7,504 research outputs found
Big Data in Critical Infrastructures Security Monitoring: Challenges and Opportunities
Critical Infrastructures (CIs), such as smart power grids, transport systems,
and financial infrastructures, are more and more vulnerable to cyber threats,
due to the adoption of commodity computing facilities. Despite the use of
several monitoring tools, recent attacks have proven that current defensive
mechanisms for CIs are not effective enough against most advanced threats. In
this paper we explore the idea of a framework leveraging multiple data sources
to improve protection capabilities of CIs. Challenges and opportunities are
discussed along three main research directions: i) use of distinct and
heterogeneous data sources, ii) monitoring with adaptive granularity, and iii)
attack modeling and runtime combination of multiple data analysis techniques.Comment: EDCC-2014, BIG4CIP-201
A Framework for Evaluating Model-Driven Self-adaptive Software Systems
In the last few years, Model Driven Development (MDD), Component-based
Software Development (CBSD), and context-oriented software have become
interesting alternatives for the design and construction of self-adaptive
software systems. In general, the ultimate goal of these technologies is to be
able to reduce development costs and effort, while improving the modularity,
flexibility, adaptability, and reliability of software systems. An analysis of
these technologies shows them all to include the principle of the separation of
concerns, and their further integration is a key factor to obtaining
high-quality and self-adaptable software systems. Each technology identifies
different concerns and deals with them separately in order to specify the
design of the self-adaptive applications, and, at the same time, support
software with adaptability and context-awareness. This research studies the
development methodologies that employ the principles of model-driven
development in building self-adaptive software systems. To this aim, this
article proposes an evaluation framework for analysing and evaluating the
features of model-driven approaches and their ability to support software with
self-adaptability and dependability in highly dynamic contextual environment.
Such evaluation framework can facilitate the software developers on selecting a
development methodology that suits their software requirements and reduces the
development effort of building self-adaptive software systems. This study
highlights the major drawbacks of the propped model-driven approaches in the
related works, and emphasise on considering the volatile aspects of
self-adaptive software in the analysis, design and implementation phases of the
development methodologies. In addition, we argue that the development
methodologies should leave the selection of modelling languages and modelling
tools to the software developers.Comment: model-driven architecture, COP, AOP, component composition,
self-adaptive application, context oriented software developmen
Designing and Valuating System on Dependability Analysis of Cluster-Based Multiprocessor System
Analysis of dependability is a significant stage in structuring and examining the safety of protection systems and computer systems. The introduction of virtual machines and multiprocessors leads to increasing the faults of the system, particularly for the failures that are software- induced, affecting the overall dependability. Also, it is different for the successful operation of the safety system at any dynamic stage, since there is a tremendous distinction in the rate of failure among the failures that are induced by the software and the hardware. Thus this paper presents a review or different dependability analysis techniques employed in multiprocessor system
Spartan Daily, May 19, 1982
Volume 78, Issue 67https://scholarworks.sjsu.edu/spartandaily/6910/thumbnail.jp
ANCHOR: logically-centralized security for Software-Defined Networks
While the centralization of SDN brought advantages such as a faster pace of
innovation, it also disrupted some of the natural defenses of traditional
architectures against different threats. The literature on SDN has mostly been
concerned with the functional side, despite some specific works concerning
non-functional properties like 'security' or 'dependability'. Though addressing
the latter in an ad-hoc, piecemeal way, may work, it will most likely lead to
efficiency and effectiveness problems. We claim that the enforcement of
non-functional properties as a pillar of SDN robustness calls for a systemic
approach. As a general concept, we propose ANCHOR, a subsystem architecture
that promotes the logical centralization of non-functional properties. To show
the effectiveness of the concept, we focus on 'security' in this paper: we
identify the current security gaps in SDNs and we populate the architecture
middleware with the appropriate security mechanisms, in a global and consistent
manner. Essential security mechanisms provided by anchor include reliable
entropy and resilient pseudo-random generators, and protocols for secure
registration and association of SDN devices. We claim and justify in the paper
that centralizing such mechanisms is key for their effectiveness, by allowing
us to: define and enforce global policies for those properties; reduce the
complexity of controllers and forwarding devices; ensure higher levels of
robustness for critical services; foster interoperability of the non-functional
property enforcement mechanisms; and promote the security and resilience of the
architecture itself. We discuss design and implementation aspects, and we prove
and evaluate our algorithms and mechanisms, including the formalisation of the
main protocols and the verification of their core security properties using the
Tamarin prover.Comment: 42 pages, 4 figures, 3 tables, 5 algorithms, 139 reference
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