Intelligent Intrusion Detection Algorithm Based on Multi-Attack for Edge-Assisted Internet of Things

Shitharth, S.; Mohammed, Gouse Baig; Ramasamy, Jayaraj; Srivel, R.

doi:10.1007/978-3-031-28150-1_6

Cited by 11 publications

(4 citation statements)

References 33 publications

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“…Although regulation of vulnerability disclosure behavior among hackers has been studied for many years, the emergence of new technologies and service models necessitates the collective participation of multiple stakeholders such as enterprises and service companies in collaborative disclosure. Especially, With the increasing prominence of security issues in fields of industry, healthcare, and the Internet of Things (IoT) [27][28][29][30], hackers exploiting vulnerabilities in artificial intelligence [31], blockchain [32], and intrusion detection systems [33] to launch large-scale targeted attacks have become norm. The demand for efficient data analysis and processing [34,35], network security protection [27], and privacy data protection [32] is steadily increasing for enterprises.…”

Section: Security Crowd-testingmentioning

confidence: 99%

Regulatory mechanism of vulnerability disclosure behavior considering security crowd-testing: An evolutionary game analysis

Zhao,

Yu,

Zhou

2024

PLoS ONE

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The security crowd-testing regulatory mechanism is a vital means to promote collaborative vulnerability disclosure. However, existing regulatory mechanisms have not considered multi-agent responsibility boundaries and stakeholders’ conflicts of interest, leading to their dysfunction. Distinguishing from previous research on the motivations and constraints of ethical hacks’ vulnerability disclosure behaviors from a legal perspective, this paper constructs an evolutionary game model of SRCs, security researchers, and the government from a managerial perspective to propose regulatory mechanisms promoting tripartite collaborative vulnerability disclosure. The results show that the higher the initial willingness of the three parties to choose the collaborative strategy, the faster the system evolves into a stable state. Regarding the government’s incentive mechanism, establishing reward and punishment mechanisms based on effective thresholds is essential. However, it is worth noting that the government has an incentive to adopt such mechanisms only if it receives sufficient regulatory benefits. To further facilitate collaborative disclosure, Security Response Centers (SRC) should establish incentive mechanisms including punishment and trust mechanisms. Additionally, publicity and training mechanisms for security researchers should be introduced to reduce their revenue from illegal participation, which promotes the healthy development of security crowd-testing. These findings contribute to improving SRCs’ service quality, guiding security researchers’ legal participation, enhancing the government’s regulatory effectiveness, and ultimately establishing a multi-party collaborative vulnerability disclosure system.

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Section: Security Crowd-testingmentioning

confidence: 99%

Regulatory mechanism of vulnerability disclosure behavior considering security crowd-testing: An evolutionary game analysis

Zhao,

Yu,

Zhou

2024

PLoS ONE

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“…Smart city applications raise a serious of concerns and challenges in terms of security and privacy threats ranging from unauthorized intrusions, acknowledgements, disruption, mitigation, scrutiny and devastation 4 . Internet of Things also raises security concerns comprising of data identification, data authentication, data integrity, availability, confidentiality, access privileges, data privacy and trust 5 . The information transmitted between the IoT devices happens through a wide open communication channel they are highly prone to security and privacy attacks 6 .…”

Section: Introductionmentioning

confidence: 99%

Dickson polynomial-based secure group authentication scheme for Internet of Things

Syed,

Manickam,

Uddin

et al. 2024

Sci Rep

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Internet of Things (IoT) paves the way for the modern smart industrial applications and cities. Trusted Authority acts as a sole control in monitoring and maintaining the communications between the IoT devices and the infrastructure. The communication between the IoT devices happens from one trusted entity of an area to the other by way of generating security certificates. Establishing trust by way of generating security certificates for the IoT devices in a smart city application can be of high cost and expensive. In order to facilitate this, a secure group authentication scheme that creates trust amongst a group of IoT devices owned by several entities has been proposed. The majority of proposed authentication techniques are made for individual device authentication and are also utilized for group authentication; nevertheless, a unique solution for group authentication is the Dickson polynomial based secure group authentication scheme. The secret keys used in our proposed authentication technique are generated using the Dickson polynomial, which enables the group to authenticate without generating an excessive amount of network traffic overhead. IoT devices' group authentication has made use of the Dickson polynomial. Blockchain technology is employed to enable secure, efficient, and fast data transfer among the unique IoT devices of each group deployed at different places. Also, the proposed secure group authentication scheme developed based on Dickson polynomials is resistant to replay, man-in-the-middle, tampering, side channel and signature forgeries, impersonation, and ephemeral key secret leakage attacks. In order to accomplish this, we have implemented a hardware-based physically unclonable function. Implementation has been carried using python language and deployed and tested on Blockchain using Ethereum Goerli’s Testnet framework. Performance analysis has been carried out by choosing various benchmarks and found that the proposed framework outperforms its counterparts through various metrics. Different parameters are also utilized to assess the performance of the proposed blockchain framework and shows that it has better performance in terms of computation, communication, storage and latency.

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“…Every device, from a simple sensor on a production line to a complex robotic arm, continuously sends and receives data. While this data-driven approach facilitates informed decision-making and predictive maintenance, it also introduces multiple points of vulnerability [4,5].…”

Section: Introductionmentioning

confidence: 99%

“…The integrity and authenticity of data in smart manufacturing systems are of paramount importance. A single piece of compromised data can not only disrupt production but also lead to significant financial losses and safety concerns [5,12]. Despite the recognized importance of this issue, there remains a gap in the development and implementation of robust security mechanisms tailored to the unique challenges of smart manufacturing.…”

Section: Introductionmentioning

confidence: 99%

Securing Smart Manufacturing by Integrating Anomaly Detection With Zero-Knowledge Proofs

Salam,

Abrar,

Amin

et al. 2024

IEEE Access

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Intelligent Intrusion Detection Algorithm Based on Multi-Attack for Edge-Assisted Internet of Things

Cited by 11 publications

References 33 publications

Regulatory mechanism of vulnerability disclosure behavior considering security crowd-testing: An evolutionary game analysis

Regulatory mechanism of vulnerability disclosure behavior considering security crowd-testing: An evolutionary game analysis

Dickson polynomial-based secure group authentication scheme for Internet of Things

Securing Smart Manufacturing by Integrating Anomaly Detection With Zero-Knowledge Proofs

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