Koroniotis et al., 2019 - Google Patents
Forensics and deep learning mechanisms for botnets in internet of things: A survey of challenges and solutionsKoroniotis et al., 2019
View PDF- Document ID
- 8393847506173394376
- Author
- Koroniotis N
- Moustafa N
- Sitnikova E
- Publication year
- Publication venue
- IEEE Access
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Snippet
The constant miniaturization of hardware and an increase in power efficiency, have made possible the integration of intelligence into ordinary devices. This trend of augmenting so- called non-intelligent everyday devices with computational capabilities has led to the …
- 238000000034 method 0 abstract description 76
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- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/14—Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic
- H04L63/1408—Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic by monitoring network traffic
- H04L63/1425—Traffic logging, e.g. anomaly detection
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/14—Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic
- H04L63/1441—Countermeasures against malicious traffic
- H04L63/1458—Denial of Service
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- H—ELECTRICITY
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- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/14—Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic
- H04L63/1408—Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic by monitoring network traffic
- H04L63/1416—Event detection, e.g. attack signature detection
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- H—ELECTRICITY
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- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/02—Network architectures or network communication protocols for network security for separating internal from external traffic, e.g. firewalls
- H04L63/0209—Architectural arrangements, e.g. perimeter networks or demilitarized zones
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- H04L63/1441—Countermeasures against malicious traffic
- H04L63/145—Countermeasures against malicious traffic the attack involving the propagation of malware through the network, e.g. viruses, trojans or worms
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- H04L63/0227—Filtering policies
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network-specific arrangements or communication protocols supporting networked applications
- H04L67/10—Network-specific arrangements or communication protocols supporting networked applications in which an application is distributed across nodes in the network
- H04L67/104—Network-specific arrangements or communication protocols supporting networked applications in which an application is distributed across nodes in the network for peer-to-peer [P2P] networking; Functionalities or architectural details of P2P networks
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- H—ELECTRICITY
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- H04L63/105—Multiple levels of security
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- H04L9/00—Cryptographic mechanisms or cryptographic arrangements for secret or secure communication
- H04L9/08—Key distribution or management, e.g. generation, sharing or updating, of cryptographic keys or passwords
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