Capturing-the-Invisible (CTI): Behavior-Based Attacks Recognition in IoT-Oriented Industrial Control Systems

Bhardwaj, Akashdeep; Al‐Turjman, Fadi; Kumar, Manoj; Stephan, Thompson; Mostarda, Leonardo

doi:10.1109/access.2020.2998983

Cited by 43 publications

(5 citation statements)

References 20 publications

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“…[24] Provides foundational understanding of IoT architectures, essential for IoT security. [25] Discusses behavior-based attack recognition in industrial control systems within IoT. [26] Addresses the critical area of firmware updates for IoT devices.…”

Section: Ref Contribution and Significance [5]mentioning

confidence: 99%

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Securing the Internet of Things in Artificial Intelligence Era: A Comprehensive Survey

Humayun,

Tariq,

Alfayad

et al. 2024

IEEE Access

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The Internet of Things (IoT) has revolutionized various domains, enabling interconnected devices to communicate and exchange data. The integration of Artificial Intelligence (AI) in IoT systems further enhances their capabilities and potential benefits. Unfortunately, in the era of AI, ensuring the privacy and security of the IoT faces novel and specific challenges. IoT security is imperative, necessitating comprehensive strategies, including comprehension of IoT security challenges, implementation of AI methodologies, adoption of resilient security frameworks, and handling of privacy and ethical concerns to construct dependable and secure IoT systems. It is vital to note that the term 'security' encompasses a more comprehensive view than cyberattacks alone. Therefore, with an emphasis on securing against cyberattacks, this comprehensive survey also includes physical security threats on the IoT. It investigates the complexities and solutions for IoT systems, placing particular emphasis on AI-based security techniques. The paper undertakes a categorization of the challenges associated with ensuring IoT security, investigates the utilization of AI in IoT security, presents security frameworks and strategies, underscores privacy and ethical considerations, and provides insights derived from practical case studies. Furthermore, the survey sheds light on emerging trends concerning IoT security in the AI era. This survey provides significant contributions to the understanding of establishing dependable and secure IoT systems through an exhaustive examination of the present condition of IoT security and the ramifications of AI on it.

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Section: Ref Contribution and Significance [5]mentioning

confidence: 99%

“…IDS powered by AI algorithms, such as anomaly detection [56] or behavior-based models [25], can identify potential security breaches and mitigate cyberattacks. These IDS systems continuously monitor network traffic, device activities, and system logs to detect deviations from normal behavior [57].…”

Section: A Threat Detection and Preventionmentioning

confidence: 99%

Securing the Internet of Things in Artificial Intelligence Era: A Comprehensive Survey

Humayun,

Tariq,

Alfayad

et al. 2024

IEEE Access

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“…The results comparatively proves high in case of accuracy with 97.02% with detection rate of 97% and 0.16% false alarm rate [48]. Considering the alert identification as a unique parameter, to improve the significance of detection for hidden attacks, Capture The Invisible (CTI) is used as a pattern recognition algorithm as proposed by Bhardwaj A et.al [49]. The authors suggest that repeated testing with dynamic datasets helps to discover invisible attacks compared to the Inductive Miner algorithm [49].…”

Section: A Machine Learning-based Solutionsmentioning

confidence: 99%

“…Considering the alert identification as a unique parameter, to improve the significance of detection for hidden attacks, Capture The Invisible (CTI) is used as a pattern recognition algorithm as proposed by Bhardwaj A et.al [49]. The authors suggest that repeated testing with dynamic datasets helps to discover invisible attacks compared to the Inductive Miner algorithm [49]. A summary of the solutions based on machine learning is shown in Table 5.…”

Section: A Machine Learning-based Solutionsmentioning

confidence: 99%

A Taxonomy of Security Issues in Industrial Internet-of-Things: Scoping Review for Existing Solutions, Future Implications, and Research Challenges

et al. 2021

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Industrial Internet of Things (IIoTs) are the extensions of the Internet of Things (IoTs) and have paved the way towards the industry revolution 4.0. IIoT accelerates the industry automation of internal and external working process including transport, manufacturing, and marketing units with a number of connected devices. Being the extension of IoT, it inherits the insecurities of the technology; however, this sensor-configured infrastructure of IIoT needs some extra effort to customize the existing security solutions. In spite of the reconstructions of security models, the scope of improved developments is open to detect unknown attacks. The present study helps the researchers to understand the cause for intrusion by classifying and comparing various attacks of each IIoT layers. The main focus of this survey is to analyze various security issues faced by IIoT and provide a comparative analysis on the available solutions to enhance the industrial IoTs' protection systems. This study also notifies some open research problems for academia, technologists, and researchers to flourish the IIoT domain and its security aspects.

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“…Cloud computing has shown remarkable development in recent decades. When the storage as a service, it occupies the center stage and backbone for many applications, such as pattern recognition [1], image forensic [2] and forgery detection [3]. As a result, larger volumes of data will be a part of the cloud area.…”

Section: Introductionmentioning

confidence: 99%

A Cloud Secure Storage Mechanism Based on Data Dispersion and Encryption

Song

2021

IEEE Access

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Capturing-the-Invisible (CTI): Behavior-Based Attacks Recognition in IoT-Oriented Industrial Control Systems

Abstract: This paragraph of the first footnote will contain support information, including sponsor and financial support acknowledgment.

Cited by 43 publications

References 20 publications

Securing the Internet of Things in Artificial Intelligence Era: A Comprehensive Survey

Securing the Internet of Things in Artificial Intelligence Era: A Comprehensive Survey

A Taxonomy of Security Issues in Industrial Internet-of-Things: Scoping Review for Existing Solutions, Future Implications, and Research Challenges

A Cloud Secure Storage Mechanism Based on Data Dispersion and Encryption

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