Background:The ongoing COVID-19 pandemic hit South America badly with multiple waves.Different COVID-19 variants have been storming across the region,leading to more severe infections and deaths even in places with hi...Background:The ongoing COVID-19 pandemic hit South America badly with multiple waves.Different COVID-19 variants have been storming across the region,leading to more severe infections and deaths even in places with high vaccination coverage.This study aims to assess the spatiotemporal variability of the COVID-19 pandemic and estimate the infection fatality rate(IFR),infection attack rate(IAR)and reproduction number(R0)for twelve most affected South American countries.Methods:We fit a susceptible-exposed-infectious-recovered(SEIR)-based model with a time-varying transmission rate to the reported COVID-19 deaths for the twelve South American countries with the highest mortalities.Most of the epidemiological datasets analysed in this work are retrieved from the disease surveillance systems by the World Health Organization,Johns Hopkins Coronavirus Resource Center and Our World in Data.We investigate the COVID-19 mortalities in these countries,which could represent the situation for the overall South American region.We employ COVID-19 dynamic model with-and-without vaccination considering time-varying flexible transmission rate to estimate IFR,IAR and R0 of COVID-19 for the South American countries.Results:We simulate the model in each scenario under suitable parameter settings and yield biologically reasonable estimates for IFR(varies between 0.303% and 0.723%),IAR(varies between 0.03 and 0.784)and R0(varies between 0.7 and 2.5)for the 12 South American countries.We observe that the severity,dynamical patterns of deaths and time-varying transmission rates among the countries are highly heterogeneous.Further analysis of the model with the effect of vaccination highlights that increasing the vaccination rate could help suppress the pandemic in South America.Conclusions:This study reveals possible reasons for the two waves of COVID-19 outbreaks in South America.We observed reductions in the transmission rate corresponding to each wave plausibly due to improvement in nonpharmaceutical interventions measures and human protective behavioral reaction to recent deaths.Thus,strategies coupling social distancing and vaccination could substantially suppress the mortality rate of COVID-19 in South America.展开更多
Objectives:Serological surveys were used to infer the infection attack rate in different populations.The sensitivity of the testing assay,Abbott,drops fast over time since infection which makes the serological data di...Objectives:Serological surveys were used to infer the infection attack rate in different populations.The sensitivity of the testing assay,Abbott,drops fast over time since infection which makes the serological data difficult to interpret.In this work,we aim to solve this issue.Methods:We collect longitudinal serological data of Abbott to construct a sensitive decay function.We use the reported COVID-19 deaths to infer the infections,and use the decay function to simulate the seroprevalence and match to the reported seroprevalence in 12 Indian cities.Results:Our model simulated seroprevalence matchs the reported seroprevalence in most of the 12 Indian cities.We obtain reasonable infection attack rate and infection fatality rate for most of the 12 Indian cities.Conclusions:Using both reported COVID-19 deaths data and serological survey data,we infer the infection attack rate and infection fatality rate with increased confidence.展开更多
The measured relative rates of halophilic and protophilic attacks (k_X/k_H) indicate that the rates of halophilic attacks are comparable in magnitude to those of protophilic attacks (deprotonations).
Similar to device-independent quantum key distribution （DI-QKD）, semi-device-independent quantum key distribu- tion （SDI-QKD） provides secure key distribution without any assumptions about the internal workings of...Similar to device-independent quantum key distribution （DI-QKD）, semi-device-independent quantum key distribu- tion （SDI-QKD） provides secure key distribution without any assumptions about the internal workings of the QKD devices. The only assumption is that the dimension of the Hilbert space is bounded. But SDI-QKD can be implemented in a one- way prepare-and-measure configuration without entanglement compared with DI-QKD. We propose a practical SDI-QKD protocol with four preparation states and three measurement bases by considering the maximal violation of dimension witnesses and specific processes of a QKD protocol. Moreover, we prove the security of the SDI-QKD protocol against collective attacks based on the min-entropy and dimension witnesses. We also show a comparison of the secret key rate between the SDI-QKD protocol and the standard QKD.展开更多
In any side-channel attack, it is desirable to exploit all the available leakage data to compute the distinguisher’s values. The profiling phase is essential to obtain an accurate leakage model, yet it may not be exh...In any side-channel attack, it is desirable to exploit all the available leakage data to compute the distinguisher’s values. The profiling phase is essential to obtain an accurate leakage model, yet it may not be exhaustive. As a result, information theoretic distinguishers may come up on previously unseen data, a phenomenon yielding empty bins. A strict application of the maximum likelihood method yields a distinguisher that is not even sound. Ignoring empty bins reestablishes soundness, but seriously limits its performance in terms of success rate. The purpose of this paper is to remedy this situation. In this research, we propose six different techniques to improve the performance of information theoretic distinguishers. We study t</span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">hem thoroughly by applying them to timing attacks, both with synthetic and real leakages. Namely, we compare them in terms of success rate, and show that their performance depends on the amount of profiling, and can be explained by a bias-variance analysis. The result of our work is that there exist use-cases, especially when measurements are noisy, where our novel information theoretic distinguishers (typically the soft-drop distinguisher) perform the best compared to known side-channel distinguishers, despite the empty bin situation.展开更多
Mobile Ad-Hoc Networks (MANETs) are highly vulnerable to insider jamming attacks. Several approaches to detect insider jammers in MANET have been proposed. However, once the insider jammer is detected and removed from...Mobile Ad-Hoc Networks (MANETs) are highly vulnerable to insider jamming attacks. Several approaches to detect insider jammers in MANET have been proposed. However, once the insider jammer is detected and removed from the network, it is possible for the insider jammer to leverage the knowledge of insider information to launch a future attack. In this paper, we focus on collaborative smart jamming attacks, where the attackers who have been detected as insider jammers in a MANET, return to attack the MANET based on the knowledge learned. The MANET uses a reputation-based coalition game to detect insider jammers. In the collaborative smart jamming attack, two or more smart jammers will form a coalition to attack the coalitions in the MANET. The smart jammers were detected and then excluded from their initial coalition, they then regrouped to start their own coalition and share previously gained knowledge about legitimate nodes in their erstwhile coalition with the aim of achieving a highly coordinated successful jamming attack on the legitimate coalition. The success of the attack largely depends on the insider jammer’s collective knowledge about the MANET. We present a technique to appropriately represent knowledge gathered by insider jammers which would lead to a successful attack. Simulation results in NS2 depict that coalition of jammers can leverage past knowledge to successfully attack MANET.展开更多
基金partially supported by a grant from the Research Grants Council of the Hong Kong Special Administrative Region,China(HKU C7123-20G)。
文摘Background:The ongoing COVID-19 pandemic hit South America badly with multiple waves.Different COVID-19 variants have been storming across the region,leading to more severe infections and deaths even in places with high vaccination coverage.This study aims to assess the spatiotemporal variability of the COVID-19 pandemic and estimate the infection fatality rate(IFR),infection attack rate(IAR)and reproduction number(R0)for twelve most affected South American countries.Methods:We fit a susceptible-exposed-infectious-recovered(SEIR)-based model with a time-varying transmission rate to the reported COVID-19 deaths for the twelve South American countries with the highest mortalities.Most of the epidemiological datasets analysed in this work are retrieved from the disease surveillance systems by the World Health Organization,Johns Hopkins Coronavirus Resource Center and Our World in Data.We investigate the COVID-19 mortalities in these countries,which could represent the situation for the overall South American region.We employ COVID-19 dynamic model with-and-without vaccination considering time-varying flexible transmission rate to estimate IFR,IAR and R0 of COVID-19 for the South American countries.Results:We simulate the model in each scenario under suitable parameter settings and yield biologically reasonable estimates for IFR(varies between 0.303% and 0.723%),IAR(varies between 0.03 and 0.784)and R0(varies between 0.7 and 2.5)for the 12 South American countries.We observe that the severity,dynamical patterns of deaths and time-varying transmission rates among the countries are highly heterogeneous.Further analysis of the model with the effect of vaccination highlights that increasing the vaccination rate could help suppress the pandemic in South America.Conclusions:This study reveals possible reasons for the two waves of COVID-19 outbreaks in South America.We observed reductions in the transmission rate corresponding to each wave plausibly due to improvement in nonpharmaceutical interventions measures and human protective behavioral reaction to recent deaths.Thus,strategies coupling social distancing and vaccination could substantially suppress the mortality rate of COVID-19 in South America.
基金supported by a grant from the Research Grants Council of the Hong Kong Special Administrative Region,China(HKU C7123-20G).
文摘Objectives:Serological surveys were used to infer the infection attack rate in different populations.The sensitivity of the testing assay,Abbott,drops fast over time since infection which makes the serological data difficult to interpret.In this work,we aim to solve this issue.Methods:We collect longitudinal serological data of Abbott to construct a sensitive decay function.We use the reported COVID-19 deaths to infer the infections,and use the decay function to simulate the seroprevalence and match to the reported seroprevalence in 12 Indian cities.Results:Our model simulated seroprevalence matchs the reported seroprevalence in most of the 12 Indian cities.We obtain reasonable infection attack rate and infection fatality rate for most of the 12 Indian cities.Conclusions:Using both reported COVID-19 deaths data and serological survey data,we infer the infection attack rate and infection fatality rate with increased confidence.
文摘The measured relative rates of halophilic and protophilic attacks (k_X/k_H) indicate that the rates of halophilic attacks are comparable in magnitude to those of protophilic attacks (deprotonations).
基金Project supported by the National Basic Research Program of China(Grant No.2013CB338002)the National Natural Science Foundation of China(Grant Nos.11304397 and 11204379)
文摘Similar to device-independent quantum key distribution （DI-QKD）, semi-device-independent quantum key distribu- tion （SDI-QKD） provides secure key distribution without any assumptions about the internal workings of the QKD devices. The only assumption is that the dimension of the Hilbert space is bounded. But SDI-QKD can be implemented in a one- way prepare-and-measure configuration without entanglement compared with DI-QKD. We propose a practical SDI-QKD protocol with four preparation states and three measurement bases by considering the maximal violation of dimension witnesses and specific processes of a QKD protocol. Moreover, we prove the security of the SDI-QKD protocol against collective attacks based on the min-entropy and dimension witnesses. We also show a comparison of the secret key rate between the SDI-QKD protocol and the standard QKD.
文摘In any side-channel attack, it is desirable to exploit all the available leakage data to compute the distinguisher’s values. The profiling phase is essential to obtain an accurate leakage model, yet it may not be exhaustive. As a result, information theoretic distinguishers may come up on previously unseen data, a phenomenon yielding empty bins. A strict application of the maximum likelihood method yields a distinguisher that is not even sound. Ignoring empty bins reestablishes soundness, but seriously limits its performance in terms of success rate. The purpose of this paper is to remedy this situation. In this research, we propose six different techniques to improve the performance of information theoretic distinguishers. We study t</span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">hem thoroughly by applying them to timing attacks, both with synthetic and real leakages. Namely, we compare them in terms of success rate, and show that their performance depends on the amount of profiling, and can be explained by a bias-variance analysis. The result of our work is that there exist use-cases, especially when measurements are noisy, where our novel information theoretic distinguishers (typically the soft-drop distinguisher) perform the best compared to known side-channel distinguishers, despite the empty bin situation.
文摘Mobile Ad-Hoc Networks (MANETs) are highly vulnerable to insider jamming attacks. Several approaches to detect insider jammers in MANET have been proposed. However, once the insider jammer is detected and removed from the network, it is possible for the insider jammer to leverage the knowledge of insider information to launch a future attack. In this paper, we focus on collaborative smart jamming attacks, where the attackers who have been detected as insider jammers in a MANET, return to attack the MANET based on the knowledge learned. The MANET uses a reputation-based coalition game to detect insider jammers. In the collaborative smart jamming attack, two or more smart jammers will form a coalition to attack the coalitions in the MANET. The smart jammers were detected and then excluded from their initial coalition, they then regrouped to start their own coalition and share previously gained knowledge about legitimate nodes in their erstwhile coalition with the aim of achieving a highly coordinated successful jamming attack on the legitimate coalition. The success of the attack largely depends on the insider jammer’s collective knowledge about the MANET. We present a technique to appropriately represent knowledge gathered by insider jammers which would lead to a successful attack. Simulation results in NS2 depict that coalition of jammers can leverage past knowledge to successfully attack MANET.
