Efficient parallel automata construction for hybrid resource-impelled data-matching

Pungilaˇ, Ciprian-Petrişor; Reja, Mario; Negru, Viorel

doi:10.1016/j.future.2013.09.008

Cited by 12 publications

(2 citation statements)

References 25 publications

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“…Each node will then just require a bitmap to indicate if a symbol is accepted or not, a failure offset indicating the node to jump to in case of a mismatch, and an offset to the first child in the stack, for situations when a symbol is accepted (the offset of the proper child to go to is computed by applying a population count in the bitmap). The approach has been successfully used in our earlier work [12] to significantly improve the construction stages of these automata, and still is at this time the most efficient storage format for heterogeneous automata processing.…”

Section: Storage Efficiencymentioning

confidence: 99%

Real-Time Hybrid Compression of Pattern Matching Automata for Heterogeneous Signature-Based Intrusion Detection

Pungila

Negru

2015

Advances in Intelligent Systems and Computing

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We are proposing a new hybrid approach to achieving real-time compression of pattern matching automata in signature-based intrusion detection systems, with particular emphasis on heterogeneous CPU/GPU architectures. We also provide details of the implementation and show how a hybrid approach can lead to improved compression ratios while performing real-time changes to the automata. By testing our methodology in a real-world scenario using sets taken from the ClamAV signature database the Snort rules database, we show that the approach we propose performs better than the current solutions, significantly reducing the storage required and paving the way for high-throughput CPU/GPU heterogeneous processing for such type of automata.

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Section: Storage Efficiencymentioning

confidence: 99%

Real-Time Hybrid Compression of Pattern Matching Automata for Heterogeneous Signature-Based Intrusion Detection

Pungila

Negru

2015

Advances in Intelligent Systems and Computing

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“…This type of instance is used for data mining [17], data-matching [29], intrusion detection [14,36] and learning [10].…”

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Optimizing cloud resources allocation for an Internet of Things architecture

Manațe¹,

Fortiş²,

Negru³

2015

SCPE

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Abstract. The optimization of the cloud resources used to power a multi-agent Internet of Things architecture is an important issue which has an important impact on the overall operation cost of the architecture. The resources tenancy is a costly operation, thus their allocation and management should be optimized based on the usage patterns. The infrastructure for the multi-agent system should not be affected by the deployment or maintenance life cycle, operations require parts of the system, or even the entire system to be offline during the execution of scheduled procedures. This paper outlines of the importance of the infrastructure audit, which offers a good insight of how the resources are used, the geographical areas which are heavily used and where the allocation or release of used resources is mandatory. Also, the security audit, in a distributed multi-agent architecture that handles a large number of heterogeneous devices, represents a good mechanism for performance improvement.Key words: Internet of Things, cloud computing, multi-agent systems 1. Introduction. The recent advances in Internet of Things (IoT) technologies and the cloud computing adoption have led to an increased usage of this two paradigms to create solid architectures that are able to handle hundred of thousands of concurrent connections, at the same time offering a good Quality of Service (QoS) and Quality of Experience (QoE) for the end user. The resources renting from public cloud providers for supporting the backbone infrastructure for an IoT architecture is beneficial for small and medium-sized enterprises (SME) or academic institutions which are trying to reach a large number of clients, because there is no need to upgrade or maintain the physical infrastructure. Even though the cloud client is not completely aware of the exact location of the hardware that delivers the required information, there are methods available that can determine the best route (considering both geographical location and bandwidth) for optimal performance [39].For handling a big number of connections from a wide range of devices, an Internet of Things architecture should employ a fast, secure, reliable and fail safe infrastructure for the services offered to the end users which rely upon the manner in which the information is collected. Because of different usage patterns that result from the daily routine of different groups of users, the best solution for building an infrastructure for the IoT framework relies on the elasticity provided by the cloud computing paradigm [11,15,23,33]. Also, the operational cost for maintaining the architecture up and running can be significantly reduced by releasing unused resources at daily time intervals when the audit operations report a low usage of the infrastructure.From the reliability and operational standpoint, the core infrastructure for the multi-agent system needs to bypass any bottlenecks introduced by the on demand created infrastructure. Therefore, any replacement or restart of the virtual machines should be...

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An Efficient Heterogeneous Approach to Building Compressed Automata for Malware Signature Matching

Pungila

Negru

2014

Advances in Intelligent Systems and Computing

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Efficient parallel automata construction for hybrid resource-impelled data-matching

Cited by 12 publications

References 25 publications

Real-Time Hybrid Compression of Pattern Matching Automata for Heterogeneous Signature-Based Intrusion Detection

Real-Time Hybrid Compression of Pattern Matching Automata for Heterogeneous Signature-Based Intrusion Detection

Optimizing cloud resources allocation for an Internet of Things architecture

An Efficient Heterogeneous Approach to Building Compressed Automata for Malware Signature Matching

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