Towards smarter cyberthreats detection model for industrial internet of things (IIoT) 4.0

被引:10
作者
Hajlaoui, Rejab [1 ]
Moulahi, Tarek [2 ,3 ]
Zidi, Salah [4 ]
El Khediri, Salim [2 ,5 ]
Alaya, Bechir [6 ]
Zeadally, Sherali [7 ]
机构
[1] Univ Hail, Coll Comp Sci & Engn, Dept Informat & Comp Sci, Hail, Saudi Arabia
[2] Qassim Univ, Coll Comp, Dept Informat Technol, Buraydah, Saudi Arabia
[3] Univ Kairouan, Fac Sci & Technol Sidi Bouzid, Kairouan, Tunisia
[4] Univ Gabes, ISSIG, Gabes, Tunisia
[5] Univ Gafsa, Fac Sci Gafsa, Dept Comp Sci, Gafsa, Tunisia
[6] Qassim Univ, Coll Business & Econ, Dept Management Informat Syst & Prod Management, Buraydah 51452, Saudi Arabia
[7] Univ Kentucky, Coll Commun & Informat, Lexington, KY USA
关键词
Cyberthreats; Industrial internet of things (IIoT); Machine learning (ML); Smart contract; Blockchain; BLOCKCHAIN TECHNOLOGY; SENSOR NETWORKS; IOT; PRIVACY; ARCHITECTURE; MANAGEMENT; SECURITY; FUTURE; ISSUES; SYSTEM;
D O I
10.1016/j.jii.2024.100595
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Recently, Artificial Intelligence (AI) has been applied to the Internet of Things (IoT) as well as Industrial IoT 4.0 (IIoT). This has improved the autonomous behavior of smart things in terms of making independent and smart decisions. However, AI techniques are the target of many attacks like the poisoning of training data and the evasion attack. In this context, blockchain can be joined to AI methods to protect their execution. In this paper, we propose SmarterChain to safely detect cyberthreats in IoT. First, we train and generate machine learning models for cyberthreats detection. Next, we protect these models by embedding them on the blockchain. Finally, the models are used by intelligent devices anywhere to facilitate safe decision-making regarding cyberthreats. In addition to identifying the type of attack, our proposed solution outperforms previous detection methods, using the same dataset, in terms of safety ensured by smart contracts, with low overhead due to deployment and runtime.
引用
收藏
页数:11
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