Mammography combined with breast dynamic contrast-enhanced-magnetic resonance imaging for the diagnosis of early breast cancer

Objective The aim of this study was to investigate the application of mammography combined with breast dynamic contrast-enhanced magnetic resonance imaging(DCE-MRI) for the diagnosis of early breast cancer. Methods Mammography and DCE-MRI were performed for 120 patients with breast cancer(malignant, 102; benign; 18). Results The sensitivity of mammography for early diagnosis of breast cancer was 66.67%, specificity was 77.78%, and accuracy was 68.33%. The sensitivity of MRI for early diagnosis of breast cancer was 94.12%, specificity was 88.89%, and accuracy was 93.33%. However, the sensitivity of mammography combined with DCE-MRI volume imaging with enhanced water signal(VIEWS) scanning for early diagnosis of breast cancer was 97.06%, specificity was 94.44%, and accuracy was 96.67%. Conclusion Mammography combined with DCE-MRI increased the sensitivity, specificity, and accuracy of diagnosing early breast cancer.

Study on Brewing Properties of Three Strong Ale Beer Yeasts

The brewing characteristics of three kinds of beer yeasts commonly used in the market were compared and studied.The results showed that the three kinds of yeasts had different characteristics and slightly different fermentation degrees,but the fermentation speeds all were higher and the diacetyl reduction ability was excellent.The finished beers were golden yellow in appearance,rich and delicate in foam,pleasant in aroma,mellow in body and similar in physicochemical indexes,all in line with domestic beer standards.

EMPSI:Efficient multiparty private set intersection(with cardinality)

Multiparty private set intersection(PSI)allows several parties,each holding a set of elements,to jointly compute the intersection without leaking any additional information.With the development of cloud computing,PSI has a wide range of applications in privacy protection.However,it is complex to build an efficient and reliable scheme to protect user privacy.To address this issue,we propose EMPSI,an efficient PSI(with cardinality)protocol in a multiparty setting.EMPSI avoids using heavy cryptographic primitives(mainly rely on symmetric-key encryption)to achieve better performance.In addition,both PSI and PSI with the cardinality of EMPSI are secure against semi-honest adversaries and allow any number of colluding clients(at least one honest client).We also do experiments to compare EMPSI with some state-of-the-art works.The experimental results show that proposed EMPSI(-CA)has better performance and is scalable in the number of clients and the set size.

IXT: Improved searchable encryption for multi-word queries based on PSI

Oblivious Cross-Tags(OXT)[1]is the first efficient searchable encryption(SE)protocol for conjunctive queries in a single-writer single-reader framework.However,it also has a trade-off between security and efficiency by leaking partial database information to the server.Recent attacks on these SE schemes show that the leakages from these SE schemes can be used to recover the content of queried keywords.To solve this problem,Lai et al.[2]propose Hidden Cross-Tags(HXT),which reduces the access pattern leakage from Keyword Pair Result Pattern(KPRP)to Whole Result Pattern(WRP).However,the WRP leakage can also be used to recover some additional contents of queried keywords.This paper proposes Improved Cross-Tags(IXT),an efficient searchable encryption protocol that achieves access and searches pattern hiding based on the labeled private set intersection.We also prove the proposed labeled private set intersection(PSI)protocol is secure against semi-honest adversaries,and IXT is-semi-honest secure(is leakage function).Finally,we do experiments to compare IXT with HXT.The experimental results show that the storage overhead and computation overhead of the search phase at the client-side in IXT is much lower than those in HXT.Meanwhile,the experimental results also show that IXT is scalable and can be applied to various sizes of datasets.

A verifiable privacy-preserving data collection scheme supporting multi-party computation in fog-based smart grid

Incorporation of fog computing with low latency,preprocession(e.g.,data aggregation)and location awareness,can facilitate fine-grained collection of smart metering data in smart grid and promotes the sustainability and efficiency of the grid.Recently,much attention has been paid to the research on smart grid,especially in protecting privacy and data aggregation.However,most previous works do not focus on privacy-preserving data aggregation and function computation query on enormous data simultaneously in smart grid based on fog computation.In this paper,we construct a novel verifiable privacy-preserving data collection scheme supporting multi-party computation(MPC),named VPDC-MPC,to achieve both functions simultaneously in smart grid based on fog computing.VPDC-MPC realizes verifiable secret sharing of users’data and data aggregation without revealing individual reports via practical cryptosystem and verifiable secret sharing scheme.Besides,we propose an efficient algorithm for batch verification of share consistency and detection of error reports if the external adversaries modify the SMs’report.Furthermore,VPDC-MPC allows both the control center and users with limited resources to obtain arbitrary arithmetic analysis(not only data aggregation)via secure multi-party computation between cloud servers in smart grid.Besides,VPDC-MPC tolerates fault of cloud servers and resists collusion.We also present security analysis and performance evaluation of our scheme,which indicates that even with tradeoff on computation and communication overhead,VPDC-MPC is practical with above features.