Nowadays, the Industrial Internet of Things (IIoT) has remarkably transformed our personal lifestyles and society operations into a novel digital mode, which brings tremendous associations with all ...walks of life, such as intelligent logistics, smart grid, and smart city. Moreover, with the rapid increase of IIoT devices, a large amount of data is swapped between heterogeneous sensors and devices every moment. This trend increases the risk of eavesdropping and hijacking attacks in communication channels, so maintaining data privacy and security becomes two notable concerns at present. Recently, based on the mechanism of the Schnorr signature, a more secure and lightweight certificateless signature (CLS) protocol is popular for the resource-constrained IIoT protocol design. Nevertheless, we found most of the existing CLS schemes are susceptible to several common security weaknesses such as man-in-the-middle attacks, key generation center compromised attacks, and distributed denial of service attacks. To tackle the challenges mentioned previously, in this article, we propose a novel pairing-free certificateless scheme that utilizes the state-of-the-art blockchain technique and smart contract to construct a novel reliable and efficient CLS scheme. Then, we simulate the Type-I and Type-II adversaries to verify the trustworthiness of our scheme. Security analysis as well as performance evaluation outcomes prove that our design can hold more reliable security assurance with less computation cost (i.e., reduced by around 40.0% at most) and communication cost (i.e., reduced by around 94.7% at most) than other related schemes.
•We design a group-agent strategy with trust computing.•We propose a stacked task sorting and ranking mechanism.•We adopt a secure and efficient content model.•Simulation results show that our scheme ...has better computational efficiency and higher reliability.
In order to meet various needs of people, different Internet of Things (IoT) devices have been developed and applied successfully in recent years. However, the consequent challenges in terms of search efficiency, reliable requirements, and resource allocation appear followed, which attract attention from both academia and industry. Facing this circumstance, it is necessary to establish a new scheme to realize data processing and sharing better. Therefore, a reliable and efficient system based on edge computing and blockchain is proposed in this paper. First, a new group-agent strategy with trust computing is designed to ensure the reliability of edge devices during interactions and improve transmission efficiency. Second, we introduce a stacked task sorting and ranking mechanism which improves resource allocation in each edge device. Third, this paper creates a new content model that uses Zipf distribution to predict context popularity of keywords and encrypt hot data with symmetric searchable encryption (SSE) technology. Finally, simulation results show that the proposed scheme has better computational efficiency and higher reliability compared with existing methods.
With the increase in total coronavirus disease 2019 (COVID-19) infection cases, post-acute COVID-19 syndrome, defined as experiencing ongoing health problems 4 or more weeks after the first severe ...acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, has become a new arising public health concern. As part of post-acute COVID-19 syndrome, gastrointestinal symptoms might be associated with dysbiosis of the gut microbiota, which has the potential to become a target for intervention. In this study, a patient with post-acute COVID-19 syndrome with long-lasting severe gastrointestinal symptoms was provided 2-month expanded access to a high-fiber formula with investigational new drug (IND) status developed to alleviate COVID-19-related symptoms by modulating the gut microbiota. Symptoms including severe "loss of appetite," palpitation, and anxiety were significantly alleviated by the end of the intervention. The medication dosage for controlling nausea decreased during the intervention. The serum lipid profile, insulin level, and leptin level were improved compared to the baseline values. Significant structural changes of the patient's gut microbiota and reduced microbial fermentation activity in the small intestine were found during the intervention. Eighteen amplicon sequence variants (ASVs) of the V4 region of the 16S rRNA gene significantly responded to this nutritional intervention. Six out of the 18 ASVs were also found to be negatively correlated with symptom severity/medication dosage. Five of the six ASVs (ASV0AKS_
, ASV009F_
, ASV02YT_
, ASV07LA_
, and ASV0AM6_Eubacterium hallii) were potential short-chain fatty acid (SCFA)-producing bacteria, which might be associated with the alleviation of symptoms. Our study indicates the feasibility of alleviating gastrointestinal symptoms in patients with post-acute COVID-19 syndrome by way of nutritional modulation of their gut microbiota.
It has become evident that the care of patients with COVID-19 does not end at the time of negative SARS-CoV-2 detection, as the number of patients with post-acute COVID-19 syndrome increases with an ever-increasing total infected patient population. This case report shows the possibility of alleviating the gastrointestinal symptoms of post-acute COVID-19 syndrome via microbiota-targeted nutritional intervention. As a promising strategy, it might not only improve the quality of life of patients but also reduce the burden to the public health system when the end of the COVID-19 pandemic is not in sight.
Due to the emergence of heterogeneous Internet of Medical Things (IoMT) (e.g., wearable health devices, smartwatch monitoring, and automated insulin delivery systems), large volumes of patient data ...are dispatched to central cloud servers for disease analysis and diagnosis. Although this direct mode brings a lot of convenience for both patients and medical professionals (MPs), the open communication channel between them also incurs several security and privacy issues, such as man-in-the-middle attacks, eavesdropping attacks, and tracking attacks. Based on the unsolved challenges in wireless medical sensor networks (WMSNs), several researchers have proposed various authentication and key agreement (AKA) protocols for this type of healthcare system recently. However, most of these protocols do not perceive physical-layer security and over-centralized server problem in WMSN. In this article, to address these two open problems, we propose a lightweight and reliable authentication protocol for WMSN, which is composed of cutting-edge blockchain technology and physically unclonable functions (PUFs). In addition, a fuzzy extractor scheme is introduced to deal with biometric information. Subsequently, two security evaluation methods are used to prove the high reliability of our proposed scheme. Finally, performance evaluation experiments illustrate that the proposed mutual authentication protocol requires the least computation and communication cost among the compared schemes.
The development of the Internet of Things (IoT) and 5th generation wireless network (5G) is set to push the smart agriculture to the next level since the massive and real-time data can be collected ...to monitor the status of crops and livestock, logistics management, and other important information. Recently, COVID-19 has attracted more human attention to food safety, which also has a positive impact on smart agriculture market share. However, the security and privacy concern for smart agriculture has become more prominent. Since smart agriculture implies working with large sets of data, which usually sensitive, some are even confidential, and once leakage it can expose user privacy. Meanwhile, considering the data publishing of smart agriculture helps the public or investors to real-timely anticipate risks and benefits, these data are also a public resource. To balance the data publishing and data privacy, in this article, a privacy-preserving data aggregation scheme with a flexibility property uses ElGamal Cryptosystem is proposed. It is proved to be secure, private, and flexible with the analysis and performance simulation.
MXene is a two-dimensional (2D) nanomaterial that exhibits several superior properties suitable for fabricating biosensors. Likewise, the nucleic acid (NA) in oligomerization forms possesses highly ...specific biorecognition ability and other features amenable to biosensing. Hence the combined use of MXene and NA is becoming increasingly common in biosensor design and development. In this review, MXene- and NA-based biosensors are discussed in terms of their sensing mechanisms and fabrication details. MXenes are introduced from their definition and synthesis process to their characterization followed by their use in NA-mediated biosensor fabrication. The emphasis is placed on the detection of various targets relevant to agricultural and food systems, including microbial pathogens, chemical toxicants, heavy metals, organic pollutants, etc. Finally, current challenges and future perspectives are presented with an eye toward the development of advanced biosensors with improved detection performance.
Smart grid has been acknowledged as the next-generation intelligent network that optimizes energy efficiency. Primarily through a bidirectional communication channel, suppliers and users can ...dynamically adjust power transmission in real time. Nonetheless, many security issues occur with the widespread deployment of smart grid, e.g., centralized register authority and potential Distributed-Denial-of-Service (DDoS) attack. These existing problems threaten the availability of smart grid. In this paper, we mainly focus on solving some identity authentication issues remained in the smart grid. Combined with blockchain, Elliptic Curve Cryptography (ECC), dynamic Join-and-Exit mechanism and batch verification, a reliable and efficient authentication protocol is proposed for smart meters and utility centers. Simultaneously, the provable security of this protocol is assured by the computational hard problem assumptions. Experiment results show that our protocol has achieved security and performance improvement compared with the other ECC related schemes.
In the context of the rapid development of blockchain technology, smart contracts have also been widely used in the Internet of Things, finance, healthcare, and other fields. There has been an ...explosion in the number of smart contracts, and at the same time, the security of smart contracts has received widespread attention because of the financial losses caused by smart contract vulnerabilities. Existing analysis tools can detect many smart contract security vulnerabilities, but because they rely too heavily on hard rules defined by experts when detecting smart contract vulnerabilities, the time to perform the detection increases significantly as the complexity of the smart contract increases. In the present study, we propose a novel hybrid deep learning model named CBGRU that strategically combines different word embedding (Word2Vec, FastText) with different deep learning methods (LSTM, GRU, BiLSTM, CNN, BiGRU). The model extracts features through different deep learning models and combine these features for smart contract vulnerability detection. On the currently publicly available dataset SmartBugs Dataset-Wild, we demonstrate that the CBGRU hybrid model has great smart contract vulnerability detection performance through a series of experiments. By comparing the performance of the proposed model with that of past studies, the CBGRU model has better smart contract vulnerability detection performance.
Blockchain presents a chance to address the security and privacy issues of the Internet of Things; however, blockchain itself has certain security issues. How to accurately identify smart contract ...vulnerabilities is one of the key issues at hand. Most existing methods require large-scale data support to avoid overfitting; machine learning (ML) models trained on small-scale vulnerability data are often difficult to produce satisfactory results in smart contract vulnerability prediction. However, in the real world, collecting contractual vulnerability data requires huge human and time costs. To alleviate these problems, this paper proposed an ensemble learning (EL)-based contract vulnerability prediction method, which is based on seven different neural networks using contract vulnerability data for contract-level vulnerability detection. Seven neural network (NN) models were first pretrained using an information graph (IG) consisting of source datasets, which then were integrated into an ensemble model called Smart Contract Vulnerability Detection method based on Information Graph and Ensemble Learning (SCVDIE). The effectiveness of the SCVDIE model was verified using a target dataset composed of IG, and then its performances were compared with static tools and seven independent data-driven methods. The verification and comparison results show that the proposed SCVDIE method has higher accuracy and robustness than other data-driven methods in the target task of predicting smart contract vulnerabilities.
The traditional covert communication channel relying on a third-party node is vulnerable to attack. The data are easily tampered with and the identity information of the communication party is ...fragile. Blockchain has the characteristics of decentralization and tamper resistance, which can effectively solve the above problems. In addition, some confidential information needs to be transmitted covertly in the transparent blockchain. A smart contract deployed in the blockchain to automatically realize its function can replace a centralized node to provide credible guarantee for communication. The diversity of parameters, data redundancy, and code programmability of smart contract make it an excellent carrier for covert communication under blockchain. In this article, we propose a covert communication model combined with smart contracts to covertly transfer information in the blockchain environment. To implement this model, we use the parameters in the contract to map the secret information sequence, and call the contract to transfer message. Voting contract and secret bidding contract are combined to instantiate the proposed model, and optimized versions of the two contracts are also proposed to reduce costs. Moreover, we use encryption algorithms and two-round protocols to ensure data privacy and design corresponding information embedding and transmission methods for different scenarios. To improve the concealment of communication, redundant options, effective price ranges, and invalid bids are set in two contracts, respectively. The experimental results show that the proposed model has tamper resistance and low complexity, and it is feasible to use this model for covert communication.
PDF
