2017
DOI: 10.1155/2017/4749085
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A Consensus Framework for Reliability and Mitigation of Zero-Day Attacks in IoT

Abstract: "Internet of Things" (IoT) bridges the communication barrier between the computing entities by forming a network between them. With a common solution for control and management of IoT devices, these networks are prone to all types of computing threats. Such networks may experience threats which are launched by exploitation of vulnerabilities that are left unhandled during the testing phases. These are often termed as "zero-day" vulnerabilities, and their conversion into a network attack is named as "zeroday" a… Show more

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Cited by 35 publications
(19 citation statements)
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“…Defense solutions against zero-day attacks: While defending zero-day attacks a new mechanism was developed by researchers such as ECC-memory and point twistedness detection in [161], [172] to advert probable memory drips in the program, but still these techniques cannot work without the source codes which are not present at edge devices. The authors of [173], [174] proposed different approaches based only on the firmware to perform memory analysis while the authors of [161], [175] used deep learning methods to find the desired solutions, for example, graph neural networks (GNN), natural language processing (NLP), and recurrent neural networks (RNN) which can identify weaknesses in firmware with high correctness rates. The authors of [176] used the SDN to establish an IoT firewall to minimize the attack surface of exposed IoT devices.…”
Section: ) Zero-day Ddos Attacksmentioning
confidence: 99%
“…Defense solutions against zero-day attacks: While defending zero-day attacks a new mechanism was developed by researchers such as ECC-memory and point twistedness detection in [161], [172] to advert probable memory drips in the program, but still these techniques cannot work without the source codes which are not present at edge devices. The authors of [173], [174] proposed different approaches based only on the firmware to perform memory analysis while the authors of [161], [175] used deep learning methods to find the desired solutions, for example, graph neural networks (GNN), natural language processing (NLP), and recurrent neural networks (RNN) which can identify weaknesses in firmware with high correctness rates. The authors of [176] used the SDN to establish an IoT firewall to minimize the attack surface of exposed IoT devices.…”
Section: ) Zero-day Ddos Attacksmentioning
confidence: 99%
“…They used three factors for trust computation, such as ability, benevolence, and integrity. Sharma et al [18] proposed a consensus framework for mitigating zero-day attacks in IoT networks. Their approach uses the context behavior of IoT devices as a detection mechanism, working with an alert message protocol and a critical data sharing protocol.…”
Section: Related Workmentioning
confidence: 99%
“…14. Network Security: It includes Domain Name Server (DNS) Attack, Sniffer Attack, (Internet Reuse) Protocol) IP Network challenges, and related cybersecurity [21]- [25]. DNS for converting domain names to IP addresses but attack users in DNS to route to other than the original cloud.…”
Section: Costing Modelmentioning
confidence: 99%