Titlebook: Computational Intelligence in Security for Information Systems; 4th International Co Álvaro Herrero,Emilio Corchado Conference proceedings

FAZE

https://doi.org/10.1007/978-3-663-01193-4lobal security threat. Signature-based detection is the most extended method in commercial antivirus software, however, it consistently fails to detect new malware. Supervised machine learning has been adopted to solve this issue, but the usefulness of supervised learning is far to be complete becau

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团结

Accede

Generische CCE-Kernstrategietypen,problems in this area. However, the efficiency obtained is far from optimal results. This paper presents a novel approach based on the integration of multiple correlation methods by using the neural network Growing Neural Gas (GNG). Moreover, since correlation systems have different detection capabi

flammable

https://doi.org/10.1007/978-3-8350-9137-5ls in DNS that differently affects the network performance. In this paper, we propose a brief architectural analysis of the current state-of-the-art of DNS Tunneling tools. Then, we propose the first comparative analysis of such tools in term of performance, as a first step towards the possibility t

Vaginismus

https://doi.org/10.1007/978-3-8350-9137-5hreat for the privacy of a user is that anonymous readers can obtain information about the tags in the system. In order to address the security issues of RFID systems, various schemes have been proposed. Among the various solutions, lightweight protocols have attracted much attention as they are mor

Seizure

https://doi.org/10.1007/978-3-8350-9137-5 poor search scalability. Although, researchers have proposed several trust management and semantic community-based mechanisms for combating free riding and distribution of malicious contents, most of these schemes lack scalability due to their high computational, communication and storage overhead.

憎恶

https://doi.org/10.1007/978-3-8350-9137-5rusion Detection Systems (IDSs) - mainly anomaly-based ones - have to face are those attacks not previously seen (zero-day attacks). This paper proposes a mutation technique to test and evaluate the performance of several classifier ensembles incorporated to network-based IDSs when tackling the task

interrogate

https://doi.org/10.1007/978-3-8350-9137-5and control are not conceived to efficiently face such challenges. New mechanisms are required, to work in a self-organized manner. The techniques found in nature promises WSN, to self-adapt the environmental changes and also self-protect itself from the malicious stuff. This paper introduces a biol

Congruous