Loye Lynn Ray
Pág. 57 - 63
Networks are up against detecting dynamic and unknown threats. Anomaly-based neural network (NN) intrusion detection systems (IDSs) can manage this if trained and tested accordingly. This requires the IDS to be evaluated on how well it can detect these i...
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Duc-Minh Ngo, Dominic Lightbody, Andriy Temko, Cuong Pham-Quoc, Ngoc-Thinh Tran, Colin C. Murphy and Emanuel Popovici
This study proposes a heterogeneous hardware-based framework for network intrusion detection using lightweight artificial neural network models. With the increase in the volume of exchanged data, IoT networks? security has become a crucial issue. Anomaly...
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Alvaro Parres-Peredo, Ivan Piza-Davila and Francisco Cervantes
Anomaly-based intrusion detection systems use profiles to characterize expected behavior of network users. Most of these systems characterize the entire network traffic within a single profile. This work proposes a user-level anomaly-based intrusion dete...
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Imtiaz Ullah, Ayaz Ullah and Mazhar Sajjad
The tremendous number of Internet of Things (IoT) applications, with their ubiquity, has provided us with unprecedented productivity and simplified our daily life. At the same time, the insecurity of these technologies ensures that our daily lives are su...
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Merve Ozkan-Okay, Refik Samet, Ömer Aslan, Selahattin Kosunalp, Teodor Iliev and Ivaylo Stoyanov
The fast development of communication technologies and computer systems brings several challenges from a security point of view. The increasing number of IoT devices as well as other computing devices make network communications more challenging. The num...
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