Evaluation and Build to honeypot System about SCADA Security for Large-Scale IoT Devices

Lu, Kuan-Chu; Liu, I-Hsien; Liao, Jia-Wei; Wu, Shao-Chun; Liu, Zongchao; Li, Jung-Shian; Li, Chu-Fen

doi:10.2991/jrnal.k.191202.008

Cited by 5 publications

(3 citation statements)

References 10 publications

(10 reference statements)

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“…In addition, a modified Elliptic Curve Cryptography (ECC) technique was used to prevent the network from attacks. Lu et al [33] built a honey pot system for improving the security of SCADA against spoofed attacks. Huda et al [34] employed an ensemble of deep belief networks for strengthening the security of SCADA-IoT systems.…”

Section: Literature Reviewmentioning

confidence: 99%

A Proficient ZESO-DRKFC Model for Smart Grid SCADA Security

Rabie

Balachandran²,

Shitharth

2022

Electronics

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Smart grids are complex cyber-physical systems that incorporate smart devices’ communication capabilities into the grid to enable remote management and the control of power systems. However, this integration reveals numerous SCADA system flaws, which could compromise security goals and pose severe cyber threats to the smart grid. In conventional works, various attack detection methodologies are developed to strengthen the security of smart grid SCADA systems. However, they have several issues with complexity, slow training speed, time consumption, and inaccurate prediction outcomes. The purpose of this work is to develop a novel security framework for protecting smart grid SCADA systems against harmful network vulnerabilities or intrusions. Therefore, the proposed work is motivated to develop an intelligent meta-heuristic-based Artificial Intelligence (AI) mechanism for securing IoT-SCADA systems. The proposed framework includes the stages of dataset normalization, Zaire Ebola Search Optimization (ZESO), and Deep Random Kernel Forest Classification (DRKFC). First, the original benchmarking datasets are normalized based on content characterization and category transformation during preprocessing. After that, the ZESO algorithm is deployed to select the most relevant features for increasing the training speed and accuracy of attack detection. Moreover, the DRKFC technique accurately categorizes the normal and attacking data flows based on the optimized feature set. During the evaluation, the performance of the proposed ZESO-DRKFC method is validated and compared in terms of accuracy, detection rate, f1-score, and false acceptance rate. According to the results, it is observed that the ZESO-DRKFC mechanism outperforms other techniques with high accuracy (99%) by precisely spotting intrusions in the smart grid systems.

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Section: Literature Reviewmentioning

confidence: 99%

A Proficient ZESO-DRKFC Model for Smart Grid SCADA Security

Rabie

Balachandran²,

Shitharth

2022

Electronics

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“…Lu et al [119] deployed Conpot on a Raspberry Pi to simulate Siemens S7 class PLCs. In addition, they used an Arduino board to simulate a PLC and another Arduino for sensor simulations.…”

Section: Cao Et Al Proposed a Distributed Ics Honeypot Calledmentioning

confidence: 99%

A Survey of Honeypots and Honeynets for Internet of Things, Industrial Internet of Things, and Cyber-Physical Systems

Franco¹,

Arış²,

Canberk³

et al. 2021

Preprint

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The Internet of Things (IoT), the Industrial Internet of Things (IIoT), and Cyber-Physical Systems (CPS) have become essential for our daily lives in contexts such as our homes, buildings, cities, health, transportation, manufacturing, infrastructure, and agriculture. However, they have become popular targets of attacks, due to their inherent limitations which create vulnerabilities. Honeypots and honeynets can prove essential to understand and defend against attacks on IoT, IIoT, and CPS environments by attracting attackers and deceiving them into thinking that they have gained access to the real systems. Honeypots and honeynets can complement other security solutions (i.e., firewalls, Intrusion Detection Systems -IDS) to form a strong defense against malicious entities. This paper provides a comprehensive survey of the research that has been carried out on honeypots and honeynets for IoT, IIoT, and CPS. It provides a taxonomy and extensive analysis of the existing honeypots and honeynets, states key design factors for the state-of-the-art honeypot/honeynet research and outlines open issues for future honeypots and honeynets for IoT, IIoT, and CPS environments.

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“…In recent years, the utilization of advanced technologies such as IoT (Internet of Thinks) and AI (Artificial Intelligence) has been remarkable. IoT [1], [2], [3], [4], [5] is attracting attention, and expectations are rising in the industrial world for the utilization of data obtained from the many sensors installed in the system. These data are accumulated in a database in real time through communication between the sensor and the cloud.…”

Section: Introductionmentioning

confidence: 99%

Development of IoT self-tuning control device using Wi-Fi

Imai

2023

Proceedings of International Conference on Artificial Life and Robotics

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In this paper, development of IoT control device using Wi-Fi. In recent years, IoT has been attracting attention, and there are growing expectations in the industrial world for the utilization of data obtained from many sensors. These data are stored in databases in real time through communication between sensors and the cloud and communicating with the cloud. Meanwhile, digital controllers are widely used in the process industry as general-purpose controllers. However, it is difficult to incorporate AI, machine learning, and databases into general-purpose controllers due to data memory limitations. Therefore, in this paper, we develop an IoT self-tuning controller using Wi-Fi. As a result of experiments, the controller and computer were connected via Wi-Fi, self-tuning was performed on the computer side, and the calculated PID gains could be sent to the controller to achieve control.

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Evaluation and Build to honeypot System about SCADA Security for Large-Scale IoT Devices

Cited by 5 publications

References 10 publications

A Proficient ZESO-DRKFC Model for Smart Grid SCADA Security

A Proficient ZESO-DRKFC Model for Smart Grid SCADA Security

A Survey of Honeypots and Honeynets for Internet of Things, Industrial Internet of Things, and Cyber-Physical Systems

Development of IoT self-tuning control device using Wi-Fi

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