Secure Internet Of Things Data Research Articles

Tiger Tally: A secure IoT data management approach based on redactable blockchain

Blockchain-based Internet of Things (IoT) data management is increasingly ubiquitous across smart cities, supply chains, e-health and other domains. The immutability of blockchain is crucial to securing these IoT data management systems. In actual application scenarios, redacting the on-chain IoT data is still desired or even legally required. Various redactable blockchain technologies have been suggested for breaking immutability and redacting on-chain data. However, conventional redactable blockchain technologies incur security and performance degradations like redact privileges abuse and key exposure, prior art merely reactively corrects rather than fundamentally forestalling such misuse. In this paper, we rethink the conflict between the immutability and redaction of blockchain-based IoT data systems and propose Tiger Tally as a secure redactable architecture to fundamentally forestall these vulnerabilities. Tiger Tally introduces a novel Targeted Policy-Based Chameleon Hash, along with tokenized redact privileges, to form integrated cryptography and access control mechanisms. We further propose a full lifecycle redactable blockchain framework with rigorous security proofs to instantiate Tiger Tally. Furthermore, to meet its practical needs, we introduce the proposed Tiger Tally to the comprehensive IoT data workflows. At last, proof-of-concept implementation and performance evaluation demonstrate that our Tiger Tally is practical for IoT data management systems and greatly reduces the time overhead caused by malicious modification by at least 73.0 % or even 3.26 times at the cost of 5.4 % incremental space overhead.

SDACS: Blockchain-Based Secure and Dynamic Access Control Scheme for Internet of Things.

With the rapid growth of the Internet of Things (IoT), massive terminal devices are connected to the network, generating a large amount of IoT data. The reliable sharing of IoT data is crucial for fields such as smart home and healthcare, as it promotes the intelligence of the IoT and provides faster problem solutions. Traditional data sharing schemes usually rely on a trusted centralized server to achieve each attempted access from users to data, which faces serious challenges of a single point of failure, low reliability, and an opaque access process in current IoT environments. To address these disadvantages, we propose a secure and dynamic access control scheme for the IoT, named SDACS, which enables data owners to achieve decentralized and fine-grained access control in an auditable and reliable way. For access control, attribute-based control (ABAC), Hyperledger Fabric, and interplanetary file system (IPFS) were used, with four kinds of access control contracts deployed on blockchain to coordinate and implement access policies. Additionally, a lightweight, certificateless authentication protocol was proposed to minimize the disclosure of identity information and ensure the double-layer protection of data through secure off-chain identity authentication and message transmission. The experimental and theoretical analysis demonstrated that our scheme can maintain high throughput while achieving high security and stability in IoT data security sharing scenarios.

Decentralized IoT Data Authentication with Signature Aggregation

The rapid expansion of the Internet of Things (IoT) has introduced significant challenges in data authentication, necessitating a balance between scalability and security. Traditional approaches often rely on third parties, while blockchain-based solutions face computational and storage bottlenecks. Our novel framework employs edge aggregating servers and Ethereum Layer 2 rollups, offering a scalable and secure IoT data authentication solution that reduces the need for continuous, direct interaction between IoT devices and the blockchain. We utilize and compare the Nova and Risc0 proving systems for authenticating batches of IoT data by verifying signatures, ensuring data integrity and privacy. Notably, the Nova prover significantly outperforms Risc0 in proving and verification times; for instance, with 10 signatures, Nova takes 3.62 s compared to Risc0’s 369 s, with this performance gap widening as the number of signatures in a batch increases. Our framework further enhances data verifiability and trust by recording essential information on L2 rollups, creating an immutable and transparent record of authentication. The use of Layer 2 rollups atop a permissionless blockchain like Ethereum effectively reduces on-chain storage costs by approximately 48 to 57 times compared to direct Ethereum use, addressing cost bottlenecks efficiently.

Enhancing IoT Data Security: Using the Blockchain to Boost Data Integrity and Privacy

The Internet of Things (IoT) is a technology that can connect billions of devices or “things” to other devices (machine to machine) or even to people via an existing infrastructure. IoT applications in real-world scenarios include smart cities, smart houses, connected appliances, shipping, monitoring, smart supply chain management, and smart grids. As the number of devices all over the world is increasing (in all aspects of daily life), huge amounts of data are being produced as a result. New issues are therefore arising from the use and development of current technologies, regarding new applications, regulation, cloud computing, security, and privacy. The blockchain has shown promise in terms of securing and preserving the privacy of users and data, in a decentralized manner. In particular, Hyperledger Fabric v2.x is a new generation of blockchain that is open source and offers versatility, modularity, and performance. In this paper, a blockchain as a service (BaaS) application based on Hyperledger Fabric is presented to address the security and privacy challenges associated with the IoT. A new architecture is introduced to enable this integration, and is developed and deployed, and its performance is analyzed in real-world scenarios. We also propose a new data structure with encryption based on public and private keys for enhanced security and privacy.

An Enhanced and Dynamic Key AES Algorithm for Internet of Things Data Security

Internet of Things (IoT) applications have become ubiquitous in various aspects of daily life, including smart homes, healthcare, and other areas where human assistance is crucial. However, the valuable real-world data collected by IoT devices and transmitted over the Internet have become a prime target for numerous malicious actors and hackers. Therefore, ensuring secure communication to prevent unauthorized access to this transmitted data is of paramount importance. This research is dedicated to the development of a robust security system for IoT to protect sensor data. Traditionally, IoT systems have relied on fixed encryption keys shared between transmitters and receivers, which presented vulnerabilities as these keys could be easily compromised. In this study, we introduce an enhanced version of the AES algorithm with dynamic keys. In this modified algorithm, each cycle involves the XOR operation of four keywords with the sequence number. Each round of the AES algorithm incorporates various transformations, including DivideSwap, SubBytes, ShiftRows, MixColumns, and AddRoundKey, with the exception of the final round, which excludes the MixColumns operation. To implement and test this upgraded security approach, we utilized hardware components such as the Arduino Uno, ESP8266, and DHT11 sensors. The enhanced AES algorithm was integrated into the Arduino Uno to secure sensor data before transmission across the network. The results of our analysis demonstrate that the proposed IoT security method presents a significantly higher level of cryptographic resilience compared to the traditional AES algorithm, making it a robust solution for safeguarding IoT data.

A Comparative Study of BFV and CKKs Schemes to Secure IoT Data Using TenSeal and Pyfhel Homomorphic Encryption Libraries

Internet of things (IoT) devices and applications are on the rise, generating large amounts of sensitive and confidential data that need to be processed securely. Due to resource constraints, the data generated is often stored and processed in the cloud. The drawback of data cloud storage and processing is the fact that it can be hacked, leaked, or sold by cloud companies. Fully homomorphic encryption (FHE) allows computation on encrypted data using basic mathematical operations and has recently been successfully implemented using schemes and libraries with better performance. In this paper, the authors propose a mixture of edge-cloud-based security schemes using FHE to secure IoT data. The authors evaluate the performance of two FHE schemes (BFV and CKKS) based on data: encoding speed, encryption speed, arithmetic operations (addition and multiplication) speed, and decryption decoding speed using two Python libraries (TenSEAL and PyFHEl). The encryption and decryption are done at the edge node using a Raspberry Pi 4, while the processing is done at the cloud node using a laptop.

Enhancing IoT Data Security through Multilayered Approach: Chaotic Map, DNA Sequencing, Blockchain Intergration

The rapid proliferation of the Internet of Things (IoT) devices has ushered in an era of unprecedented connectivity, yet it also poses significant challenges in terms of data security and privacy. In this research, a robust and innovative approach is proposed to address these challenges by introducing a multi-layered security model integrating three powerful technologies: chaotic maps, DNA computing, and block chain technology to fortify IoT data protection. The key objective of proposed technique is to offer security to data at multiple levels while minimizing the Encryption Time (ET) and Decryption Time (DT). In the proposed work, two types of inputs i.e., textual data and medical image data is taken upon which proposed technique is implemented. The key innovation lies in the generation of binary keys from chaotic maps, making it different from traditional chaotic key methods, thereby establishing a unique and robust foundation for encryption. Furthermore, to enhance the encryption process, a dual layer of security is implemented through DNA sequencing and blockchain, ensuring an unprecedented level of data integrity and confidentiality. Notably, the blockchain phase utilizes SHA-256 for generating hash values, fortifying the blocks with an additional layer of cryptographic strength. This novel approach offers a comprehensive and sophisticated solution, effectively mitigating security concerns in IoT ecosystems. By combining the power of chaotic maps, DNA encoding, and blockchain technology, proposed model stands at the forefront of IoT data security, providing a resilient defence against contemporary and future threats.The performance of proposed approach is examined and validated in terms of ET and DT in MATLAB software. Simulating results revealed that proposed model is outperforming other similar models by attaining lowest ET and DT time for both text and image data.

N-Accesses: A Blockchain-Based Access Control Framework for Secure IoT Data Management.

With the rapid advancement of network communication and big data technologies, the Internet of Things (IoT) has permeated every facet of our lives. Meanwhile, the interconnected IoT devices have generated a substantial volume of data, which possess both economic and strategic value. However, owing to the inherently open nature of IoT environments and the limited capabilities and the distributed deployment of IoT devices, traditional access control methods fall short in addressing the challenges of secure IoT data management. On the one hand, the single point of failure issue is inevitable for the centralized access control schemes. On the other hand, most decentralized access control schemes still face problems such as token underutilization, the insecure distribution of user permissions, and inefficiency.This paper introduces a blockchain-based access control framework to address these challenges. Specifically, the proposed framework enables data owners to host their data and achieves user-defined lightweight data management. Additionally, through the strategic amalgamation of smart contracts and hash-chains, our access control scheme can limit the number of times (i.e., n-times access) a user can access the IoT data before the deadline. This also means that users can utilize their tokens multiple times (predefined by the data owner) within the deadline, thereby improving token utilization while ensuring strict access control. Furthermore, by leveraging the intrinsic characteristics of blockchain, our framework allows data owners to gain capabilities for auditing the access records of their data and verifying them. To empirically validate the effectiveness of our proposed framework and approach, we conducted extensive simulations, and the experimental results demonstrated the feasibility and efficiency of our solution.

Secure IoT data management and sharing architecture for information security using cryptographic technique

The massive amounts of data produced and gathered by smart devices through the internet support a wide range of applications, considerably improving our daily lives. Data sharing among smart devices must be safeguarded due to the sensitivity of the data involved in the transmission. The Internet of Things (IoT) environment must be protected from unauthorised access due to a variety of variables, including its attractiveness to cybercriminals, previous successful cyber-attacks, and consumers’ perceptions of security and reliability. Blockchain technology appears to be one promising technology that appears to address these security challenges extremely effectively. However, given the volume and rate at which smart devices generate data, Blockchain appears to be inefficient for storing it. The pace of data collection in the IoT context and the speed of transaction confirmation in the Blockchain network are the two key elements behind this. We connect the Blockchain and the Inter-Planetary File System (IPFS) in this study to permit data recording on a distributed storage and a mechanism to restrict access to recorded data to authorised organisations only. Over the Blockchain network, the access policy definition for safe data sharing and cryptographic hash content is stored. The real IoT-generated data, on the other hand, is collected via a distributed storage network, which improves availability and security. The proposed scheme’s analysis and performance evaluation show that it is secure and feasible. Furthermore, simulations are undertaken to assess the operating costs of smart contracts and to test the efficacy and viability of the suggested architecture.

Data Protection in IoT using CoAP based on Enhanced DTLS

The Internet of Things (IoT), refers to all the infrastructures and technologies put in place to operate various objects through an Internet connection, it is about connected objects. One of the most frequently used IoT application protocols is the Constrained Application Protocol (CoAP) that matches restricted computers. CoAP is a solution for in-regulated data formats and a high security to protect government-related data from cyber-attacks. CoAP advises using DTLS (Datagram Transport Layer Security) to provide robust security of the UDP-based TLS edition. Initially, DTLS was planned for conventional networks. Therefore, a heavyweight solution is created by moving the protocols over the resource-limited computers. Unfortunately, DTLS has some security issues regarding the management of keys and its vulnerability against common cyber-attacks especially Denial of Service (DoS). Thus, a security approach is important to secure CoAP-based IoT infrastructures from these attacks. In our work, we propose to secure IoT data using enhanced DTLS protocol over CoAP. The enhancement DTLS make it possible to prevent DoS and Distributed DoS attacks. In our proposition, we apply a thrusted party (TP) to which we delegate the process of the authentication and authorization of clients. In addition, the TP is responsible of the verification of IP addresses in order to mitigate attackers from flooding the network with fake hello messages

UAV-Assisted Computation Offloading Toward Energy-Efficient Blockchain Operations in Internet of Things

The advances in the Internet of Things (IoT) have provided generous opportunities for various applications, yet the data security concerns need to be specially addressed due to the limited capability of IoT devices. Toward this issue, we propose to deploy a blockchain system with practical Byzantine fault tolerance (PBFT) consensus for IoT data security provisioning. In particular, we conduct profound analyses regarding the PBFT procedure and elaborate on the computation burden therein. Then, an unmanned aerial vehicle (UAV) is leveraged to offload the computation and assist the blockchain operations. The system energy efficiency is introduced as the ratio of the blockchained IoT data amount and energy consumption for the computation and communication in the network. Further, we maximize the system energy efficiency by the joint design of offloading and transmission strategies, as well as the UAV deployment, within a reinforcement learning framework. Finally, simulation results are provided to corroborate the effectiveness of our proposal.

Blockchain integration with the internet of things for the employee performance management

As time went on, technological progress inevitably altered our daily routines. Many new technologies, such as the Internet of Things (IoT) and cryptocurrency, offer revolutionary possibilities. To put it simply, the blockchain is a distributed, public, and auditable database that can be used to record financial transactions. The IoT, or “Internet of Things,” is a system of interconnected electronic devices that can communicate with one another and be remotely monitored and handled. This paper reviews the most recent findings in the field of blockchain and Internet of Things with the goal of examining blockchain as a possible answer to secure IoT data management within supply networks. There is a dearth of literature in the early stages of both blockchain and IoT study because they are such novel topics. The study's findings suggest that in order to improve their leadership quality to intentionally impact employee performance, industry managers should pay attention to human resource management indicators like collaboration, involvement, actualization, perception, and teamwork. This is primarily because of the inherent limitations of IoT devices and the distributed ledger architecture of the blockchain technology. There is potential for IoT to provide many advantages if blockchain capabilities can be optimized for it.

A computer-aided feature-based encryption model with concealed access structure for medical Internet of Things

One of the Internet of Things (IoT) security issues is the secure sharing and granular management of data access. This study recommends a feature-based encryption scheme with a hidden access structure for medical IoT data security. While establishing fine-grained access control of ciphertext data, the system can guarantee clinical client data privacy. First, it is recommended to convert identity-based encryption (IBE) into a feature-based encryption model (FBEM) using a universal conversion technique that supports multi-valued attributes and gates. IBE characteristics could be inherited by the converted FBEM. The conversion method is then used to change the receiver anonymous IBE scheme into the FBEM scheme with concealed access structure. The FBEM model is then used to construct the IoT scenario for the smart medical application. Theoretical analysis and experimental findings reveal that the suggested system provides advantages over prominent systems regarding computing efficiency, storage load, and security when the access structure is disguised.

A Blockchain-based MQTT Protocol Optimization Algorithm

The communication protocol is an important support to realize the communication between equipment and Internet. And it covers all aspects of the IoT (Internet of things) system. To address the security problem of forging or tampering of key data in traditional IoT protocols, this paper designs an improved MQTT (message queue telemetry transmission) protocol that uses blockchain technology to ensure the security of transmitted data in the process of data transmission. Because the information in the blockchain is not tamperable, which in turn ensures that data stored in brokers are not maliciously tampered with. Through simulation experiments, it is proved that this scheme is lightweight, efficient and easy to implement, which helps to protect the security of IoT data.

Security and Privacy Aware Programming Model for IoT Applications in Cloud Environment

The introduction of Internet of Things (IoT) applications into daily life has raised serious privacy concerns among consumers, network service providers, device manufacturers, and other parties involved. This paper gives a high-level overview of the three phases of data collecting, transmission, and storage in IoT systems as well as current privacy-preserving technologies. The following elements were investigated during these three phases:(1) Physical and data connection layer security mechanisms(2) Network remedies(3) Techniques for distributing and storing data. Real-world systems frequently have multiple phases and incorporate a variety of methods to guarantee privacy. Therefore, for IoT research, design, development, and operation, having a thorough understanding of all phases and their technologies can be beneficial. In this Study introduced two independent methodologies namely generic differential privacy (GenDP) and Cluster-Based Differential privacy ( Cluster-based DP) algorithms for handling metadata as intents and intent scope to maintain privacy and security of IoT data in cloud environments. With its help, we can virtual and connect enormous numbers of devices, get a clearer understanding of the IoT architecture, and store data eternally. However, due of the dynamic nature of the environment, the diversity of devices, the ad hoc requirements of multiple stakeholders, and hardware or network failures, it is a very challenging task to create security-, privacy-, safety-, and quality-aware Internet of Things apps. It is becoming more and more important to improve data privacy and security through appropriate data acquisition. The proposed approach resulted in reduced loss performance as compared to Support Vector Machine (SVM) , Random Forest (RF) .

Medical Data Security in IOT Using DNA Cryptography and Insertion Method

The Internet of Things (IOT) system is a network system that communicates with other devices and systems via the web by using any one of the sensors, devices, applications, and other tools. To prevent unauthorized data transmission access, these systems and networks should include a suitable cryptography mechanism. The security of the shared resources on the data communication network is regarded as one of the key challenges. In this paper, the proposed scheme consists of two parts: (i) generating a key using an array of prime numbers based on the RSA algorithm, and (ii) devising a secure communication scheme based on DNA cryptography and Insertion Method. DNA cryptography is a cryptographic technique that uses DNA sequences to encode and decode source data using biological processes. It is an innovative way to protect data from hackers using DNA. The proposed scheme's security analysis shows that it is secure against the relevant threat models and provides a higher level of protection than previous related studies in the literature.

Quality of Service aware secure data transmission model for Internet of Things assisted wireless sensor networks

AbstractWireless sensor networks (WSNs) are the most critical networks in developing various Internet of Things (IoT) based applications. However, such intelligent devices have drawbacks for energy, memory, processing, and computation resources. In addition, achieving Quality of Service (QoS) with secure data transmission (DT) is a significant challenge for WSNs. This article proposes efficient IoT authentication and energy‐aware safe DT models for achieving better QoS and security with lower energy consumption (EC) in WSNs. Initially, the network randomly deploys the sensor nodes (SNs) and performs the registration of the SNs with the base station (BS). Second, the Entropy‐based Jaccard similarity induced fuzzy C‐means clustering (EJS‐FCM) model clusters the SNs based on the intrinsic qualities of nodes. Then the boosted grasshopper optimization algorithm (BGOA) selects the cluster heads (CHs) optimally by considering major fitness parameters such as communication distance, energy, and distance centroid. Following that, an Adler‐32 hashing‐based authentication scheme performs authentication of every IoT node deployed in the network to provide safer DT. After successful authentication, secure hash elliptical curve cryptography (SHECC) encrypts the data collected from the CHs by incorporating a hashing function both in encryption and decryption, enhancing the IoT data's security level. Finally, in a cloud server (CS), the decentralized blockchain (BC) stores the encrypted data and the authentication credentials of the IoT devices from the BS, which provide additional security to the network. The results of the presented model show its performance efficiency over existing approaches for energy efficiency (EE), QoS, and security.

Improving IoT Data Security and Integrity Using Lightweight Blockchain Dynamic Table

Over the past few years, the Internet of Things (IoT) is one of the most significant technologies ever used, as everything is connected to the Internet. Integrating IoT technologies with the cloud improves the performance, activity, and innovation of such a system. However, one of the major problems which cannot be ignored in such integration is the security of the data that are transferred between the client (IoT) and the server (cloud). Solving that problem leads to the use the of IoT technologies in more critical applications and fields. This paper proposes a new security framework by combining blockchain technology with the AES algorithm. Blockchain technology is used and modified to protect data integrity and generate unique device identification within minimal power consumption and best performance. The AES algorithm is used to improve the data confidentiality when being transmitted to the server. The outcomes demonstrated that the proposed solution improves the security system of the IoT healthcare data and proved its efficiency and power consumption compared to other methods.

Internet of Things and the Implication of Legal Risks and Solutions

So far the Internet has been conceived as the network of people connected to one another. Recently, a lot of things works in connection with one another connected via the Internet. Thus this Internet is called Internet of Things(IoT). The things include not only the electronic devices for personal use such as smartphones and notebooks but also the variety of home appliances, cars, airplanes and even the satellite in the space. The things in the IoT are working based upon the most important two technologies, which are Artificial Intelligence and 5G Telecommunication Technology. Though IoT can be defined a bit differently by scholars and institutions, it is a common understanding that AI and 5G Telecommunication are the key elements. On one hand IoT’s capacity to sense, collect, analyze the informations and make decisions in a very high speed and effective way, makes possible the smart home, smart factory, smart city and even the smart government. On the other hand, it may also generate high risk and problems that it makes personal information leak and misused, person’s privacy is invaded, and even the national security can be threatened.
 The goals of benefiting IoT at the same time protecting people from the risks caused by IoT could be achieved through variety of efforts including setting up appropriate policies and enacting rules and regulations. This article addressed the alternative solutions for the achievement of the goals such as making soft laws, implementing governance process, and the application of blockchain. In sum, with all the pros and cons, this article strongly recommends people (including corporations, consumers, and other groups and associations), as the members of the community they belong to, that they adopt their own soft law best fit for their purpose and community environment to regulate themselves first and to make the soft law to regulate the society general as a de facto binding rules. While doing so we may go through the governance process to harmonize the conflicting interests of the constituents of the society and also adopt the new technology such as blockchain to strengthen the practicability of the soft law at the same time.
 Any soft law standards regarding the IoT should be purported to assure individuals that their data will not be misused or hacked, and that they facilitate trust and communication, and avoid the premature and heavy-handed stifling of innovation. Soft law can help these technologies proliferate while giving people the confidence that, contrary to the current belief, the benefits of the IoT far outweigh the risks. Soft law for IoT can be enhanced by convening a multistakeholder process, as one of the public governance process, to develop best practices for protecting the privacy and security of IoT data, including implementing security by blockchain solutions for the IoT.

Towards Secure and Intelligent Internet of Health Things: A Survey of Enabling Technologies and Applications

With the growth of computing and communication technologies, the information processing paradigm of the healthcare environment is evolving. The patient information is stored electronically, making it convenient to store and retrieve patient information remotely when needed. However, evolving the healthcare systems into smart healthcare environments comes with challenges and additional pressures. Internet of Things (IoT) connects things, such as computing devices, through wired or wireless mediums to form a network. There are numerous security vulnerabilities and risks in the existing IoT-based systems due to the lack of intrinsic security technologies. For example, patient medical data, data privacy, data sharing, and convenience are considered imperative for collecting and storing electronic health records (EHR). However, the traditional IoT-based EHR systems cannot deal with these paradigms because of inconsistent security policies and data access structures. Blockchain (BC) technology is a decentralized and distributed ledger that comes in handy in storing patient data and encountering data integrity and confidentiality challenges. Therefore, it is a viable solution for addressing existing IoT data security and privacy challenges. BC paves a tremendous path to revolutionize traditional IoT systems by enhancing data security, privacy, and transparency. The scientific community has shown a variety of healthcare applications based on artificial intelligence (AI) that improve health diagnosis and monitoring practices. Moreover, technology companies and startups are revolutionizing healthcare with AI and related technologies. This study illustrates the implication of integrated technologies based on BC, IoT, and AI to meet growing healthcare challenges. This research study examines the integration of BC technology with IoT and analyzes the advancements of these innovative paradigms in the healthcare sector. In addition, our research study presents a detailed survey on enabling technologies for the futuristic, intelligent, and secure internet of health things (IoHT). Furthermore, this study comprehensively studies the peculiarities of the IoHT environment and the security, performance, and progression of the enabling technologies. First, the research gaps are identified by mapping security and performance benefits inferred by the BC technologies. Secondly, practical issues related to the integration process of BC and IoT devices are discussed. Third, the healthcare applications integrating IoT, BC, and ML in healthcare environments are discussed. Finally, the research gaps, future directions, and limitations of the enabling technologies are discussed.