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Insider threats in Internet of Things (IoT) networks pose significant risks, as compromised devices can misuse their privileges to cause substantial harm. Centralized methods for insider threat detection in IoT devices are critical for identifying and mitigating insider risks. User behavior, such as access patterns, login times and data transmission, is profiled using machine learning algorithms to detect deviations that may indicate insider risks. However, training a model that generalizes across different data sources is challenging due to data heterogeneity, which can lead to a drift in performance. This paper introduces a decentralized approach called federated learning (FL) to address these challenges. An advanced privacy-preserving method is proposed for detecting and reducing insider threats in IoT devices. The process begins with a trust authority generating a random digital certificate using the hybrid Rivest–Shamir–Adleman and elliptic curve digital signature algorithm for IoT user registration. Node clustering is performed using the ordering points to identify the clustering structure with centroid refinement algorithm, ensuring data privacy by transmitting only cluster heads to local models. Additionally, the federated automatic weight optimization hash-based message authentication code with secure hash algorithm is introduced to further strengthen protection. The experimental results show accuracy rates of 98.85% on the simulated dataset and 83.74% on the X-IIoTID test dataset. These finding facilitates the effectiveness of the proposed solution in terms of accuracy, time, throughput, node scalability and overall performance. The results indicate that the proposed model outperforms other prominent approaches in the field. [ABSTRACT FROM AUTHOR]

Integration of the internet of things (IoT) and robotics into the internet of robotic things (IoRT) presents inherent security and trust challenges. This article introduces an innovative blockchain-centred framework designed to address these challenges. By harnessing the features of oneM2M and blockchain technology, the architecture enhances accessibility, security and data management within IoRT. Encompassing key aspects such as data flow, user authentication, health data management and security, the proposed framework ensures compliance with the oneM2M standard. A notable contribution is the integration of a private blockchain network on ZedBoard development boards, focusing on access control and data integrity verification. External IoT data are securely transmitted to a cloud platform hosted on AWS, ensuring streamlined data management with minimal impact on the resources of ZedBoards. In a stride towards bolstering IoRT security, the study implements elliptic curve digital signature algorithm (ECDSA) with Radix-2w optimizations on ZedBoards, demonstrating a significant 58.63% reduction in addition operation costs compared to standard ECDSA. The practical implementation on ZedBoards validates the effectiveness of this approach, offering a comprehensive solution for securing IoRT networks. This research caters to industries relying on the seamless integration of IoT and robotics, concluding with noteworthy findings and suggesting potential avenues for future research, including optimizations in hardware/software co-design for ECDSA on Zynq boards.

Physically unclonable functions (PUFs) are crucial for enhancing cybersecurity by providing unique, intrinsic identifiers for electronic devices, thus ensuring their authenticity and preventing unauthorized cloning. The SRAM-PUF, characterized by its simple structure and ease of implementation in various scenarios, has gained widespread usage. The soft-decision Reed–Muller (RM) code, an error correction code, is commonly employed in these designs. This paper introduces the design of an RM code soft-decision attack algorithm to reveal its potential security risks. To address this problem, we propose a soft-decision SRAM-PUF structure based on the elliptic curve digital signature algorithm (ECDSA). To improve the processing speed of the proposed secure SRAM-PUF, we propose a custom ECDSA scheme. Further, we also propose a universal architecture for the critical operations in ECDSA, elliptic curve scalar multiplication (ECSM), and elliptic curve double scalar multiplication (ECDSM) based on the differential addition chain (DAC). For ECSMs, iterations can be performed directly; for ECDSMs, a two-dimensional DAC is constructed through precomputation, followed by iterations. Moreover, due to the high similarity of ECSM and ECDSM data paths, this universal architecture saves hardware resources. Our design is implemented on a field-programmable gate array (FPGA) and an application-specific integrated circuit (ASIC) using a Xilinx Virtex-7 and an TSMC 40 nm process. Compared to existing research, our design exhibits a lower bit error rate ( 2.7 × 10 − 10 ) and better area–time performance (3902 slices, 6.615 μ s ECDSM latency). [ABSTRACT FROM AUTHOR]

Physically unclonable functions (PUFs) are crucial for enhancing cybersecurity by providing unique, intrinsic identifiers for electronic devices, thus ensuring their authenticity and preventing unauthorized cloning. The SRAM-PUF, characterized by its simple structure and ease of implementation in various scenarios, has gained widespread usage. The soft-decision Reed–Muller (RM) code, an error correction code, is commonly employed in these designs. This paper introduces the design of an RM code soft-decision attack algorithm to reveal its potential security risks. To address this problem, we propose a soft-decision SRAM-PUF structure based on the elliptic curve digital signature algorithm (ECDSA). To improve the processing speed of the proposed secure SRAM-PUF, we propose a custom ECDSA scheme. Further, we also propose a universal architecture for the critical operations in ECDSA, elliptic curve scalar multiplication (ECSM), and elliptic curve double scalar multiplication (ECDSM) based on the differential addition chain (DAC). For ECSMs, iterations can be performed directly; for ECDSMs, a two-dimensional DAC is constructed through precomputation, followed by iterations. Moreover, due to the high similarity of ECSM and ECDSM data paths, this universal architecture saves hardware resources. Our design is implemented on a field-programmable gate array (FPGA) and an application-specific integrated circuit (ASIC) using a Xilinx Virtex-7 and an TSMC 40 nm process. Compared to existing research, our design exhibits a lower bit error rate (2.7×10−10) and better area–time performance (3902 slices, 6.615 μs ECDSM latency).

Lattice attacks can compromise the security of encryption algorithms used in blockchain networks, allowing attackers to tamper with transaction records, steal private keys, and execute other forms of attacks. With symmetric encryption, both parties can encrypt and decrypt messages using the same key. Lattice attacks on digital signature algorithms (ECDSA) involve forming a basis and setting a target vector from signatures, then solving the closest vector problem (CVP) or shortest vector problem (SVP) in the generated lattice to obtain the private key. Prior research focused on obtaining leakage information from the signature's random nonce to facilitate a CVP or SVP solution. This study establishes a clear boundary for a successful ECDSA attack and introduces a "double basis" lattice version that expands the boundary or reduces the necessary signatures by nearly half with the same lattice rank. To approach the boundary, a heuristic strategy is employed to shift the target vector in different directions with a feasible step size, using tests on the Trusted Platform Module (TPM) 2.0 ECDSA. The distance from the closest moved target vector to the boundary is reduced by a ratio of 424 to 179 to the minimal length of orthogonal vectors in the formed basis. Experimental results show that moving attempts in two directions with the original basis and 84 signatures take approximately 247.7 s on the experiment computer. [ABSTRACT FROM AUTHOR]

In this paper, we introduce a series of attacks on DSA schemes that, under certain assumptions, can expose the secret key when one or more signed messages are accessible. By utilizing these signed messages, we construct a system of linear congruences with at most one solution smaller than a specific bound, which can be efficiently determined using Babai's Nearest Plane Algorithm. As a case study, we provide a successful attack on secp161k1, assuming that a particular multiple of an ephemeral key is 161 bits long. [ABSTRACT FROM AUTHOR]

The concept of blockchain has sparked hopes in the field of communication security between IoT devices. In blockchain, all network nodes need to verify its legitimacy before accepting and recording it. Users of HIoTNs (Hierarchical IoT Networks) want to get real-time data from specific sensors in a specific implementation. Users need authentications at GNs for obtaining their required services. On successful authentications, parties on either sides of communication can create secret session keys for safe communications. Critical issues like this in HIoTNs are addressed in this work by its novel proposed multimodal-biometrics based lightweight user authentications. The scheme based on block chain technologies is called SMUAAKMPs (Secure Multimodal Biometrics-based User Anonymous Authenticated Key Management Protocols). ECDSAs (Elliptic Curve Digital Signature Algorithms) are utilised for devices and GNs, to generate public and private keys. In addition, multimodal biometric verifications are executed using fuzzy commitment approaches. The fuzzy commitment technique is then used to validate the biometric authentication using the segmented face. This work's detailed security analyses use ROR (Real-Or-Random) models where formal security verifications are done by software verification tool AVISPAs (Automated Validation of Internet Security Protocols and Applications). Informal security analyses show that the proposed SMUAAKMPs withstand multiple known attacks. The system also provides improved safety and functionalities at reduced costs in computations and communications when compared to UABKMPs, UAKMPs, and SMBUAKEPs. • Users of HIoTNs (Hierarchical IoT Networks) want to get real-time data from specific sensors in a specific implementation. • Secure Multimodal Biometrics-based User Anonymous Authenticated Key Management Protocol (SMUAAKMPs) block chain technologies. • Improved safety and reduced costs in computations and communications when compared to UABKMPs, UAKMPs, and SMBUAKEPs. [ABSTRACT FROM AUTHOR]

The privacy and utility are treated as a major factor in influencing the role of data privacy preservation in cloud environments. There exists a trade-off between these two factors, where one factor should compromise its functionality over the other. It is hence necessary to maintain both utility and privacy for a data offloaded or accessed across cloud computing environment. In this paper, we develop a utility privacy model that established utility using Deep Adaptive Clustering (DAC) and privacy using Elliptic Curve Digital Signature Algorithm (ECDSA). The utility is performed using clustering of the input datasets using DAC and the privacy is maintained using ECDSA. The simulation is conducted on specific datasets to test the efficacy of the model and the results shows improved accuracy on clustering, and efficient privacy metrics than existing methods. [ABSTRACT FROM AUTHOR]

In this paper, we present a deterministic attack on (EC)DSA signature scheme, providing that several signatures are known such that the corresponding ephemeral keys share a certain amount of bits without knowing their value. By eliminating the shared blocks of bits between the ephemeral keys, we get a lattice of dimension equal to the number of signatures having a vector containing the private key. We compute an upper bound for the distance of this vector from a target vector, and next, using Kannan's enumeration algorithm, we determine it and hence the secret key. The attack can be made highly efficient by appropriately selecting the number of shared bits and the number of signatures. [ABSTRACT FROM AUTHOR]