In traditional cloud storage systems, attribute-based encryption (ABE) is regarded as an important technology for solving the problem of data privacy and fine-grained access control. However, in all ...ABE schemes, the private key generator has the ability to decrypt all data stored in the cloud server, which may bring serious problems such as key abuse and privacy data leakage. Meanwhile, the traditional cloud storage model runs in a centralized storage manner, so single point of failure may leads to the collapse of system. With the development of blockchain technology, decentralized storage mode has entered the public view. The decentralized storage approach can solve the problem of single point of failure in traditional cloud storage systems and enjoy a number of advantages over centralized storage, such as low price and high throughput. In this paper, we study the data storage and sharing scheme for decentralized storage systems and propose a framework that combines the decentralized storage system interplanetary file system, the Ethereum blockchain, and ABE technology. In this framework, the data owner has the ability to distribute secret key for data users and encrypt shared data by specifying access policy, and the scheme achieves fine-grained access control over data. At the same time, based on smart contract on the Ethereum blockchain, the keyword search function on the cipher text of the decentralized storage systems is implemented, which solves the problem that the cloud server may not return all of the results searched or return wrong results in the traditional cloud storage systems. Finally, we simulated the scheme in the Linux system and the Ethereum official test network Rinkeby, and the experimental results show that our scheme is feasible.
Plant hormones play central roles in plant growth, developmental processes, and plant response to biotic and abiotic stresses. On the one hand, plant hormones may allocate limited resources to the ...most serious stresses; on the other hand, the crosstalks among multiple plant hormone signaling regulate the balance between plant growth and defense. Many studies have reported the mechanism of crosstalks between jasmonic acid (JA) and other plant hormones in plant growth and stress responses. Based on these studies, this paper mainly reviews the crosstalks between JA and other plant hormone signaling in regulating the balance between plant growth and defense response. The suppressor proteins JASMONATE ZIM DOMAIN PROTEIN (JAZ) and MYC2 as the key components in the crosstalks are also highlighted in the review. We conclude that JA interacts with other hormone signaling pathways such as auxin, ethylene (ET), abscisic acid (ABA), salicylic acid (SA), brassinosteroids (BRs), and gibberellin (GA) to regulate plant growth, abiotic stress tolerance, and defense resistance against hemibiotrophic pathogens such as
Magnaporthe oryzae
and
Pseudomonas syringae
. Notably, JA may act as a core signal in the phytohormone signaling network.
An inexpensive, facile, and environmentally benign method has been developed for the preparation of multiresponsive, dynamic, and self-healing chitosan-based hydrogels. A dibenzaldehyde-terminated ...telechelic poly(ethylene glycol) (PEG) was synthesized and was allowed to form Schiff base linkages between the aldehyde groups and the amino groups in chitosan. Upon mixing the telechelic PEG with chitosan at 20 °C, hydrogels with solid content of 4–8% by mass were generated rapidly in <60 s. Because of the dynamic equilibrium between the Schiff base linkage and the aldehyde and amine reactants, the hydrogels were found to be self-healable and sensitive to many biochemical-stimuli, such as pH, amino acids, and vitamin B6 derivatives. In addition, chitosan could be digested by enzymes such as papain, leading to the decomposition of the hydrogels. Encapsulation and controlled release of small molecules such as rhodamine B and proteins such as lysozyme have been successfully carried out, demonstrating the potential biomedical applications of these chitosan-based dynamic hydrogels.
Fuzzy C-means clustering algorithm is one of the typical clustering algorithms in data mining applications. However, due to the sensitive information in the dataset, there is a risk of user privacy ...being leaked during the clustering process. The fuzzy C-means clustering of differential privacy protection can protect the user's individual privacy while mining data rules, however, the decline in availability caused by data disturbances is a common problem of these algorithms. Aiming at the problem that the algorithm accuracy is reduced by randomly initializing the membership matrix of fuzzy C-means, in this paper, the maximum distance method is firstly used to determine the initial center point. Then, the gaussian value of the cluster center point is used to calculate the privacy budget allocation ratio. Additionally, Laplace noise is added to complete differential privacy protection. The experimental results demonstrate that the clustering accuracy and effectiveness of the proposed algorithm are higher than baselines under the same privacy protection intensity.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Now more and more data are being outsourced to cloud services. In order to ensure data security and privacy, data are usually stored on the cloud server in the form of ciphertext. When a user ...requests access to the encrypted data, an access key distributed by a third party is needed. However, if the third party is dishonest, the security of the system will be threatened. Faced with this problem, in this paper, we propose a new secure cloud storage framework with access control by using the Ethereum blockchain technology. Our new scheme is a combination of Ethereum blockchain and ciphertext-policy attribute-based encryption (CP-ABE). The proposed cloud storage framework is decentralized, that is, there is no trusted third party in the system. Our scheme has three main features. First, as the Ethereum blockchain technology is used, the data owner can store ciphertext of data through smart contracts in a blockchain network. Second, the data owner can set valid access periods for data usage so that the ciphertext can only be decrypted during valid access periods. Finally, as the creation and invocation of each smart contract can be stored in the blockchain, thus, the function of the trace is achieved. The analysis of the security and experiment shows that our scheme is feasible.
The sharing of personal health records can help to improve the accuracy of the doctor's diagnosis and to promote the progress of medical research. Currently, to reduce the maintenance cost of data, ...personal health records are usually outsourced to a third party such as the cloud service provider. In this case, patients may lose direct control over their personal health records and the semi-trusted cloud service provider may tamper with or reveal personal health records. Therefore, ensuring the privacy and integrity of personal health records and realizing the fine-grained access control are crucial issues when personal health records are shared. As a distributed architecture with decentralized and tamper-proof features, blockchain provides a new way to protect the personal health records sharing system. In this paper, we propose a new personal health records sharing scheme with data integrity verifiable based on blockchain. Aiming at the problems of privacy disclosure, limited keyword search ability and loss of control rights in the process of personal health record sharing, the new scheme uses searchable symmetric encryption and attribute-based encryption techniques to achieve privacy protection, keyword search, and fine-grained access control. Compared with the existing similar schemes, the new scheme allows patients to distribute attribute private key for users, avoiding many security problems caused by the existing of attribute authority in the scheme. Furthermore, the new scheme uses blockchain to manage keys in the scheme, avoiding the single point failure problem of centralized key management. In particular, the new scheme stores the hash values of encrypted personal health records in blockchain, and the related index set is stored in smart contract, which can further improve the efficiency of data integrity verification. Finally, performance evaluation and security analysis indicate that our scheme is secure and feasible for practical use.
This paper, based on differential privacy protecting K-means clustering algorithm, realizes privacy protection by adding data-disturbing Laplace noise to cluster center point. In order to solve the ...problem of Laplace noise randomness which causes the center point to deviate, especially when poor availability of clustering results appears because of small privacy budget parameters, an improved differential privacy protecting K-means clustering algorithm was raised in this paper. The improved algorithm uses the contour coefficients to quantitatively evaluate the clustering effect of each iteration and add different noise to different clusters. In order to be adapted to the huge number of data, this paper provides an algorithm design in MapReduce Framework. Experimental finding shows that the new algorithm improves the availability of the algorithm clustering results under the condition of ensuring individual privacy without significantly increasing its operating time.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
With the improvement of living standard, people begin to pay more attention to food safety and product quality. Therefore, for consumers, it is necessary to establish a reliable system that can trace ...the source of products. However, most existing traceability systems tend to lack transparency, data is primarily stored within the enterprise, and the cost of tampering with data is very low. Besides, the supply chain nodes are easy to evade responsibility when product safety or quality issues arise under the traditional centralized management model, and it is difficult to trace the root of issues. The development of blockchain technology provides us with new ideas for realizing the traceability of products in supply chain scenarios. Due to its characteristics of decentralization, transparency, and immutability, blockchain can be effectively used to alleviate the above problems. In this paper, we propose a product traceability system based on blockchain technology, in which all product transferring histories are perpetually recorded in a distributed ledger by using smart contracts and a chain is formed that can trace back to the source of the products. In particular, we design an event response mechanism to verify the identities of both parties of the transaction, so that the validity of the transaction can be guaranteed. And all events are permanently stored in the form of logs as a basis for handling disputes and tracking responsible entities. Furthermore, a system prototype is constructed based on the testing framework of Truffle. The contract code is deployed on a test network TestRpc that runs in local memory, and a decentralized web page interface is implemented based on the prototype. Finally, the system security analysis and experimental results show that our solution is feasible.
•Accumulated (lagged) drought significantly affected 50% (60%) of the vegetated area in the YRB.•Vegetation in the arid zone tended to be more sensitive and resistant to drought.•Grasslands and crops ...were more vulnerable to accumulated and lagged drought than forests.•Cumulative effect was stronger than lag effect independent of climate zone and vegetation type.•Cumulative and lag effects were significantly correlated with annual water availability.
Yellow River Basin (YRB), a climate-sensitive and ecologically compromised area in China, is increasingly affected by extreme climate events (especially droughts) resulting from climate change and frequent human activity. Vegetation responds asymmetrically to drought with cumulative and time-lag effects, whereas response across various climatic zones and diverse vegetation types in the YRB remains unclear. To address this deficiency, we examined the spatiotemporal patterns of accumulated and lagged drought effects on vegetation dynamics for the period 1982 to 2015. The examination was based on the long-term Normalized Difference Vegetation Index (NDVI) and multiscale dataset of the Standardized Precipitation Evapotranspiration Index (SPEI). Cumulative (time-lag) effects were determined via the maximum correlation between the NDVI and the one- to 12-month timescale SPEI (one-month timescale SPEI), as well as the corresponding months of optimal response to drought. The main findings were as follows: (1) Accumulated and lagged drought significantly affected approximately 50% and 60% of the vegetated area in the YRB, respectively, with the strongest effects and the corresponding optimal months varying across climatic zones and vegetation types. (2) In general, vegetation in the arid zone tended to be more sensitive and resistant to drought, as evidenced by the occurrence of lagged and accumulated drought effects mostly in the short-term (one–three months) and medium-term (six–eight months), respectively. This finding may be related to the vegetation’s strategy for coping with water deficits. (3) The biome-level effects of drought on grassland and cultivated vegetation were stronger than those on forests, which may be associated with differences in the functional characteristics of root systems. (4) Annual water availability significantly affected the spatiotemporal patterns by which the NDVI responded to droughts of multiple timescales, with the correlation coefficients and corresponding months of response decreasing with increasing average annual SPEI. These results indicate that vegetated areas with low water availability were more susceptible to cumulative (time-lag) droughts. (5) Independent of the climate zone or vegetation type, drought cumulatively affected vegetation more than time-lag effects. The study improves the knowledge of climate–vegetation relationships in the YRB and provides theoretical support for addressing drought risk in a changing climate.
PDF
