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In e-healthcare system, an increasing number of patients enjoy high-quality medical services by sharing encrypted personal healthcare records (PHRs) with doctors or medical research institutions. However, one of the important issues is that the encrypted PHRs prevent effective search of information, resulting in the decrease of data usage. Another issue is that medical treatment process requires the doctor to be online all the time, which may be unaffordable for all doctors (e.g., to be absent under certain circumstances). In this paper, we design a new secure and practical proxy searchable re-encryption scheme, allowing medical service providers to achieve remote PHRs monitoring and research safely and efficiently. Through our scheme DSAS, (1) patients’ healthcare records collected by the devices are encrypted before uploading to the cloud server ensuring privacy and confidentiality of PHRs; (2) only authorized doctors or research institutions have access to the PHRs; (3) Alice (doctor-in-charge) is able to delegate medical research and utilization to Bob (doctor-in-agent) or certain research institution through the cloud server, supporting minimizing information exposure to the cloud server. We formalize the security definition and prove the security of our scheme. Finally, performance evaluation shows the efficiency of our scheme.

With the sustained evolution and expeditious popularization of cloud computing, an ever-increasing number of individuals and enterprises are encouraged to outsource data to cloud servers for reducing management overhead and ease of access. Privacy requirements demand encryption of sensitive information before outsourcing, which, on the other hand, diminishes the usability of data and makes considerable efficient keyword search techniques used on plaintext inapplicable. In this paper, we propose a secure multi-keyword ranked search scheme based on document similarity to work out the problem. In order to achieve the goals of multi-keyword search and ranking search results, we adopt the vector space model and TF-IDF model to generate index and query vectors. By introducing the secure kNN computation, index and query vectors can be encrypted to prevent cloud servers from obtaining sensitive frequency information. For the need of efficiency advancement, we adopt the $B^{+}$ -tree as the basic structure to build the index and construct a similar document collection for each document. Due to the use of our unique index structure, compared to linear search, the search efficiency is more exceptional. Extensive experiments on the real-world document collection are conducted to demonstrate the feasibility and efficiency of the proposed solution.

We present a fiber sensing for temperature with two different mode interferences. The sensor consists of a single mode-multimode-single mode (SMS) fiber with a specifically designed and synthesized thermo-optic polymer cladding, forming a leaky mode fiber interferometer and a guided one at different temperatures. A maximum temperature sensitivity of 1.4 dB/°C below 61°C and of 15 nm/°C above 72°C have been achieved. The high temperature sensitivity is mainly attributed to the high thermo-optic coefficient of the polymer cladding. The phenomenon of the fiber temperature sensing around the transformation point can be observed and studied using the proposed fiber sample. It is found that the SMS fiber sensor is more sensitive to temperature for both of the mode interferences when the refractive index (RI) of the polymer is closer to that of the multimode fiber core, and the measurement range is relatively wide. [ABSTRACT FROM PUBLISHER]