Blockchain-Based Digital Forensics Investigation Framework in the Internet of Things and Social Systems

Li, Shancang; Qin, Tao; Min, Geyong

doi:10.1109/tcss.2019.2927431

Cited by 86 publications

(28 citation statements)

References 38 publications

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“…Deep learning (DL) is considered to be the founding pillar of modern artificial intelligence [8]. DL has been widely used in computer vision, speech recognition, robotics, and many other application areas.…”

Section: Behaviour Modelling and Analysis Of Iot Using Deep Learningmentioning

confidence: 99%

Deep Learning-Based Security Behaviour Analysis in IoT Environments: A Survey

Yue

Legg

et al. 2021

Security and Communication Networks

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Internet of Things (IoT) applications have been used in a wide variety of domains ranging from smart home, healthcare, smart energy, and Industrial 4.0. While IoT brings a number of benefits including convenience and efficiency, it also introduces a number of emerging threats. The number of IoT devices that may be connected, along with the ad hoc nature of such systems, often exacerbates the situation. Security and privacy have emerged as significant challenges for managing IoT. Recent work has demonstrated that deep learning algorithms are very efficient for conducting security analysis of IoT systems and have many advantages compared with the other methods. This paper aims to provide a thorough survey related to deep learning applications in IoT for security and privacy concerns. Our primary focus is on deep learning enhanced IoT security. First, from the view of system architecture and the methodologies used, we investigate applications of deep learning in IoT security. Second, from the security perspective of IoT systems, we analyse the suitability of deep learning to improve security. Finally, we evaluate the performance of deep learning in IoT system security.

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Section: Behaviour Modelling and Analysis Of Iot Using Deep Learningmentioning

confidence: 99%

Deep Learning-Based Security Behaviour Analysis in IoT Environments: A Survey

Yue

Legg

et al. 2021

Security and Communication Networks

Self Cite

View full text Add to dashboard Cite

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“…Firstly, two parameters are introduced into the scheme, which can effectively resist the weak randomness attack of Bitcoin ECDSA; Secondly, the scheme uses the Hamming weight of Hash function instead of Hash value to sign, which avoids the inverse operation in the signing and verification stage. Li et al [26] proposed a new digital forensics (DF) investigation framework based on blockchain in the environment of Internet of things and social systems, which can provide proof of existence and privacy protection for evidence item inspection. Based on the Internet of things forensics chain (IoTFC), the framework can provide good authenticity, invariance, traceability, flexibility and distributed trust forensics investigation between evidence obligees and reviewers.…”

Section: Blockchain and Digital Twins Techniquementioning

confidence: 99%

Blockchain-Based BIM Digital Project Management Mechanism Research

Sun

Wang

2021

IEEE Access

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The construction industry lacks a comprehensive and overall scheme for the use and management of building information modeling (BIM) in the whole building life cycle, especially the use of BIM technology for asset management and facility management. However, there is little understanding and implementation of enterprise BIM. BIM influences and changes the new project management mode of the whole life cycle of construction projects from design to construction. The safety, audit, responsibility and value of BIM are the forward-looking problems in current BIM, but it is difficult to realize the whole process value management based on the contribution of all parties, it is not conducive to the popularization and application of BIM. From the perspective of new technology and the whole life cycle, this paper analyzes the development and promotion of Blockchain technology to construction projects, and puts forward the fusion point of BIM and Blockchain technology: multi-user, multi-stage, multi-target data fusion and traceability mechanism; It is a consensus process model of multi-party collaboration, interest balance, non-destructive transmission of building information, responsibility traceability and customer satisfaction. It realizes the supporting framework and implementation ideas of BIM and Blockchain technology in construction projects from the aspects of design technology, construction management, material scheduling and whole life cycle construction. This paper will provide some new ideas for the whole life cycle collaborative management of digital construction.

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“…Data according to the weights and bias, in OLSR routing protocol, "sends HELLO packets" subroutines in rebuilding the single hidden layer neural network, all nodes and the entire network movement speed data as the input parameters of neural network, and can output the HELLO broadcast cycle under this movement speed which will have a kind of routing performance, including energy consumption, AEED, PDR, jitter, throughput, etc. By combining the above information and making use of multiattribute decision, the optimal HELLO broadcast cycle is obtained, and the result is taken as the time of the next HELLO package broadcast [18][19][20].…”

Section: Mac Layer Energy Consumption and Routing Protocol Algorithm mentioning

confidence: 99%

MAC Layer Energy Consumption and Routing Protocol Optimization Algorithm for Mobile Ad Hoc Networks

Liu

2021

Complexity

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Mobile ad hoc network is a network composed of mobile terminals without infrastructure. Due to its fast-networking ability, it is widely used in smart cities, car networking, military, agriculture, medicine, and other fields. Routing technology is a key technology in the field of MANET (mobile ad hoc network). The energy consumption is optimized through the technical network simulator NS-3, and the nodes in the MANET routing protocol can accurately simulate the problem, thereby optimizing the MAC layer of important research tools. This article combines the advantages of the lithium-ion (lithium) battery model. Compared with the KiBaM battery model, the effective charge in the KiBaM model simulates the output voltage well, which can reflect the battery capacity effect rate and the recovery effect of the lithium-ion-KiBaM battery model. The model can respond to the characteristics of the output voltage as the society gets lower and lower. In order to solve the problem that the analytic solution of differential equations cannot be obtained in the model, a numerical solution of the optimization algorithm is proposed based on the implicit Runge–Kutta method. The MAC layer energy consumption and routing protocol optimization algorithm proposed in this paper can be applied well in various fields.

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Blockchain-Based Digital Forensics Investigation Framework in the Internet of Things and Social Systems

Cited by 86 publications

References 38 publications

Deep Learning-Based Security Behaviour Analysis in IoT Environments: A Survey

Deep Learning-Based Security Behaviour Analysis in IoT Environments: A Survey

Blockchain-Based BIM Digital Project Management Mechanism Research

MAC Layer Energy Consumption and Routing Protocol Optimization Algorithm for Mobile Ad Hoc Networks

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