Aggregatable Certificateless Designated Verifier Signature

In recent years, the Internet of Things (IoT) devices have become increasingly deployed in many industries and generated a large amount of data that needs to be processed in a timely and efficient manner. Using aggregate signatures, it provides a secure and efficient way to handle large numbers of digital signatures with the same message. Recently, the privacy issue has been concerned about the topic of data sharing on the cloud. To provide the integrity, authenticity, authority, and privacy on the data sharing in the cloud storage, the notion of an aggregatable certificateless designated verifier signature scheme (ACLDVS) was proposed. ACLDVS also is a perfect tool to enable efficient privacy-preserving authentication systems for IoT and or the vehicular ad hoc networks (VANET). Our concrete scheme was proved to be secured underling of the Computational Diffie-Hellman assumption. Compared to other related schemes, our scheme is efficient, and the signature size is considerably short

Securing IT/OT Links for Low Power IIoT Devices:Design considerations for industry 4.0

Manufacturing is facing a host of new security challenges due to the convergence of information technology (IT) and operational technology (OT) in the industry. This article addresses the challenges that arise due to the use of low power Industrial Internet of Things (IIoT) devices in modular manufacturing systems of Industry 4.0. First, we analyze security challenges concerning the manufacturing execution system (MES) and programmable logic controllers (PLC) in IIoT through a selective literature review. Second, we present an exploratory case study to determine a protocol for cryptographic key management and key exchange suitable for the Smart Production Lab of Aalborg University (a learning cyber-physical factory). Finally, we combine the findings of the case study with a quality function deployment (QFD) method to determine design requirements for Industry 4.0. We identify specific requirements from both the high-level domain of factory capabilities and the low-level domain of cryptography and translate requirements between these domains using a QFD analysis. The recommendations for designing a secure smart factory focus on how security can be implemented for low power and low-cost IIoT devices. Even though there have been a few studies on securing IT to OT data exchange, we conclude that the field is not yet in a state where it can be applied in practice with confidence

APEX2S: A Two-Layer Machine Learning Model for Discovery of host-pathogen protein-protein Interactions on Cloud-based Multiomics Data

Presented by the avalanche of biological interactions data, computational biology is now facing greater challenges on big data analysis and solicits more studies to mine and integrate cloud-based multiomics data, especially when the data are related to infectious diseases. Meanwhile, machine learning techniques have recently succeeded in different computational biology tasks. In this article, we have calibrated the focus for host-pathogen protein-protein interactions study, aiming to apply the machine learning techniques for learning the interactions data and making predictions. A comprehensive and practical workflow to harness different cloud-based multiomics data is discussed. In particular, a novel two-layer machine learning model, namely APEX2S, is proposed for discovery of the protein-protein interactions data. The results show that our model can better learn and predict from the accumulated host-pathogen protein-protein interactions

Security of IoT in 5G Cellular Networks: A Review of Current Status, Challenges and Future Directions

The Internet of Things (IoT) refers to a global network that integrates real life physical objects with the virtual world through the Internet for making intelligent decisions. In a pervasive computing environment, thousands of smart devices, that are constrained in storage, battery backup and computational capability, are connected with each other. In such an environment, cellular networks that are evolving from 4G to 5G, are set to play a crucial role. Distinctive features like high bandwidth, wider coverage, easy connectivity, in-built billing mechanism, interface for M2M communication, etc., makes 5G cellular network a perfect candidate to be adopted as a backbone network for the future IoT. However, due to resource constrained nature of the IoT devices, researchers have anticipated several security and privacy issues in IoT deployments over 5G cellular network. Off late, several schemes and protocols have been proposed to handle these issues. This paper performs a comprehensive review of such schemes and protocols proposed in recent times. Different open security issues, challenges and future research direction are also summarized in this review paper

A blockchain-based Shamir's Threshold Cryptography Scheme for data protection in Industrial internet of Things settings

The Industrial Internet of Things (IIoT), a typical Internet of Things (IoT) application, integrates the global industrial system with other advanced computing, analysis, and sensing technologies through Internet connectivity. Due to the limited storage and computing capacity of edge and IIoT devices, data sensed and collected by these devices are usually stored in the cloud. Encryption is commonly used to ensure privacy and confidentiality of IIoT data. However, the key used for data encryption and decryption is usually directly stored and managed by users or third-party organizations, which has security and privacy implications. To address this potential security and privacy risk, we propose a Shamir threshold cryptography scheme for IIoT data protection using blockchain: STCChain. Specifically, in our solution, the edge gateway uses a symmetric key to encrypt the data uploaded by the IoT device and stores it in the cloud. The symmetric key is protected by a private key generated by the edge gateway. To prevent the loss of the private key and privacy leakage, we use a Shamir secret sharing algorithm to divide the private key, encrypt it, and publish it on the blockchain. We implement a prototype of STCChain using Xuperchain, and the results show that STCChain can effectively prevent attackers from stealing data as well as ensuring the security of the encryption key

Unleashing the power of internet of things and blockchain: A comprehensive analysis and future directions.

As the fusion of the Internet of Things (IoT) and blockchain technology advances, it is increasingly shaping diverse fields. The potential of this convergence to fortify security, enhance privacy, and streamline operations has ignited considerable academic interest, resulting in an impressive body of literature. However, there is a noticeable scarcity of studies employing Latent Dirichlet Allocation (LDA) to dissect and categorize this field. This review paper endeavours to bridge this gap by meticulously analysing a dataset of 4455 journal articles drawn solely from the Scopus database, cantered around IoT and blockchain applications. Utilizing LDA, we have extracted 14 distinct topics from the collection, offering a broad view of the research themes in this interdisciplinary domain. Our exploration underscores an upswing in research pertaining to IoT and blockchain, emphasizing the rising prominence of this technological amalgamation. Among the most recurrent themes are IoT and blockchain integration in supply chain management and blockchain in healthcare data management and security, indicating the significant potential of this convergence to transform supply chains and secure healthcare data. Meanwhile, the less frequently discussed topics include access control and management in blockchain-based IoT systems and energy efficiency in wireless sensor networks using blockchain and IoT. To the best of our knowledge, this paper is the first to apply LDA in the context of IoT and blockchain research, providing unique perspectives on the existing literature. Moreover, our findings pave the way for proposed future research directions, stimulating further investigation into the less explored aspects and sustaining the growth of this dynamic field

MAKE-IT—A Lightweight Mutual Authentication and Key Exchange Protocol for Industrial Internet of Things

Continuous development of the Industrial Internet of Things (IIoT) has opened up enormous opportunities for the engineers to enhance the efficiency of the machines. Despite the development, many industry administrators still fear to use Internet for operating their machines due to untrusted nature of the communication channel. The utilization of internet for managing industrial operations can be widespread adopted if the authentication of the entities are performed and trust is ensured. The traditional schemes with their inherent security issues and other complexities, cannot be directly deployed to resource constrained network devices. Therefore, we have proposed a strong mutual authentication and secret key exchange protocol to address the vulnerabilities of the existing schemes. We have used various cryptography operations such as hashing, ciphering, and so forth, for providing secure mutual authentication and secret key exchange between different entities to restrict unauthorized access. Performance and security analysis clearly demonstrates that the proposed work is energy efficient (computation and communication inexpensive) and more robust against the attacks in comparison to the traditional scheme