13,164 research outputs found
To What Extent Are Honeypots and Honeynets Autonomic Computing Systems?
Cyber threats, such as advanced persistent threats (APTs), ransomware, and
zero-day exploits, are rapidly evolving and demand improved security measures.
Honeypots and honeynets, as deceptive systems, offer valuable insights into
attacker behavior, helping researchers and practitioners develop innovative
defense strategies and enhance detection mechanisms. However, their deployment
involves significant maintenance and overhead expenses. At the same time, the
complexity of modern computing has prompted the rise of autonomic computing,
aiming for systems that can operate without human intervention. Recent honeypot
and honeynet research claims to incorporate autonomic computing principles,
often using terms like adaptive, dynamic, intelligent, and learning. This study
investigates such claims by measuring the extent to which autonomic principles
principles are expressed in honeypot and honeynet literature. The findings
reveal that autonomic computing keywords are present in the literature sample,
suggesting an evolution from self-adaptation to autonomic computing
implementations. Yet, despite these findings, the analysis also shows low
frequencies of self-configuration, self-healing, and self-protection keywords.
Interestingly, self-optimization appeared prominently in the literature. While
this study presents a foundation for the convergence of autonomic computing and
deceptive systems, future research could explore technical implementations in
sample articles and test them for autonomic behavior. Additionally,
investigations into the design and implementation of individual autonomic
computing principles in honeypots and determining the necessary ratio of these
principles for a system to exhibit autonomic behavior could provide valuable
insights for both researchers and practitioners.Comment: 18 pages, 3 figures, 5 table
TUNeEngine : An Adaptable Autonomic Administration System
International audienceThe Autonomic Administration technology has proved its efficiency for the administration of complex com-puting systems. However, experiments conducted with several Autonomic Administration Systems (AAS) revealed the need to adapt the AAS according to the administrated system or the considered administration facet. Consequently, users usually have to adapt even to re-implement the AAS according to their specific needs but these tasks require high expertise on the AAS implementation that users do not necessarily have. In this paper we propose a service-oriented components approach to build a generic, flexible, and useful AAS. We present an implementation of this approach, the design principles and the prototype called TUNeEngine. We illustrate the flexibility of this prototype through the administration of a complex computing system which is a virtualized cloud platform
SLA-Oriented Resource Provisioning for Cloud Computing: Challenges, Architecture, and Solutions
Cloud computing systems promise to offer subscription-oriented,
enterprise-quality computing services to users worldwide. With the increased
demand for delivering services to a large number of users, they need to offer
differentiated services to users and meet their quality expectations. Existing
resource management systems in data centers are yet to support Service Level
Agreement (SLA)-oriented resource allocation, and thus need to be enhanced to
realize cloud computing and utility computing. In addition, no work has been
done to collectively incorporate customer-driven service management,
computational risk management, and autonomic resource management into a
market-based resource management system to target the rapidly changing
enterprise requirements of Cloud computing. This paper presents vision,
challenges, and architectural elements of SLA-oriented resource management. The
proposed architecture supports integration of marketbased provisioning policies
and virtualisation technologies for flexible allocation of resources to
applications. The performance results obtained from our working prototype
system shows the feasibility and effectiveness of SLA-based resource
provisioning in Clouds.Comment: 10 pages, 7 figures, Conference Keynote Paper: 2011 IEEE
International Conference on Cloud and Service Computing (CSC 2011, IEEE
Press, USA), Hong Kong, China, December 12-14, 201
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
Incorporating prediction models in the SelfLet framework: a plugin approach
A complex pervasive system is typically composed of many cooperating
\emph{nodes}, running on machines with different capabilities, and pervasively
distributed across the environment. These systems pose several new challenges
such as the need for the nodes to manage autonomously and dynamically in order
to adapt to changes detected in the environment. To address the above issue, a
number of autonomic frameworks has been proposed. These usually offer either
predefined self-management policies or programmatic mechanisms for creating new
policies at design time. From a more theoretical perspective, some works
propose the adoption of prediction models as a way to anticipate the evolution
of the system and to make timely decisions. In this context, our aim is to
experiment with the integration of prediction models within a specific
autonomic framework in order to assess the feasibility of such integration in a
setting where the characteristics of dynamicity, decentralization, and
cooperation among nodes are important. We extend an existing infrastructure
called \emph{SelfLets} in order to make it ready to host various prediction
models that can be dynamically plugged and unplugged in the various component
nodes, thus enabling a wide range of predictions to be performed. Also, we show
in a simple example how the system works when adopting a specific prediction
model from the literature
- …