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

HETEROGENEOUS SERVER RETRIAL QUEUEING MODEL WITH FEEDBACK AND WORKING VACATION USING ARTIFICIAL BEE COLONY OPTIMIZATION ALGORITHM

This research delves into the dynamics of a retrial queueing system featuring heterogeneous servers with intermittent availability, incorporating feedback and working vacation mechanisms. Employing a matrix geometric approach, this study establishes the steady-state probability distribution for the queue size in this complex heterogeneous service model. Additionally, a range of system performance metrics is developed, alongside the formulation of a cost function to evaluate decision variable optimization within the service system. The Artificial Bee Colony (ABC) optimization algorithm is harnessed to determine service rates that minimize the overall cost. This work includes numerical examples and sensitivity analyses to validate the model's effectiveness. Also, a comparison between the numerical findings and the neuro-fuzzy results has been examined by the adaptive neuro fuzzy interface system (ANFIS)

A Retrial Queueing Model With Thresholds and Phase Type Retrial Times

There is an extensive literature on retrial queueing models. While a majority of the literature on retrial queueing models focuses on the retrial times to be exponentially distributed (so as to keep the state space to be of a reasonable size), a few papers deal with nonexponential retrial times but with some additional restrictions such as constant retrial rate, only the customer at the head of the retrial queue will attempt to capture a free server, 2-state phase type distribution, and finite retrial orbit. Generally, the retrial queueing models are analyzed as level-dependent queues and hence one has to use some type of a truncation method in performing the analysis of the model. In this paper we study a retrial queueing model with threshold-type policy for orbiting customers in the context of nonexponential retrial times. Using matrix-analytic methods we analyze the model and compare with the classical retrial queueing model through a few illustrative numerical examples. We also compare numerically our threshold retrial queueing model with a previously published retrial queueing model that uses a truncation method

Performance-oriented Cloud Provisioning: Taxonomy and Survey

Cloud computing is being viewed as the technology of today and the future. Through this paradigm, the customers gain access to shared computing resources located in remote data centers that are hosted by cloud providers (CP). This technology allows for provisioning of various resources such as virtual machines (VM), physical machines, processors, memory, network, storage and software as per the needs of customers. Application providers (AP), who are customers of the CP, deploy applications on the cloud infrastructure and then these applications are used by the end-users. To meet the fluctuating application workload demands, dynamic provisioning is essential and this article provides a detailed literature survey of dynamic provisioning within cloud systems with focus on application performance. The well-known types of provisioning and the associated problems are clearly and pictorially explained and the provisioning terminology is clarified. A very detailed and general cloud provisioning classification is presented, which views provisioning from different perspectives, aiding in understanding the process inside-out. Cloud dynamic provisioning is explained by considering resources, stakeholders, techniques, technologies, algorithms, problems, goals and more.Comment: 14 pages, 3 figures, 3 table

A multiple channel queueing model under an uncertain environment with multiclass arrivals for supplying demands in a cement industry

In recent years, cement consumption has increased in most Asian countries, including Malaysia. There are many factors which affect the supply of the increasing order demands in the cement industry, such as traffic congestion, logistics, weather and machine breakdowns. These factors hinder smooth and efficient supply, especially during periods of peak congestion at the main gate of the industry where queues occur as a result of inability to keep to the order deadlines. Basic elements, such as arrival and service rates, that cannot be predetermined must be considered under an uncertain environment. Solution approaches including conventional queueing techniques, scheduling models and simulations were unable to formulate the performance measures of the cement queueing system. Hence, a new procedure of fuzzy subset intervals is designed and embedded in a queuing model with the consideration of arrival and service rates. As a result, a multiple channel queueing model with multiclass arrivals, (M1, M2)/G/C/2Pr, under an uncertain environment is developed. The model is able to estimate the performance measures of arrival rates of bulk products for Class One and bag products for Class Two in the cement manufacturing queueing system. For the (M1, M2)/G/C/2Pr fuzzy queueing model, two defuzzification techniques, namely the Parametric Nonlinear Programming and Robust Ranking are used to convert fuzzy queues into crisp queues. This led to three proposed sub-models, which are sub-model 1, MCFQ-2Pr, sub-model 2, MCCQESR-2Pr and sub-model 3, MCCQ-GSR-2Pr. These models provide optimal crisp values for the performance measures. To estimate the performance of the whole system, an additional step is introduced through the TrMF-UF model utilizing a utility factor based on fuzzy subset intervals and the α-cut approach. Consequently, these models help decision-makers deal with order demands under an uncertain environment for the cement manufacturing industry and address the increasing quantities needed in future

Architecture for Mobile Heterogeneous Multi Domain Networks

Multi domain networks can be used in several scenarios including military, enterprize networks, emergency networks and many other cases. In such networks, each domain might be under its own administration. Therefore, the cooperation among domains is conditioned by individual domain policies regarding sharing information, such as network topology, connectivity, mobility, security, various service availability and so on. We propose a new architecture for Heterogeneous Multi Domain (HMD) networks, in which one the operations are subject to specific domain policies. We propose a hierarchical architecture, with an infrastructure of gateways at highest-control level that enables policy based interconnection, mobility and other services among domains. Gateways are responsible for translation among different communication protocols, including routing, signalling, and security. Besides the architecture, we discuss in more details the mobility and adaptive capacity of services in HMD. We discuss the HMD scalability and other advantages compared to existing architectural and mobility solutions. Furthermore, we analyze the dynamic availability at the control level of the hierarchy

Queueing Networks for Vertical Handover

PhDIt is widely expected that next-generation wireless communication systems will be heterogeneous, integrating a wide variety of wireless access networks. Of particular interest recently is a mix of cellular networks (GSM/GPRS and WCDMA) and wireless local area networks (WLANs) to provide complementary features in terms of coverage, capacity and mobility support. If cellular/ WLAN interworking is to be the basis for a heterogeneous network then the analysis of complex handover traffic rates in the system (especially vertical handover) is one of the most essential issues to be considered. This thesis describes the application of queueing-network theory to the modelling of this heterogeneous wireless overlay system. A network of queues (or queueing network) is a powerful mathematical tool in the performance evaluation of many large-scale engineering systems. It has been used in the modelling of hierarchically structured cellular wireless networks with much success, including queueing network modelling in the study of cellular/ WLAN interworking systems. In the process of queueing network modelling, obtaining the network topology of a system is usually the first step in the construction of a good model, but this topology analysis has never before been used in the handover traffic study in heterogeneous overlay wireless networks. In this thesis, a new topology scheme to facilitate the analysis of handover traffic is proposed. The structural similarity between hierarchical cellular structure and heterogeneous wireless overlay networks is also compared. By replacing the microcells with WLANs in a hierarchical structure, the interworking system is modelled as an open network of Erlang loss systems and with the new topology, the performance measures of blocking probabilities and dropping probabilities can be determined. Both homogeneous and non-homogeneous traffic have been considered, circuit switched and packet-switched. Example scenarios have been used to validate the models, the numerical results showing clear agreement with the known validation scenarios

Operational Analysis Revisited: Error Measure Limits of Assumptions

The assumptions used to develop operational analysiscomputer performance measures, such as number of jobs at adevice or response times, are stated in terms of the data itself,rather than the underlying system which produces the data. Inspite of claims of validity and as an aid in introducing queueingtheory in teaching, little has been written about operationalanalysis in the past ten years. Accuracy of operational analysisperformance measures depend on data behavior assumptionswhich can be validated with data based error measures.Increased soundness of the operational analysis approach may beobtained by determining the limits of assumption errors as thetime period of observation increases. Part I of this paper is areview of operational analysis and addresses some of the previousconcerns with its approach. Part II develops furtherunderstanding of operational analysis assumption errors byexamining their limits. Limits are found for the assumptionerrors of job flow balance, homogeneous arrivals andhomogenous services. While the job flow balance assumptionerror measure is shown to approach zero over time, thehomogeneity assumption error measures, in general, do not