m2-ABKS: Attribute-Based Multi-Keyword Search over Encrypted Personal Health Records in Multi-Owner Setting.

Online personal health record (PHR) is more inclined to shift data storage and search operations to cloud server so as to enjoy the elastic resources and lessen computational burden in cloud storage. As multiple patients' data is always stored in the cloud server simultaneously, it is a challenge to guarantee the confidentiality of PHR data and allow data users to search encrypted data in an efficient and privacy-preserving way. To this end, we design a secure cryptographic primitive called as attribute-based multi-keyword search over encrypted personal health records in multi-owner setting to support both fine-grained access control and multi-keyword search via Ciphertext-Policy Attribute-Based Encryption. Formal security analysis proves our scheme is selectively secure against chosen-keyword attack. As a further contribution, we conduct empirical experiments over real-world dataset to show its feasibility and practicality in a broad range of actual scenarios without incurring additional computational burden.

IRLT: Integrating Reputation and Local Trust for Trustworthy Service Recommendation in Service-Oriented Social Networks.

With the prevalence of Social Networks (SNs) and services, plenty of trust models for Trustworthy Service Recommendation (TSR) in Service-oriented SNs (S-SNs) have been proposed. The reputation-based schemes usually do not contain user preferences and are vulnerable to unfair rating attacks. Meanwhile, the local trust-based schemes generally have low reliability or even fail to work when the trust path is too long or does not exist. Thus it is beneficial to integrate them for TSR in S-SNs. This work improves the state-of-the-art Combining Global and Local Trust (CGLT) scheme and proposes a novel Integrating Reputation and Local Trust (IRLT) model which mainly includes four modules, namely Service Recommendation Interface (SRI) module, Local Trust-based Trust Evaluation (LTTE) module, Reputation-based Trust Evaluation (RTE) module and Aggregation Trust Evaluation (ATE) module. Besides, a synthetic S-SN based on the famous Advogato dataset is deployed and the well-known Discount Cumulative Gain (DCG) metric is employed to measure the service recommendation performance of our IRLT model with comparing to that of the excellent CGLT model. The results illustrate that our IRLT model is slightly superior to the CGLT model in honest environment and significantly outperforms the CGLT model in terms of the robustness against unfair rating attacks.

Investigation of High-Energy Ion-Irradiated MA957 Using Synchrotron Radiation under In-Situ Tension.

In this study, an MA957 oxide dispersion-strengthened (ODS) alloy was irradiated with high-energy ions in the Argonne Tandem Linac Accelerator System. Fe ions at an energy of 84 MeV bombarded MA957 tensile specimens, creating a damage region ~7.5 µm in depth; the peak damage (~40 dpa) was estimated to be at ~7 µm from the surface. Following the irradiation, in-situ high-energy X-ray diffraction measurements were performed at the Advanced Photon Source in order to study the dynamic deformation behavior of the specimens after ion irradiation damage. In-situ X-ray measurements taken during tensile testing of the ion-irradiated MA957 revealed a difference in loading behavior between the irradiated and un-irradiated regions of the specimen. At equivalent applied stresses, lower lattice strains were found in the radiation-damaged region than those in the un-irradiated region. This might be associated with a higher level of Type II stresses as a result of radiation hardening. The study has demonstrated the feasibility of combining high-energy ion radiation and high-energy synchrotron X-ray diffraction to study materials' radiation damage in a dynamic manner.