The exponential growth in the use of Internet of Things (IoT) devices has introduced numerous challenges, in particular dealing with new security threats. In addition, for connecting heterogeneous devices using differ...
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The exponential growth in the use of Internet of Things (IoT) devices has introduced numerous challenges, in particular dealing with new security threats. In addition, for connecting heterogeneous devices using different protocols, large networks need resilient software-based security systems that can defend against unprecedented attacks for which the traditional security countermeasures prove to be ineffective. Furthermore, to deal with the ever growing onslaught on data and networks, modern security systems need to utilize novel machine learning mechanisms. This paper proposes a software-basedarchitecture that provides network function virtualization (NFV) capability to combat malware spread for heterogeneous IoT networks. To build a scalable and generalized Intrusion Detection System (IDS), we propose for these networks a RNN-LSTM learning model that can predict malware attacks in a timely manner for the NFV to deploy appropriate countermeasures. In addition, we investigate the scalability of the network and discuss how the generalized IDS can deal with a broad range of malwares that can be detected. The analysis utilizes the susceptible (S), exposed (E), infected (I), and resistant (R) (SEIR) epidemic model to moniter the spread of the malware attack and subsequently provides patching to the system. Our analysis focuses primarily on the feasibility and the performance evaluation of the proposed integrated RNN-LSTM and NFV architecture.
the increasing difficultly of developing modern test systems is compounded by shortened development times and exponentially more complex devices under test. The fundamental need for connectivity to a wide variety of h...
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ISBN:
(纸本)9781424479597
the increasing difficultly of developing modern test systems is compounded by shortened development times and exponentially more complex devices under test. The fundamental need for connectivity to a wide variety of hardware has not changed, but test engineers often find themselves building systems without the final hardware and without access to the actual device that will be tested. This need for flexibility and reusability in modern test applications has driven the emphasis on software based architectures. National Instruments LabVIEW is the most widely used development environment for instrument connectivity and test applications, but it's often used in hybrid systems that combine a variety of programming approaches. As a result, it's important to understand how graphical code compares to, and can work with, traditional text-based alternatives for use in these complex test systems.
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