Research on DDoS Attack Detection Based on ELM in IoT Environment

Li, Zhihui; Wei, Lihong; Li, Wei; Wei, Lai; Chen, Minshi; Liu, Ming; Zhi, Xulong; Wang, Chenguang; Gao, Nan

doi:10.1109/icsess47205.2019.9040855

Cited by 12 publications

(8 citation statements)

References 4 publications

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“…It can lead to serious consequences such as distributed denial of service attacks (DDoS). The other types of attacks may be similar attacks, i.e., trojan attacks [32]- [34], worm attacks [17], [35], [36], Denial-of-Service attacks (DoS) [3], [19], [34], [37], or data can be spoofed by Man-in-the-middle attacks (MITM) [3], [4], Meet-in-the-middle attacks (MeetITM) [38], and repudiation attacks [39] while one-way encryption schemes are best suited to hinder the attack vector [30], [40]- [42].…”

Section: A Transmission Layer Adversariesmentioning

confidence: 99%

A Blockchain Footprint for Authentication of IoT-Enabled Smart Devices in Smart Cities: State-of-the-Art Advancements, Challenges and Future Research Directions

et al. 2022

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The mechanisms based on the distributed environment have become an obvious choice for solutions, while they have not been limited only to a specific domain (i.e., crypto-currency). Rather, it has influenced other industries to develop robust privacy and security solutions, such as smart houses, smart electrical grids, smart agriculture, smart health care, smart transportation, etc. These Cyber-Physical Systems heavily depend on IoT-based smart devices that constitute a networked system of devices dependent on each other for the smooth operation of the overall system. Hence, security and privacy have become an integral part of all the architectural frameworks they operate in. The adoption of these architectures, such as the Internet of Things (IoT), Internet of Cyber-Physical Things (IoCPT), Cyber-Physical Systems (CPSs), and Internet of Everything (IoE), has reinforced the need to develop solutions based on a distributed environment. Distributed ledger technology, i.e., Blockchain, has taken the lead and may support the development of solutions with robust privacy and security. We provide an updated review of authentication mechanisms developed on blockchain technology that enforce decentralized architectures. We discuss the security issues regarding the authentication of these IoT-enabled smart devices. We evaluate and analyze the study of the proposed literature schemes that pose authentication challenges in terms of computational costs, communication overheads, and models applied to attain robustness. Hence, lightweight solutions for managing, maintaining, processing, and storing authentication data of IoT-enabled assets are a must. From an integration perspective, cloud computing has provided strong support. In contrast, decentralized ledger technology, i.e., Blockchain, and lightweight cryptosystems are the areas for much more to explore. Finally, we discuss the future research challenges, which present an improvement standpoint to help address the ambiguities.

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Section: A Transmission Layer Adversariesmentioning

confidence: 99%

A Blockchain Footprint for Authentication of IoT-Enabled Smart Devices in Smart Cities: State-of-the-Art Advancements, Challenges and Future Research Directions

et al. 2022

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“…They combined diversified feature selection with extreme learning machine to build classifier and claimed to achieve promising results. In 2019, Li and Wei [89] analyzed DDoS attack to propose joint entropy features. combining with extreme learning machine for detection of DDoS attack.…”

Section: Iot Applicationmentioning

confidence: 99%

A review on extreme learning machine

Wang

et al. 2021

Multimed Tools Appl

228

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Extreme learning machine (ELM) is a training algorithm for single hidden layer feedforward neural network (SLFN), which converges much faster than traditional methods and yields promising performance. In this paper, we hope to present a comprehensive review on ELM. Firstly, we will focus on the theoretical analysis including universal approximation theory and generalization. Then, the various improvements are listed, which help ELM works better in terms of stability, efficiency, and accuracy. Because of its outstanding performance, ELM has been successfully applied in many real-time learning tasks for classification, clustering, and regression. Besides, we report the applications of ELM in medical imaging: MRI, CT, and mammogram. The controversies of ELM were also discussed in this paper. We aim to report these advances and find some future perspectives.

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“…As discussed in Section 5.3 , the manufacturers’ low concentration of security features in the IoT-enabled smart assets has uprooted the attack vector to target the devices according to the need. The flaws in security features such as easy-to-guess default login credentials, open ports, unencrypted and weak versions of SSL (v2, v3, and CBC mode) services, etc., give the attack vector an edge to turn these devices vulnerabilities to botnet attacks such as Ramnit (2015), Mootbot (2020), etc., causing the cost of IoT hacks for small US firms amounts to 13% of their annual revenue [ 27 , 28 , 29 , 30 ].…”

Section: Smart City Layered Adversariesmentioning

confidence: 99%

“…In these attacks, the service delivery is compromised to the resources such as network devices, applications, and even specific functions within applications. It may also exist in different forms such as ping-of-death, Smurf, and Black Energy series (BE-1, BE-2) [ 30 , 37 , 38 , 39 ].…”

Section: Smart City Layered Adversariesmentioning

confidence: 99%

A Comparative Analysis on Blockchain versus Centralized Authentication Architectures for IoT-Enabled Smart Devices in Smart Cities: A Comprehensive Review, Recent Advances, and Future Research Directions

Khalil

Malik

Uddin

et al. 2022

Sensors

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Smart devices have become an essential part of the architectures such as the Internet of Things (IoT), Cyber-Physical Systems (CPSs), and Internet of Everything (IoE). In contrast, these architectures constitute a system to realize the concept of smart cities and, ultimately, a smart planet. The adoption of these smart devices expands to different cyber-physical systems in smart city architecture, i.e., smart houses, smart healthcare, smart transportation, smart grid, smart agriculture, etc. The edge of the network connects these smart devices (sensors, aggregators, and actuators) that can operate in the physical environment and collects the data, which is further used to make an informed decision through actuation. Here, the security of these devices is immensely important, specifically from an authentication standpoint, as in the case of unauthenticated/malicious assets, the whole infrastructure would be at stake. We provide an updated review of authentication mechanisms by categorizing centralized and distributed architectures. We discuss the security issues regarding the authentication of these IoT-enabled smart devices. We evaluate and analyze the study of the proposed literature schemes that pose authentication challenges in terms of computational costs, communication overheads, and models applied to attain robustness. Hence, lightweight solutions in managing, maintaining, processing, and storing authentication data of IoT-enabled assets are an urgent need. From an integration perspective, cloud computing has provided strong support. In contrast, decentralized ledger technology, i.e., blockchain, light-weight cryptosystems, and Artificial Intelligence (AI)-based solutions, are the areas with much more to explore. Finally, we discuss the future research challenges, which will eventually help address the ambiguities for improvement.

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Research on DDoS Attack Detection Based on ELM in IoT Environment

Cited by 12 publications

References 4 publications

A Blockchain Footprint for Authentication of IoT-Enabled Smart Devices in Smart Cities: State-of-the-Art Advancements, Challenges and Future Research Directions

A Blockchain Footprint for Authentication of IoT-Enabled Smart Devices in Smart Cities: State-of-the-Art Advancements, Challenges and Future Research Directions

A review on extreme learning machine

A Comparative Analysis on Blockchain versus Centralized Authentication Architectures for IoT-Enabled Smart Devices in Smart Cities: A Comprehensive Review, Recent Advances, and Future Research Directions

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