A hyperelliptic curve digital signature algorithm （HECDSA） can be viewed as the hyperelliptic curve analogue of the standard digital signature algorithm （DSA）. This article discusses divisor evaluations, the basic...A hyperelliptic curve digital signature algorithm （HECDSA） can be viewed as the hyperelliptic curve analogue of the standard digital signature algorithm （DSA）. This article discusses divisor evaluations, the basic HECDSA, variants, two HECDSA equations and a 4-tuple HECDSA scheme, and puts forward a generalized equation for HECDSA. From this generalized equation, seven general HECDSA types are derived based on the efficiency requirements. Meanwhile, the securities of these general HECDSA types are analyzed in detail.展开更多
With the rapid development and widespread application of Wireless Body Area Networks(WBANs),the traditional centralized system architecture cannot handle the massive data generated by the edge devices.Meanwhile,in ord...With the rapid development and widespread application of Wireless Body Area Networks(WBANs),the traditional centralized system architecture cannot handle the massive data generated by the edge devices.Meanwhile,in order to ensure the security of physiological privacy data and the identity privacy of patients,this paper presents a privacy protection strategy for Mobile Edge Computing(MEC)enhanced WBANs,which leverages the blockchain-based decentralized MEC paradigm to support efficient transmission of privacy information with low latency,high reliability within a high-demand data security scenario.On this basis,the Merkle tree optimization model is designed to authenticate nodes and to verify the source of physiological data.Furthermore,a hybrid signature algorithm is devised to guarantee the node anonymity with unforgeability,data integrity and reduced delay.The security performance analysis and simulation results show that our proposed strategy not only reduces the delay,but also secures the privacy and transmission of sensitive WBANs data.展开更多
Cloud computing has reached the peak of Gartner hype cycle,and now the focus of the whole telecom industry is the ability to scale data storage with minimal investment.But data privacy and communication issues will oc...Cloud computing has reached the peak of Gartner hype cycle,and now the focus of the whole telecom industry is the ability to scale data storage with minimal investment.But data privacy and communication issues will occur with the increment of the cloud data storage.The key privacy concern for scalability is caused by the dynamic membership allocation and multi-owner data sharing.This paper addresses the issues faced by multiple owners through a mutual authentication mechanism using the Enhanced Elliptic Curve Diffie-Hellman(EECDH)key exchange protocol along with the Elliptic Curve Digital Signature Algorithm(ECDSA).The proposed EECDH scheme is used to exchange the secured shared key among multiple owners and also to eliminate the Man-In-The-Middle(MITM)attacks with less computational complexity.By leveraging these algorithms,the integrity of data sharing among multiple owners is ensured.The EECDH improves the level of security only slightly increasing the time taken to encrypt and decrypt the data,and it is secured against the MITM attacks,which is experimented using the AVISPA tool.展开更多
The concept of batch verifying multiple digital signatures is to find a method by which multiple digital signatures can be verified simultaneously in a lower time complexity than separately verifying all the signature...The concept of batch verifying multiple digital signatures is to find a method by which multiple digital signatures can be verified simultaneously in a lower time complexity than separately verifying all the signatures. In this article, we analyze the complexity of the batch verifying schemes defined by Li, Hwang and Chen in 2010, and propose a new batch verifying multiple digital signature scheme, in two variants： one for RSA - by completing the Harn＇s schema with an identifying illegal signatures algorithm, and the other adapted for a modified Elliptic Curve Digital Siggnature Algorithm protocol.展开更多
Neoadjuvant chemotherapy for breast cancer patients with large tumor size is a necessary treatment.After this treatment patients who achieve a pathologic Complete Response（p CR） usually have a favorable prognosis th...Neoadjuvant chemotherapy for breast cancer patients with large tumor size is a necessary treatment.After this treatment patients who achieve a pathologic Complete Response（p CR） usually have a favorable prognosis than those without. Therefore, p CR is now considered as the best prognosticator for patients with neoadjuvant chemotherapy. However, not all patients can benefit from this treatment. As a result, we need to find a way to predict what kind of patients can induce p CR. Various gene signatures of chemosensitivity in breast cancer have been identified, from which such predictors can be built. Nevertheless, many of them have their prediction accuracy around 80%. As such, identifying gene signatures that could be employed to build high accuracy predictors is a prerequisite for their clinical tests and applications. Furthermore, to elucidate the importance of each individual gene in a signature is another pressing need before such signature could be tested in clinical settings. In this study, Genetic Algorithm（GA） and Sparse Logistic Regression（SLR） along with t-test were employed to identify one signature. It had 28 probe sets selected by GA from the top 65 probe sets that were highly overexpressed between p CR and Residual Disease（RD） and was used to build an SLR predictor of p CR（SLR-28）. This predictor tested on a training set（n = 81） and validation set（n = 52） had very precise predictions measured by accuracy,specificity, sensitivity, positive predictive value, and negative predictive value with their corresponding P value all zero. Furthermore, this predictor discovered 12 important genes in the 28 probe set signature. Our findings also demonstrated that the most discriminative genes measured by SLR as a group selected by GA were not necessarily those with the smallest P values by t-test as individual genes, highlighting the ability of GA to capture the interacting genes in p CR prediction as multivariate techniques. Our gene signature produced superior performance over a signature found in one previous study with prediction accuracy 92% vs 76%, demonstrating the potential of GA and SLR in identifying robust gene signatures in chemo response prediction in breast cancer.展开更多
基金supported by the National Natural Science Foundation of China (60763009)the Science and Technology Key Project of the Ministry of Education of China (207089)Zhejiang Natural Science Foundation of Outstanding Youth Team Project (R1090138)
文摘A hyperelliptic curve digital signature algorithm （HECDSA） can be viewed as the hyperelliptic curve analogue of the standard digital signature algorithm （DSA）. This article discusses divisor evaluations, the basic HECDSA, variants, two HECDSA equations and a 4-tuple HECDSA scheme, and puts forward a generalized equation for HECDSA. From this generalized equation, seven general HECDSA types are derived based on the efficiency requirements. Meanwhile, the securities of these general HECDSA types are analyzed in detail.
基金This work was supported in part by the National Natural Science Foundation of China(61871062,61771082 and 61901071)in part by the Program for Innovation Team Building at Institutions of Higher Education in Chongqing(CXTDX201601020)+1 种基金Science and Technology Research Program of Chongqing Municipal Education Commission(KJQN201800615)General Project of Natural Science Foundation of Chongqing(cstc2019jcyj-msxm1238).
文摘With the rapid development and widespread application of Wireless Body Area Networks(WBANs),the traditional centralized system architecture cannot handle the massive data generated by the edge devices.Meanwhile,in order to ensure the security of physiological privacy data and the identity privacy of patients,this paper presents a privacy protection strategy for Mobile Edge Computing(MEC)enhanced WBANs,which leverages the blockchain-based decentralized MEC paradigm to support efficient transmission of privacy information with low latency,high reliability within a high-demand data security scenario.On this basis,the Merkle tree optimization model is designed to authenticate nodes and to verify the source of physiological data.Furthermore,a hybrid signature algorithm is devised to guarantee the node anonymity with unforgeability,data integrity and reduced delay.The security performance analysis and simulation results show that our proposed strategy not only reduces the delay,but also secures the privacy and transmission of sensitive WBANs data.
文摘Cloud computing has reached the peak of Gartner hype cycle,and now the focus of the whole telecom industry is the ability to scale data storage with minimal investment.But data privacy and communication issues will occur with the increment of the cloud data storage.The key privacy concern for scalability is caused by the dynamic membership allocation and multi-owner data sharing.This paper addresses the issues faced by multiple owners through a mutual authentication mechanism using the Enhanced Elliptic Curve Diffie-Hellman(EECDH)key exchange protocol along with the Elliptic Curve Digital Signature Algorithm(ECDSA).The proposed EECDH scheme is used to exchange the secured shared key among multiple owners and also to eliminate the Man-In-The-Middle(MITM)attacks with less computational complexity.By leveraging these algorithms,the integrity of data sharing among multiple owners is ensured.The EECDH improves the level of security only slightly increasing the time taken to encrypt and decrypt the data,and it is secured against the MITM attacks,which is experimented using the AVISPA tool.
文摘The concept of batch verifying multiple digital signatures is to find a method by which multiple digital signatures can be verified simultaneously in a lower time complexity than separately verifying all the signatures. In this article, we analyze the complexity of the batch verifying schemes defined by Li, Hwang and Chen in 2010, and propose a new batch verifying multiple digital signature scheme, in two variants： one for RSA - by completing the Harn＇s schema with an identifying illegal signatures algorithm, and the other adapted for a modified Elliptic Curve Digital Siggnature Algorithm protocol.
文摘Neoadjuvant chemotherapy for breast cancer patients with large tumor size is a necessary treatment.After this treatment patients who achieve a pathologic Complete Response（p CR） usually have a favorable prognosis than those without. Therefore, p CR is now considered as the best prognosticator for patients with neoadjuvant chemotherapy. However, not all patients can benefit from this treatment. As a result, we need to find a way to predict what kind of patients can induce p CR. Various gene signatures of chemosensitivity in breast cancer have been identified, from which such predictors can be built. Nevertheless, many of them have their prediction accuracy around 80%. As such, identifying gene signatures that could be employed to build high accuracy predictors is a prerequisite for their clinical tests and applications. Furthermore, to elucidate the importance of each individual gene in a signature is another pressing need before such signature could be tested in clinical settings. In this study, Genetic Algorithm（GA） and Sparse Logistic Regression（SLR） along with t-test were employed to identify one signature. It had 28 probe sets selected by GA from the top 65 probe sets that were highly overexpressed between p CR and Residual Disease（RD） and was used to build an SLR predictor of p CR（SLR-28）. This predictor tested on a training set（n = 81） and validation set（n = 52） had very precise predictions measured by accuracy,specificity, sensitivity, positive predictive value, and negative predictive value with their corresponding P value all zero. Furthermore, this predictor discovered 12 important genes in the 28 probe set signature. Our findings also demonstrated that the most discriminative genes measured by SLR as a group selected by GA were not necessarily those with the smallest P values by t-test as individual genes, highlighting the ability of GA to capture the interacting genes in p CR prediction as multivariate techniques. Our gene signature produced superior performance over a signature found in one previous study with prediction accuracy 92% vs 76%, demonstrating the potential of GA and SLR in identifying robust gene signatures in chemo response prediction in breast cancer.
