Towards a Secure Signature Scheme Based on Multimodal Biometric Technology: Application for IOT Blockchain Network

Hassen, Oday A.; Abdulhussein, Ansam A.; Darwish, Saad M.; Othman, Zulaiha Ali; Tiun, Sabrina; Lotfy, Yasmin A.

doi:10.3390/sym12101699

Cited by 21 publications

(7 citation statements)

References 42 publications

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“…Benefitted from the feature fusion, the multi-modal system increases recognition accuracy by more than 50% compared to that using only face or voice features. To strengthen network security, Hassen et al [ 47 ] extracted a private key from multi-modal biometrics (fingerprint and finger-vein) to authenticate and validate blockchain transactions. Experiment results demonstrate that the proposed method attains a high security level in defending spoofing and signature forgery with high throughput and low latency.…”

Section: Biometric-based Systems For Iot-oriented Authenticationmentioning

confidence: 99%

Biometrics for Internet-of-Things Security: A Review

Yang

Wang

Sahri

et al. 2021

Sensors

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The large number of Internet-of-Things (IoT) devices that need interaction between smart devices and consumers makes security critical to an IoT environment. Biometrics offers an interesting window of opportunity to improve the usability and security of IoT and can play a significant role in securing a wide range of emerging IoT devices to address security challenges. The purpose of this review is to provide a comprehensive survey on the current biometrics research in IoT security, especially focusing on two important aspects, authentication and encryption. Regarding authentication, contemporary biometric-based authentication systems for IoT are discussed and classified based on different biometric traits and the number of biometric traits employed in the system. As for encryption, biometric-cryptographic systems, which integrate biometrics with cryptography and take advantage of both to provide enhanced security for IoT, are thoroughly reviewed and discussed. Moreover, challenges arising from applying biometrics to IoT and potential solutions are identified and analyzed. With an insight into the state-of-the-art research in biometrics for IoT security, this review paper helps advance the study in the field and assists researchers in gaining a good understanding of forward-looking issues and future research directions.

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Section: Biometric-based Systems For Iot-oriented Authenticationmentioning

confidence: 99%

Biometrics for Internet-of-Things Security: A Review

Yang

Wang

Sahri

et al. 2021

Sensors

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“…Physiological characteristics include those retrieved from the human body, such as iris [4], faces [5,6], retinas, veins [7], fingerprints [8][9][10][11], palm prints, finger knuckle print, and DNA, ECG [12][13][14][15], while behavioral characteristics include voice, stride, signature, and keystroke [16][17][18][19][20]. Biometrics traits are commonly employed in systems such as Security in IoT [21][22][23][24][25], e-banking [26][27][28][29], cloud security [30][31][32][33], access control [34][35][36][37], network security systems [38][39][40][41][42], and ID cards [43][44][45][46][47], and other applications related to IoT [48][49][50]…”

Section: Introductionmentioning

confidence: 99%

DeepKnuckle: Deep Learning for Finger Knuckle Print Recognition

et al. 2022

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Biometric technology has received a lot of attention in recent years. One of the most prevalent biometric traits is the finger-knuckle print (FKP). Because the dorsal region of the finger is not exposed to surfaces, FKP would be a dependable and trustworthy biometric. We provide an FKP framework that uses the VGG-19 deep learning model to extract deep features from FKP images in this paper. The deep features are collected from the VGG-19 model’s fully connected layer 6 (F6) and fully connected layer 7 (F7). After applying multiple preprocessing steps, such as combining features from different layers and performing dimensionality reduction using principal component analysis (PCA), the extracted deep features are put to the test. The proposed system’s performance is assessed using experiments on the Delhi Finger Knuckle Dataset employing a variety of common classifiers. The best identification result was obtained when the Artificial neural network (ANN) classifier was applied to the principal components of the averaged feature vector of F6 and F7 deep features, with 95% of the data variance preserved. The findings also demonstrate the feasibility of employing these deep features in an FKP recognition system.

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“…Blockchain technology combined with a decentralized database offers the practical concept of realizing decentralized current MS. However, in the industrial sector, blockchain technology is only a concept and lacks implementation for the current MS [13][14][15]. It is still challenging to provide a consensus technique suitable for applications [16] in the industrial domain with reliable validation techniques.…”

Section: Introductionmentioning

confidence: 99%

An Implementation of Trust Chain Framework with Hierarchical Content Identifier Mechanism by Using Blockchain Technology

Chen

Irawan

Hsu

et al. 2022

Sensors

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Advances in information technology (IT) and operation technology (OT) accelerate the development of manufacturing systems (MS) consisting of integrated circuits (ICs), modules, and systems, toward Industry 4.0. However, the existing MS does not support comprehensive identity forensics for the whole system, limiting its ability to adapt to equipment authentication difficulties. Furthermore, the development of trust imposed during their crosswise collaborations with suppliers and other manufacturers in the supply chain is poorly maintained. In this paper, a trust chain framework with a comprehensive identification mechanism is implemented for the designed MS system, which is based and created on the private blockchain in conjunction with decentralized database systems to boost the flexibility, traceability, and identification of the IC-module-system. Practical implementations are developed using a functional prototype. First, the decentralized application (DApp) and the smart contracts are proposed for constructing the new trust chain under the proposed comprehensive identification mechanism by using blockchain technology. In addition, the blockchain addresses of IC, module, and system are automatically registered to InterPlanetary File System (IPFS), individually. In addition, their corresponding hierarchical CID (content identifier) values are organized by using Merkle DAG (Directed Acyclic Graph), which is employed via the hierarchical content identifier mechanism (HCIDM) proposed in this paper. Based on insights obtained from this analysis, the trust chain based on HCIDM can be applied to any MS system, for example, this trust chain could be used to prevent the counterfeit modules and ICs employed in the monitoring system of a semiconductor factory environment. The evaluation results show that the proposed scheme could work in practice under the much lower costs, compared to the public blockchain, with a total cost of 0.002094 Ether. Finally, this research is developed an innovation trust chain mechanism that could be provided the system-level security for any MS toward Industrial 4.0 in order to meet the requirements of both manufacturing innovation and product innovation in Sustainable Development Goals (SDGs).

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Towards a Secure Signature Scheme Based on Multimodal Biometric Technology: Application for IOT Blockchain Network

Cited by 21 publications

References 42 publications

Biometrics for Internet-of-Things Security: A Review

Biometrics for Internet-of-Things Security: A Review

DeepKnuckle: Deep Learning for Finger Knuckle Print Recognition

An Implementation of Trust Chain Framework with Hierarchical Content Identifier Mechanism by Using Blockchain Technology

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