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IOTA is an emerging decentralized computing paradigm for developing blockchain-based Internet of Things (IoT) applications. It has the advantages of zero transaction fees, incremental scalability, and high-performance transaction rates. Despite its well-understood benefits, IOTA nodes need to withstand considerable resource costs to generate the distributed ledger. The main reason for this is that IOTA abandons the original blockchain reward mechanism and does not charge transaction fees. Therefore, in this paper we address the cost optimization issue for IOTA based on Lyapunov optimization theory. We take the first step in investigating the cost optimization problem of IOTA and exploring a new optimization scheme using Lyapunov optimization theory. Our proposed scheme enables IOTA to minimize the total cost of IOTA nodes through a computational optimization algorithm. Then, an optimized transaction rate control algorithm can be designed based on the large deviation theory to reduce orphan tangles that waste computational costs. In addition, we define and deduce the effective width of the tangle to monitor the total throughput and reduce the time spent on cost optimization to avoid unnecessary waste of resources. Lastly, a comprehensive theoretical analysis and simulation experiments demonstrate that the proposed strategy is both efficient and practical. [ABSTRACT FROM AUTHOR]

In recent years, blockchain technology has received attention because of its decentralized, immutable and other characteristics, but it faces storage and retrieval challenges. To address these challenges, this paper introduces IOTA distributed ledger technology, which solves the scalability and cost problems of traditional blockchains. By analyzing and experimenting the Tangle, the underlying consensus structure of IOTA, this paper reveals the main factors affecting its development, and proposes a segmented adaptive cutting-edge transaction selection algorithm to optimize the system performance. At the same time, based on IOTA distributed ledger, this paper proposes a data encryption storage and retrieval scheme, which speeds up the data link and retrieval speed, and ensures the integrity and security of data. Finally, this paper discusses the application of blockchain in accounting informatization, and puts forward the scheme of building a new generation of accounting informatization platform, which is of great value to the construction of accounting informatization. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) is bringing new ways to collect and analyze data to develop applications answering or anticipating users' needs. These data may be privacy-sensitive, requiring efficient privacy-preserving mechanisms. The IoT is a distributed system of unprecedented scale, creating challenges for performance and security. Classic blockchains could be a solution by providing decentralization and strong security guarantees. However, they are not efficient and scalable enough for large scale IoT systems, and available tools designed for preserving privacy in blockchains, e.g. coin mixing, have a limited effect due to high transaction costs and insufficient transaction rates. This article provides a framework based on several technologies to address the requirements of privacy, security and performance of the Internet of Things. The basis of the framework is the IOTA technology, a derivative of blockchains relying on a directed acyclic graph to create transactions instead of a linear chain. IOTA improves distributed ledger performance by increasing transaction throughput as more users join the network, making the network scalable. As IOTA is not designed for privacy protection, we complement it with privacy-preserving mechanisms: merge avoidance and decentralized mixing. Finally, privacy is reinforced by introducing usage control mechanisms for users to monitor the use and dissemination of their data. A Proof of Concept is proposed to demonstrate the feasibility of the proposed framework. Performance tests are conducted on this Proof of Concept, showing the framework can work on resource-constrained devices and within a reasonable time. The originality of this contribution is also to integrate an IOTA node within the usage control system, to support privacy as close as possible to the objects that need it. [ABSTRACT FROM AUTHOR]

The adoption of blockchain platforms to bolster the security of Internet of Things (IoT) systems has attracted significant attention in recent years. Currently, there is a lack of comprehensive and systematic survey papers in the literature addressing these platforms. This paper discusses six of the most popular emerging blockchain platforms adopted by IoT systems and analyses their usage in state-of-the-art works to solve security problems. The platform was compared in terms of security features and other requirements. Findings from the study reveal that most blockchain components contribute directly or indirectly to IoT security. Blockchain platform components such as cryptography, consensus mechanism, and hashing are common ways that security is achieved in all blockchain platform for IoT. Technologies like Interplanetary File System (IPFS) and Transport Layer Security (TLS) can further enhance data and communication security when used alongside blockchain. To enhance the applicability of blockchain in resource-constrained IoT environments, future research should focus on refining cryptographic algorithms and consensus mechanisms to optimise performance and security. [ABSTRACT FROM AUTHOR]

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Introduction: Oral hydrogel dressings are required to speed up the healing of oral mucosal wounds by reducing plaque and bacterial infection of the wound. Hydrogel dressing is able to maintain wound moisture and act as an extracellular matrix. Red algae contain carrageenan, which is a polysaccharide of the hydrogel. This study aimed to analyse hydrogel dressing based on red algae carrageenan on the viability of fibroblast culture cells. Materials and methods: The study used human gingival primary culture, treated with hydrogel dressing. There were five treatment groups: base composition hydrogel dressing (group 1), base composition plus carrageenan kappa (group 2), base composition plus carrageenan iota (group 3), base composition + carrageenan kappa without carbomer (group 4) and base composition plus carrageenan iota without carbomer, each divided into four groups of 0.5% concentration. 1%, 2% and 3%. Viability was analysed using an MTT assay. Results: In this study, all groups showed a high percentage of viability. The administration of carrageenan showed that the viability percentage decreased due to changes in gel elasticity. The high elasticity of the gel inhibits cell differentiation and proliferation. Cell viability in iota carrageenan hydrogel was higher than in kappa-carrageenan hydrogel. The group's overall survival exceeded 70%, indicating that the hydrogel was not toxic but supported differentiation and proliferation. Conclusion: It was concluded that the hydrogel dressing in all treatments showed a high percentage of cell viability and did not cause cell toxicity. The carrageenan in the hydrogel causes the hydrogel film layer to become stiffer and stronger, thus affecting its viability. [ABSTRACT FROM AUTHOR]

With the increase of IoT devices generating large amounts of user-sensitive data, improper firmware harms users' security and privacy. Latest home appliances are integrated with features to assure compatibility with smart home IoT. However, applying complex security mechanisms to IoT is limited by device hardware capabilities, making them vulnerable to attacks. Such attacks have recently become frequent. To address this issue, we developed a secure verification mechanism for firmware released by the device's manufacturer. We proposed an IoT gateway for secure firmware verification and updating for smart home IoT devices utilizing the IOTA MAM (Masked Authenticated Messaging) protocol and a distributed file system with IPFS (Inter-Planetary File System) protocol. These two communication protocols ensure decentralized communication and firmware file distribution between the IoT device vendor and the IoT end device. The proposed scheme securely shares latest firmware content over IOTA and IPFS networks, performs a secure firmware update on IoT end devices and ensures authenticity and integrity of the firmware. Two types of validation methods were proposed for firmware updating and validation. We implemented the proposed scheme using three entities, Vendor, IoT gateway, and IoT end device. Our system yielded promising results in performing secure automated firmware updates on IoT end devices with very low computational power. The system's functionality was implemented using IOTA's MAM run on Raspberry Pi as an IoT gateway along with an ESP8266 Wi-Fi microcontroller, demonstrating the effectiveness of our approach. Our proposed methodology can be used for secure firmware distribution on home IoT applications. [ABSTRACT FROM AUTHOR]

Due to the advantages of high volume of transactions and low resource consumption, Directed Acyclic Graph (DAG)-based Distributed Ledger Technology (DLT) has been considered a possible next-generation alternative to block-chain. However, the security of the DAG-based system has yet to be comprehensively understood. Aiming at verifying and evaluating the security of DAG-based DLT, we develop a Multi-Agent based IOTA Simulation platform called MAIOTASim. In MAIOTASim, we model honest and malicious nodes and simulate the configurable network environment, including network topology and delay. The double-spending attack is a particular security issue related to DLT. We perform the security verification of the consensus algorithms under multiple double-spending attack strategies. Our simulations show that the consensus algorithms can resist the parasite chain attack and partially resist the splitting attack, but they are ineffective under the large weight attack. We take the cumulative weight difference of transactions as the evaluation criterion and analyze the effect of different consensus algorithms with parameters under each attack strategy. Besides, MAIOTASim enables users to perform large-scale simulations with multiple nodes and tens of thousands of transactions more efficiently than state-of-the-art ones. [ABSTRACT FROM AUTHOR]

The IOTA Tangle, a Directed Acyclic Graph (DAG)-based distributed ledger, is popular for its scalability and suitability for IoT applications, offering fee-less transactions. A critical component of IOTA’s architecture is the Cumulative Weight Calculation (CWC), essential for its tip selection mechanism. This paper introduces an optimization of the IOTA Reference Implementation (IRI) CWC process originally implemented using Breadth-First Search (BFS) by employing Depth-First Search (DFS) and Iterative Deepening Search (IDS) algorithms. We present a comparative analysis of these methods, demonstrating that DFS and IDS provide significant improvements in computational efficiency, particularly beneficial for IoT devices with limited processing capabilities. Our findings are substantiated through a series of experiments on a Tangle snapshot, highlighting the enhanced performance and reduced resource utilization of the proposed methods. This study contributes to the ongoing development of DAG-based distributed ledgers, offering insights into more efficient algorithmic solutions for large-scale, decentralized networks.

Purpose: This study aims to systematically compare the diagnostic performance of the Ovarian-Adnexal Reporting and Data System with the International Ovarian Tumor Analysis Simple Rules and the Assessment of Different NEoplasias in the adneXa model for risk stratification of ovarian cancer and adnexal masses. Methods: A literature search of online databases for relevant studies up to July 2023 was conducted by two independent reviewers. The summary estimates were pooled with the hierarchical summary receiver-operating characteristic model. The quality of the included studies was assessed with the Quality Assessment of Diagnostic Accuracy Studies-2 and the Quality Assessment of Diagnostic Accuracy Studies-Comparative Tool. Metaregression and subgroup analyses were performed to explore the impact of varying clinical settings. Results: A total of 13 studies met the inclusion criteria. The pooled sensitivity and specificity for eight head-to-head studies between the Ovarian-Adnexal Reporting and Data System and the Assessment of Different NEoplasias in the adneXa model were 0.96 (95% CI 0.92-0.98) and 0.82 (95% CI 0.71-0.90) vs. 0.94 (95% CI 0.91-0.95) and 0.83 (95% CI 0.77-0.88), respectively, and for seven head-to-head studies between the Ovarian-Adnexal Reporting and Data System and the International Ovarian Tumor Analysis Simple Rules, the pooled sensitivity and specificity were 0.95 (95% CI 0.93-0.97) and 0.75 (95% CI 0.62-0.85) vs. 0.91 (95% CI 0.82-0.96) and 0.86 (95% CI 0.76-0.93), respectively. No significant differences were found between the Ovarian-Adnexal Reporting and Data System and the Assessment of Different NEoplasias in the adneXa model as well as the International Ovarian Tumor Analysis Simple Rules in terms of sensitivity (P = 0.57 and P = 0.21) and specificity (P = 0.87 and P = 0.12). Substantial heterogeneity was observed among the studies for all three guidelines. Conclusion: All three guidelines demonstrated high diagnostic performance, and no significant differences in terms of sensitivity or specificity were observed between the three guidelines. [ABSTRACT FROM AUTHOR]

The internet of things (IoT) enables machine-to-machine communication without human intervention. Consequently, every object connected to the internet can exchange information with each other. Internet of things application (IOTA) has undertaken a project to address the high transaction fees inherent in traditional blockchain systems and enhance the efficiency of microtransactions between machines by combining blockchain and IoT. IOTA employs its unique Tangle technology, which introduces a novel transaction consensus method, addressing the fee issues, limited scalability, and the inability to conduct offline transactions associated with traditional blockchains. This paper provides a detailed overview of the characteristics of the Tangle structure and the concepts applied in IOTA. Additionally, it explores potential approaches for integrating blockchain into IoT. [ABSTRACT FROM AUTHOR]

The IOTA Tangle, a Directed Acyclic Graph (DAG)-based distributed ledger, is popular for its scalability and suitability for IoT applications, offering fee-less transactions. A critical component of IOTA's architecture is the Cumulative Weight Calculation (CWC), essential for its tip selection mechanism. This paper introduces an optimization of the IOTA Reference Implementation (IRI) CWC process originally implemented using Breadth-First Search (BFS) by employing Depth-First Search (DFS) and Iterative Deepening Search (IDS) algorithms. We present a comparative analysis of these methods, demonstrating that DFS and IDS provide significant improvements in computational efficiency, particularly beneficial for IoT devices with limited processing capabilities. Our findings are substantiated through a series of experiments on a Tangle snapshot, highlighting the enhanced performance and reduced resource utilization of the proposed methods. This study contributes to the ongoing development of DAG-based distributed ledgers, offering insights into more efficient algorithmic solutions for large-scale, decentralized networks. [ABSTRACT FROM AUTHOR]

Background: IOTA proposed Simple Ultrasound Rules in 2009 for preoperative diagnosis of ovarian masses based on ultrasound only. It is an accurate, simple and inexpensive method. RMI, however, requires CA125 level. While RMI-4 is the latest, RMI-1 is still the most widely used method. The present study was done to compare IOTA Rules with RMI-1 and RMI-4. Purpose: To differentiate benign and malignant adnexal masses preoperatively using IOTA simple rules and compare its accuracy with RMI-1 and RMI-4. Methods: A prospective observational study was performed from 1st November 2019 to 31st March 2021 in the Department of Obstetrics and Gynaecology, ABVIMS and Dr. RML Hospital, New Delhi. This study was conducted on 70 patients with adnexal masses who underwent pre-operative evaluation using IOTA Simple Rules, RMI-1 and RMI-4. Histopathology was used to compare the results. Results: Out of 70 patients, 59 (84.3%) cases were benign and 11 (15.7%) were malignant. The IOTA Rules were applicable to 60 cases (85.7%), and the results were inconclusive in 10 cases (14.3%). Where applicable, the sensitivity and specificity of the IOTA Rules (88.9% and 94.1%, respectively) were significantly higher than RMI-1 (45.5% and 93.2%, respectively) and RMI-4 (45.5% and 89.8%, respectively). When inconclusive results were included as malignant, the sensitivity of the IOTA Rules increased (88.9% vs 90.9%); however, the specificity decreased (94.1% vs 81.4%). Conclusion: IOTA Simple Rules were more accurate at diagnosing benign from malignant adnexal masses than RMI-1 and RMI-4. However, the rules were not applicable to 14% of the cases. [ABSTRACT FROM AUTHOR]

As the potential of directed acyclic graph (DAG)-based distributed ledgers in IoT systems unfolds, a need arises to understand their intricate dynamics in real-world scenarios. It is well known that discrete event simulations can provide high-fidelity evaluations of protocols. However, there is a lack of public discrete event simulators capable of assessing DAG-based distributed ledgers. In this paper, a discrete-event-based distributed ledger simulator is introduced, with which we investigate a custom Python-based implementation of IOTA's Tangle DAG protocol. The study reveals the dynamics of Tangle (particularly Poisson processes in transaction dynamics), the efficiency and intricacies of the random walk in Tangle, and the quantitative assessment of node convergence. Furthermore, the research underscores the significance of weight updates without depth limitations and provides insights into the role, challenges, and implications of the coordinator/validator in DAG architectures. The results are striking, and although the findings are reported only for Tangle, they demonstrate the need for adaptable and versatile discrete event simulators for DAG architectures and tip selection methodologies in general. [ABSTRACT FROM AUTHOR]

The IOTA Extended UTXO (IOTA EUTXO) model extends the UTXO blockchain to include features like smart contracts and non-fungible tokens. In this work, we show that the IOTA EUTXO model maintains the base correctness properties of the UTXO model while extending it with extra functionality. We achieve this by specifying and verifying the essential concepts of the base UTXO model and the extensions proposed by IOTA using the Isabelle proof assistant. The specification is designed to be modular and extensible, meaning it can be used as a foundation for further research of the UTXO and IOTA EUTXO models. [ABSTRACT FROM AUTHOR]

PURPOSE: To evaluate interobserver agreement in assigning imaging features and classifying adnexal masses using the IOTA simple rules versus O-RADS lexicon and identify causes of discrepancy. METHODS: Pelvic ultrasound (US) examinations in 114 women with 118 adnexal masses were evaluated by eight radiologists blinded to the final diagnosis (4 attendings and 4 fellows) using IOTA simple rules and O-RADS lexicon. Each feature category was analyzed for interobserver agreement using intraclass correlation coefficient (ICC) for ordinal variables and free marginal kappa for nominal variables. The two-tailed significance level (a) was set at 0.05. RESULTS: For IOTA simple rules, interobserver agreement was almost perfect for three malignant lesion categories (M2-4) and substantial for the remaining two (M1, M5) with k-values of 0.80-0.82 and 0.68-0.69, respectively. Interobserver agreement was almost perfect for two benign feature categories (B2, B3), substantial for two (B4, B5) and moderate for one (B1) with k-values of 0.81-0.90, 0.69-0.70 and 0.60, respectively. For O-RADS, interobserver agreement was almost perfect for two out of ten feature categories (ascites and peritoneal nodules) with k-values of 0.89 and 0.97. Interobserver agreement ranged from fair to substantial for the remaining eight feature categories with k-values of 0.39-0.61. Fellows and attendings had ICC values of 0.725 and 0.517, respectively. CONCLUSION: O-RADS had variable interobserver agreement with overall good agreement. IOTA simple rules had more uniform interobserver agreement with overall excellent agreement. Greater reader experience did not improve interobserver agreement with O-RADS.

Objective: To study the clinical value of the International Ovarian Tumor Analysis(IOTA) ADNEX(the Assessment of Differential NEopasia in the adneXa) model in differentiating metastatic ovarian cancer from primary ovarian cancer. Methods: Patients who underwent transvaginal ultrasonography and operation in our hospital from March 2016 to April 2021 were selected. Preoperative ultrasound examination was performed, and the model prediction results were recorded. Based on the postoperative pathological results， the sensitivity, specificity and area under receiver operating characteristic (ROC) curve of the ADNEX model with and without CA125 in distinguishing metastatic and primary ovarian cancer was calculated. Results: A total of 197 patients with ovarian cancer were enrolled, including 153 patients with primary ovarian cancer (36 patients with stage Ⅰ ovarian cancer, 117 patients with stage Ⅰ-Ⅳ ovarian cancer) and 44 patients with metastatic ovarian cancer. The area under the ROC curve of ADNEX model without CA125 in differentiating metastatic and primary ovarian cancer was 0.621 (95% confidence interval 0.534-0.708), with a sensitivity of 93.2% and a specificity of 31.4%.The area under the ROC curve of ADNEX model with CA125 was 0.810 (95% confidence interval 0.747-0.872), with a sensitivity of 79.5% and a specificity of 69.3%. The difference between the two was statistically significant (P

IOTA is an emerging decentralized computing paradigm for developing blockchain-based Internet of Things (IoT) applications. It has the advantages of zero transaction fees, incremental scalability, and high-performance transaction rates. Despite its well-understood benefits, IOTA nodes need to withstand considerable resource costs to generate the distributed ledger. The main reason for this is that IOTA abandons the original blockchain reward mechanism and does not charge transaction fees. Therefore, in this paper we address the cost optimization issue for IOTA based on Lyapunov optimization theory. We take the first step in investigating the cost optimization problem of IOTA and exploring a new optimization scheme using Lyapunov optimization theory. Our proposed scheme enables IOTA to minimize the total cost of IOTA nodes through a computational optimization algorithm. Then, an optimized transaction rate control algorithm can be designed based on the large deviation theory to reduce orphan tangles that waste computational costs. In addition, we define and deduce the effective width of the tangle to monitor the total throughput and reduce the time spent on cost optimization to avoid unnecessary waste of resources. Lastly, a comprehensive theoretical analysis and simulation experiments demonstrate that the proposed strategy is both efficient and practical.

Ensuring authorized access control in the IoT is vital for privacy and safety protection. Our study presents the novel IHIBE framework, which combines IOTA (a distributed ledger technology) with hierarchical identity-based encryption (HIBE), thereby enhancing both IoT security and scalability. This approach secures access tokens and policies while reducing the computational demand on data owners. Our empirical findings reveal a significant performance gap, with access rights delegation on the Raspberry Pi 4 exceeding those on AWS by over 250%. Moreover, our analysis uncovers optimal identity policy depths: up to 640 identities on AWS and 640 on the Raspberry Pi 4 for systems with higher tolerable delays, and 320 identities on AWS versus 160 on the Raspberry Pi 4 for systems with lower tolerable delays. The system shows practical viability, exhibiting insignificant operational time differences compared to Zhang et al.'s schemes, particularly in access rights verification processes, with a minimal difference of 33.35%. Our extensive security assessment, encompassing scenarios like encrypted token theft and compromise of authority, affirms the efficacy of our challenge-response and last-word challenge (LWC) mechanisms. This study underscores the importance of platform choice in IoT system architectures and provides insights for deploying efficient, secure, and scalable IoT environments. [ABSTRACT FROM AUTHOR]

The paper presents a traceability framework founded upon a methodological approach specifically designed for the integration of the IOTA-based distributed ledger within the mining industry. This framework constitutes an initial stride towards the certification and labelling of sustainable material production. The efficacy of this methodology is subject to real-world evaluation within the framework of the European Commission funded project DIG_IT. Within the architectural framework, the integration of decentralized identifiers (DIDs) and the IOTA network are instrumental in effecting the encryption of data records, with associated hashes securely anchored on the explorer. Recorded environmental parameters, encompassing metrics such as pH level, turbidity, electrical conductivity, and emissions, serve as tangible evidence affirming their adherence to prevailing regulatory standards. The overarching system architecture encompasses a sophisticated Industrial Internet of Things platform (IIoTp), facilitating the seamless connection of data from a diverse array of sensors. End users, including governmental entities, mining managers, and the general public, stand to derive substantial benefits from tailored dashboards designed to facilitate the validation of data for emission compliance. [ABSTRACT FROM AUTHOR]

In the pharmaceutical research and development process, the third phase of clinical trials involves double-blind trials to mitigate the influence of human subjective awareness on the experimental results and ensure the efficacy and safety of drugs or vaccines. However, conventional double-blind trials are often overseen by a single institution responsible for the entire trial process. Researchers centrally manage data, introducing risks of data loss and tampering. Furthermore, since researchers have full access to all experimental data, there is a potential for premature unblinding and leakage of results to specific individuals, giving rise to bias and conflicts of interest. To address these problems, this paper proposes a distributed-ledger-based double-blind trial platform called "BlindBox". This platform leverages the immutability and decentralization of distributed ledgers to enhance the security of experimental data. On the other hand, the platform employs smart contracts to restrict personnel's access to experimental data, coupled with RFID technology to encode and shuffle the experimental drugs discreetly. This ensures that no one can ascertain the pairing between test subjects and drug groups, preventing collusion and result manipulation. When the trial period concludes, smart contracts automatically unblind the results and publish them on the IOTA platform. By utilizing IOTA's zero-value transactions, the platform reduces the cost of repeated data access and ensures information openness and transparency. This approach prevents deliberate premature unblinding or insider trading stemming from monopolized information. The platform proposed in this study is expected to enhance the credibility and accuracy of double-blind trials while promoting the willingness and convenience of public participation in experiments. [ABSTRACT FROM AUTHOR]

Security presents significant challenges due to the exponential growth in the number of Internet of Things (IoT) devices that generate and collect data over the network. It is crucial to ensure the integrity and security of IoT devices, as well as to address issues such as interoperability and trust in data sources. In the proposed article, we present a novel architecture together with its implementation as a proof-of-concept of a traceability and auditing IoT system based on Distributed Ledger Technology (DLT). To demonstrate the applicability of the proposed solution, a smart contract-based system for occupational risk prevention (ORP) has been developed to monitor oxygen concentration in confined spaces that exist in ships and shipyards. The system has been devised for the operators that weld inside the ships of the Spanish shipbuilding company Navantia, which is one of the largest shipbuilders in the world. Specifically, the IOTA network has been used, which benefits the system through its decentralized, secure, and scalable data structure. In addition, the integration of smart contracts allows for establishing predefined rules and conditions, ensuring the execution of logic in a reliable and automated manner. To demonstrate the viability of the system, it has been tested locally and in the IOTA testing environment. Despite the challenges in deploying smart contracts with IOTA, the developed system is considered useful for the traceability and auditing of the oxygen concentrations without the need for any human intervention. Furthermore, it establishes the groundwork for future advancements in IoT traceability and auditing in industrial ORP scenarios. [ABSTRACT FROM AUTHOR]

Since the introduction of the first cryptocurrency, Bitcoin, in 2008, the gain in popularity of distributed ledger technologies (DLTs) has led to an increasing demand and, consequently, a larger number of network participants in general. Scaling blockchain-based solutions to cope with several thousand transactions per second or with a growing number of nodes has always been a desirable goal for most developers. Enabling these performance metrics can lead to further acceptance of DLTs and even faster systems in general. With the introduction of directed acyclic graphs (DAGs) as the underlying data structure to store the transactions within the distributed ledger, major performance gains have been achieved. In this article, we review the most prominent directed acyclic graph platforms and evaluate their key performance indicators in terms of transaction throughput and network latency. The evaluation aims to show whether the theoretically improved scalability of DAGs also applies in practice. For this, we set up multiple test networks for each DAG and blockchain framework and conducted broad performance measurements to have a mutual basis for comparison between the different solutions. Using the transactions per second numbers of each technology, we created a side-by-side evaluation that allows for a direct scalability estimation of the systems. Our findings support the fact that, due to their internal, more parallelly oriented data structure, DAG-based solutions offer significantly higher transaction throughput in comparison to blockchain-based platforms. Although, due to their relatively early maturity state, fully DAG-based platforms need to further evolve in their feature set to reach the same level of programmability and spread as modern blockchain platforms. With our findings at hand, developers of modern digital storage systems are able to reasonably determine whether to use a DAG-based distributed ledger technology solution in their production environment, i.e., replacing a database system with a DAG platform. Furthermore, we provide two real-world application scenarios, one being smart grid communication and the other originating from trusted supply chain management, that benefit from the introduction of DAG-based technologies. [ABSTRACT FROM AUTHOR]

Abstract Background The accuracy of ultrasound in distinguishing benign from malignant adnexal masses is highly correlated with the experience of ultrasound physicians. In China, most of ultrasound differentiation is done by junior physicians. Purpose To compare the diagnostic performance of the International Ovarian Tumour Analysis (IOTA) Simple Rules Risk (SRR) and IOTA Logistic Regression Model 2 (LR2) scoring systems in Chinese patients with adnexal masses. Methods Retrospective analysis of ovarian cancer tumor patients who underwent surgery at a hospital in China from January 2016 to December 2021. Screening patients with at least one adnexal mass on inclusion and exclusion criteria. Two trained junior physicians evaluated each mass using the two scoring systems. A receiver operating characteristic curve was used to test the diagnostic performance of each system. Results A total of 144 adnexal masses were retrospectively collected. Forty masses were histologically diagnosed as malignant. Compared with premenopausal women, postmenopausal women had a much higher rate of malignant masses. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) of the SRR was 97.5% (95% CI: 86.8 -99.9%), 82.7% (95% CI: 74.0 -89.4%), 68.4% (95% CI: 58.7 -76.8%) and 98.9% (95% CI: 92.5 -99.8%). The sensitivity, specificity, PPV, NPV of the LR2 were 90.0% (95% CI: 76.5 -97.2%), 89.4% (95% CI: 81.9 -94.6%), 76.6% (95% CI: 65.0 -85.2%), and 95.9% (95% CI: 90.2 -98.3%). There was good agreement between two scoring systems, with 84.03% total agreement and a kappa value of 0.783 (95% CI: 0.70-0.864). The areas under the curve for predicting malignant tumours using SRR and LR2 were similar for all patients (P > 0.05 ). Conclusion The two scoring systems can effectively distinguish benign from malignant adnexal masses. Both scoring systems have high diagnostic efficacy, and diagnostic efficacy is stable, which can provide an important reference for clinical decision making.

IOTA is a new public chain system specifically designed for the Internet of Things (IoT), which provides strong support for the high concurrency, scalability, and zero handling fees of the IoT. The distributed ledger of IOTA, called the tangle, adopts a Directed Acyclic Graph (DAG) structure. However, compared to the single-chain architecture, the tangle is more complex and highly vulnerable to security threats. The existing transaction verification methods still cannot simultaneously meet the need for accelerating approval speed and improving security to resist illegal transactions, such as lazy tips and permanent tips. In this work, we propose TDTS, a tip-selection algorithm based on time division to improve the efficiency of transaction verification. The main idea of the algorithm is to quickly determine two tips of an incoming transaction that need to be confirmed by sorting tip values in a time slot. It shortens the transaction verification time and reduces the number of lazy tips and permanent tips. A comprehensive theoretical analysis confirmed the effectiveness of our proposed algorithm. Based on 1000 IOTA nodes, the evaluations showed that TDTS can select tips quickly like URTS and resist lazy tips like MCMC. [ABSTRACT FROM AUTHOR]

Environmental monitoring devices based on IoT collect a large amount of data about the environment and our surroundings. These data are collected and processed before being uploaded to third-party servers and accessed and viewed by ordinary or specialized users. However, they may hold sensitive information that should not be exposed to unauthorized users. Therefore, accessing this sensitive information must be strictly controlled and limited in order to prevent unauthorized access. This research intends to create an access control mechanism based on distributed ledger technologies. The idea is to use a hybrid of IOTA technology and Ciphertext-Policy Attribute-Based Signcryption (CP-ABSC) technology. The permissions to access these data are written in a token, and this token will be sent to the Tangle after being signcrypted with CP-ABSC. Consequently, the data will be safeguarded, their confidentiality and integrity will be maintained, and unauthorized individuals will be unable to access the information. The proposed system was evaluated in terms of performance and the results showed that the system is straightforward, rapid, and convenient to use. Furthermore, a security assessment was conducted by running several scenarios to evaluate its feasibility and protection. [ABSTRACT FROM AUTHOR]

Abstract The privacy of electricity consumers has become one of the most critical subjects in designing smart meters and their proliferation. In this work, a multilayer architecture has been proposed for anonymous data collection from smart meters, which provides: (1) The anonymity of information for third‐party data consumers; (2) Secure communication to utility provider network for billing purposes; (3) Online control of data sharing for end‐users; (4) Low communication costs based on available Internet of things (IoT) communication protocols. The core elements of this architecture are, first, the digital twin equivalent of the cyber‐physical system and, second, the Tangle distributed ledger network with IOTA cryptocurrency. In this architecture, digital twin models are updated in real‐time by information received from trusted nodes of the Tangle distributed network anonymously. A small‐scale laboratory prototype based on this architecture has been developed using the dSPACE SCALEXIO real‐time simulator and open‐source software tools to prove the feasibility of the proposed solution. The numerical results confirm that after a few seconds of anomaly detection, the microgrid was fully stabilized around its operating point with less than 5% deviation during the transition time.

Background: Comparative performance of various ultrasound models in diagnosing ovarian lesions has not been adequately studied. This study aimed to evaluate the diagnostic performance of the International Ovarian Tumor Analysis (IOTA) simple rules and Assessment of Different NEoplasias in the adneXa (ADNEX) models in women with ovarian lesions. Methods: Women 18?80 years, with an ovarian lesion planned for surgery were recruited in this prospective observational cohort study. Preoperative risk stratification was done by both IOTA simple rules and the ADNEX model. The diagnostic performance of both models was estimated using histopathology as the gold standard. Results: A total of 90 women were recruited into the study. The IOTA simple rules were applicable to 77 (85.5%) participants and the ADNEX model on 100% women. Both the simple rules and the ADNEX model had good diagnostic performance. The sensitivity and specificity of the IOTA simple rules for predicting malignancy was 66.6% and 91%, while that of the ADNEXA model was 80% and 94%, respectively. The maximum diagnostic accuracy for prediction of both benign and malignant tumors was obtained when cancer antigen-125 (CA-125) was combined with the IOTA ADNEX model (91.0%), but for Stage I malignancy, the maximum diagnostic accuracy was for ADNEX without CA-125 (91.0%). Conclusion: Both the IOTA models have a good diagnostic accuracy and are of paramount importance in differentiating benign from malignant tumors and predicting the stage of the malignant disease.

Attribute spoofing is a major security threat in information exchange solutions based on Ciphertext-Policy Attribute-Based-Encryption (CP-ABE) and distributed CP-ABE (dCP-ABE), which can compromise privacy and security. This threat occurs when an attacker forces the Attribute Authorities to generate keys for attributes they do not possess. This paper analyzes the threat of attribute spoofing and identifies the primary attack vectors, including direct interference with the Attribute Authority and compromise of the shared attribute storage database. The authors propose a solution based on IOTA, a DAG-type DLT, and Interplanetary File System (IPFS) to prevent attribute spoofing. The solution requires distributed attribute storage, validation, and user authentication to counteract the two attack vectors effectively. The proposed solution mitigates the consequences of attribute spoofing, including privilege escalation and reduction, acquisition of private keys, and cutoff of data access. The authors also evaluate their proposal through a value-chain use case and conclude that it effectively mitigates the consequences of attribute spoofing.

Abstract Background: The international ovarian tumor analysis (IOTA) study technique is a specialized method for classifying and identifying adnexal growths. It employs 10 simple ultrasound directions to characterize masses as benign or malignant. Objectives: This study aims to provide pre-operative information to help gynecologists manage ovarian masses, avoiding delays in malignancy treatment and unnecessary surgery for benign lesions. Methods: This was a hospital-based observational study conducted in the radiology department on patients with clinical diagnoses of ovarian masses from August 2020 to March 2022 by prospective randomized sampling method. Patients with suspected ovarian pathology were evaluated using IOTA ultrasound rules and designated benign or malignant. The patients underwent a thorough history and clinical examination. Ultrasound was used to confirm the ovarian origin of the mass and differentiate it as benign or malignant. A transvaginal ultrasound was performed where necessary. Histopathological examination was the gold standard to confirm ultrasound and Doppler findings. Descriptive stats: Frequencies/percentages for categorical data, mean ± SD for normal, median with IQR for non-normal Uncertainty measured by 95% CI. Results: During the study, 50 women were eligible for the study, and the mean age of the participants was 45.3 years. Of 50 patients who underwent surgery, 38 cases were considered benign based on IOTA USG rules, of which 35 were benign and 3 were malignant histologically Eight cases were considered malignant based on IOTA USG rules, of which 6 were malignant and 2 were benign. Four cases were considered indeterminate, with two being benign and two being malignant histologically. If inconclusive cases are classified as malignant, the sensitivity and specificity are 75% and 88%, respectively. Conclusions: USG is an easily available imaging tool that can be used as an initial modality in evaluating ovarian masses. IOTA simple ultrasound rules have diagnostic accuracy in distinguishing benign and malignant ovarian masses and help in management.

This paper proposes a general and interoperable Web of Things (WoT)-oriented architecture to support a distributed storage application. In particular, the focus is on a distributed ledger service dedicated to machine-to-machine (M2M) transactions occurring in an intelligent ecosystem. For this purpose, the basic functional modules have been characterized and integrated into a comprehensive framework relying on an IOTA approach. Furthermore, a general protocol that is built upon an underlying publish-and-subscribe framework is proposed to support all the application phases. The proposed approach has been validated by a simulation campaign targeting the achievable latency and throughput and, further, by a qualitative analysis of high-level metrics, both pointing out several advantages in terms of interoperability, scalability, and mobility support, together with addressing some constraints affecting service availability and security. [ABSTRACT FROM AUTHOR]

Blockchain 3.0, an advanced iteration of blockchain technology, has emerged with diverse applications encompassing various sectors such as identity authentication, logistics, medical care, and Industry 4.0/5.0. Notably, the integration of blockchain with industrial automation and control systems (IACS) holds immense potential in this evolving landscape. As industrial automation and control systems gain popularity alongside the widespread adoption of 5G networks, Internet of Things (IoT) devices are transforming into integral nodes within the blockchain network. This facilitates decentralized communication and verification, paving the way for a fully decentralized network. This paper focuses on showcasing the implementation and execution results of data preservation from industrial automation and control systems to IOTA, a prominent distributed ledger technology. The findings demonstrate the practical application of IOTA in securely preserving data within the context of industrial automation and control systems. The presented numerical results validate the effectiveness and feasibility of leveraging IOTA for seamless data preservation, ensuring data integrity, confidentiality, and transparency. By adopting IOTA's innovative approach based on Directed Acyclic Graph (DAG), the paper contributes to the advancement of blockchain technology in the domain of Industry 4.0/5.0. [ABSTRACT FROM AUTHOR]

The privacy and security of patients' health records have been an ongoing issue, and researchers are in a race against technology to design a system that can help stop the compromising of patient data. Many researchers have proposed solutions; however, most solutions have not incorporated potential parameters that can ensure private and secure personal health records management, which is the focus of this study. To design and develop a solution, this research thoroughly investigated existing solutions and identified potential key contexts. These include IOTA Tangle, Distributed Ledger Technology (DLT), IPFS protocols, Application Programming Interface (API), Proxy Re-encryption (PRE), and access control, which are analysed and integrated to secure patient medical records, and Internet of Things (IoT) medical devices, to develop a patient-based access management system that gives patients full control of their health records. This research developed four prototype applications to demonstrate the proposed solution: the web appointment application, the patient application, the doctor application, and the remote medical IoT device application. The results indicate that the proposed framework can improve healthcare services by providing immutable, secure, scalable, trusted, self-managed, and traceable patient health records while giving patients full control of their own medical records. [ABSTRACT FROM AUTHOR]

Healthcare has evolved significantly in recent years primarily due to the advancements in and increasing adoption of technology in healthcare processes such as data collection, storage, diagnostics, and treatment. The emergence of the industrial internet of things (IIoT) has further evolved e-Health by facilitating the development of connected healthcare systems which can significantly improve data connectivity, visibility, and interoperability leading to improved quality of service delivered to patients. However, such technological advancements come with their perils—there are growing concerns with regards to the security and privacy of healthcare data especially when collected, shared, and processed using cutting-edge connected sensor devices affecting the adoption of next-generation e-healthcare systems. In particular, during the front-end and back-end data transfer in health information exchange (HIE) there exist a security risk in term of confidentiality, integrity, authentication and access control of the data due to the limited capabilities of IoT devices involved. In this paper, we investigate the use of distributed ledger technologies (DLT) to address such security concerns for emerging healthcare systems. In particular, we use masked authenticated messaging (MAM) over the Tangle to achieve secure data sharing within a healthcare system and provide a proof-of-concept of applying the proposed approach for securing healthcare data in a connected IIoT environment. Further, we have performed the evaluation and analysis of data communication against the metrics of encryption and efficiency in transaction time. [ABSTRACT FROM AUTHOR]