order to provide advanced and intelligent services for human beings in their day-to-day life style. Therefore, trust on IoT devices plays an important role in IoT based services and applications. Cloud computing has been changing the way how provides are looking into these issues. Many studies have proposed different techniques to address trust management although non of them addresses autonomic trust management in cloud based highly dynamic IoT systems. To our understanding, IoT cloud ecosystems help to solve many of these issues while enhancing robustness and scalability. On this basis, we came up with an autonomic trust management framework based on MAPE-K feedback control loop to evaluate the level of trust. Finally, we presents the results that verify the effectiveness of this framework

Achieving Autonomic Computing through the Use of Variability Models at Run-time

Increasingly, software needs to dynamically adapt its behavior at run-time in response to changing conditions in the supporting computing infrastructure and in the surrounding physical environment. Adaptability is emerging as a necessary underlying capability, particularly for highly dynamic systems such as context-aware or ubiquitous systems. By automating tasks such as installation, adaptation, or healing, Autonomic Computing envisions computing environments that evolve without the need for human intervention. Even though there is a fair amount of work on architectures and their theoretical design, Autonomic Computing was criticised as being a \hype topic" because very little of it has been implemented fully. Furthermore, given that the autonomic system must change states at runtime and that some of those states may emerge and are much less deterministic, there is a great challenge to provide new guidelines, techniques and tools to help autonomic system development. This thesis shows that building up on the central ideas of Model Driven Development (Models as rst-order citizens) and Software Product Lines (Variability Management) can play a signi cant role as we move towards implementing the key self-management properties associated with autonomic computing. The presented approach encompass systems that are capable of modifying their own behavior with respect to changes in their operating environment, by using variability models as if they were the policies that drive the system's autonomic recon guration at runtime. Under a set of recon guration commands, the components that make up the architecture dynamically cooperate to change the con guration of the architecture to a new con guration. This work also provides the implementation of a Model-Based Recon guration Engine (MoRE) to blend the above ideas. Given a context event, MoRE queries the variability models to determine how the system should evolve, and then it provides the mechanisms for modifying the system.Cetina Englada, C. (2010). Achieving Autonomic Computing through the Use of Variability Models at Run-time [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/7484Palanci

Policy-based autonomic control service

Recently, there has been a considerable interest in policy-based, goal-oriented service management and autonomic computing. Much work is still required to investigate designs and policy models and associate meta-reasoning systems for policy-based autonomic systems. In this paper we outline a proposed autonomic middleware control service used to orchestrate selfhealing of distributed applications. Policies are used to adjust the systems autonomy and define self-healing strategies to stabilize/correct a given system in the event of failures

Semantic-based policy engineering for autonomic systems

This paper presents some important directions in the use of ontology-based semantics in achieving the vision of Autonomic Communications. We examine the requirements of Autonomic Communication with a focus on the demanding needs of ubiquitous computing environments, with an emphasis on the requirements shared with Autonomic Computing. We observe that ontologies provide a strong mechanism for addressing the heterogeneity in user task requirements, managed resources, services and context. We then present two complimentary approaches that exploit ontology-based knowledge in support of autonomic communications: service-oriented models for policy engineering and dynamic semantic queries using content-based networks. The paper concludes with a discussion of the major research challenges such approaches raise

Enabling the Autonomic Management of Federated Identity Providers

The autonomic management of federated authorization infrastructures (federations) is seen as a means for improving the monitoring and use of a service provider’s resources. However, federations are comprised of independent management domains with varying scopes of control and data ownership. The focus of this paper is on the autonomic management of federated identity providers by service providers located in other domains, when the identity providers have been diagnosed as the source of abuse. In particular, we describe how an autonomic controller, external to the domain of the identity provider, exercises control over the issuing of privilege attributes. The paper presents a conceptual design and implementation of an effector for an identity provider that is capable of enabling cross-domain autonomic management. The implementation of an effector for a SimpleSAMLphp identity provider is evaluated by demonstrating how an autonomic controller, together with the effector, is capable of responding to malicious abuse

The evolutionary origins of volition

It appears to be a straightforward implication of distributed cognition principles that there is no integrated executive control system (e.g. Brooks 1991, Clark 1997). If distributed cognition is taken as a credible paradigm for cognitive science this in turn presents a challenge to volition because the concept of volition assumes integrated information processing and action control. For instance the process of forming a goal should integrate information about the available action options. If the goal is acted upon these processes should control motor behavior. If there were no executive system then it would seem that processes of action selection and performance couldn’t be functionally integrated in the right way. The apparently centralized decision and action control processes of volition would be an illusion arising from the competitive and cooperative interaction of many relatively simple cognitive systems. Here I will make a case that this conclusion is not well-founded. Prima facie it is not clear that distributed organization can achieve coherent functional activity when there are many complex interacting systems, there is high potential for interference between systems, and there is a need for focus. Resolving conflict and providing focus are key reasons why executive systems have been proposed (Baddeley 1986, Norman and Shallice 1986, Posner and Raichle 1994). This chapter develops an extended theoretical argument based on this idea, according to which selective pressures operating in the evolution of cognition favor high order control organization with a ‘highest-order’ control system that performs executive functions

A Generic Agent Organisation Framework For Autonomic Systems

Autonomic computing is being advocated as a tool for managing large, complex computing systems. Specifically, self-organisation provides a suitable approach for developing such autonomic systems by incorporating self-management and adaptation properties into large-scale distributed systems. To aid in this development, this paper details a generic problem-solving agent organisation framework that can act as a modelling and simulation platform for autonomic systems. Our framework describes a set of service-providing agents accomplishing tasks through social interactions in dynamically changing organisations. We particularly focus on the organisational structure as it can be used as the basis for the design, development and evaluation of generic algorithms for self-organisation and other approaches towards autonomic systems