In 2010,Lee et al proposed two simple and efficient three-party password-authenticated key exchange protocols that had been proven secure in the random oracle model.They argued that the two protocols could resist offl...In 2010,Lee et al proposed two simple and efficient three-party password-authenticated key exchange protocols that had been proven secure in the random oracle model.They argued that the two protocols could resist offline dictionary attacks.Indeed,the provable approach did not provide protection against off-line dictionary attacks.This paper shows that the two protocols are vulnerable to off-line dictionary attacks in the presence of an inside attacker because of an authentication flaw.This study conducts a detailed analysis on the flaw in the protocols and also shows how to eliminate the security flaw.展开更多
Power Line Communications-Artificial Intelligence of Things(PLC-AIo T)combines the low cost and high coverage of PLC with the learning ability of Artificial Intelligence(AI)to provide data collection and transmission ...Power Line Communications-Artificial Intelligence of Things(PLC-AIo T)combines the low cost and high coverage of PLC with the learning ability of Artificial Intelligence(AI)to provide data collection and transmission capabilities for PLC-AIo T devices in smart parks.With the development of smart parks,their emerging services require secure and accurate time synchronization of PLC-AIo T devices.However,the impact of attackers on the accuracy of time synchronization cannot be ignored.To solve the aforementioned problems,we propose a tampering attack-aware Deep Q-Network(DQN)-based time synchronization algorithm.First,we construct an abnormal clock source detection model.Then,the abnormal clock source is detected and excluded by comparing the time synchronization information between the device and the gateway.Finally,the proposed algorithm realizes the joint guarantee of high accuracy and low delay for PLC-AIo T in smart parks by intelligently selecting the multi-clock source cooperation strategy and timing weights.Simulation results show that the proposed algorithm has better time synchronization delay and accuracy performance.展开更多
The number and creativity of side channel attacks have increased dramatically in recent years. Of particular interest are attacks leveraging power line communication to 1) gather information on power consumption from ...The number and creativity of side channel attacks have increased dramatically in recent years. Of particular interest are attacks leveraging power line communication to 1) gather information on power consumption from the victim and 2) exfiltrate data from compromised machines. Attack strategies of this nature on the greater power grid and building infrastructure levels have been shown to be a serious threat. This project further explores this concept of a novel attack vector by creating a new type of penetration testing tool: an USB power adapter capable of remote monitoring of device power consumption and communicating through powerline communications.展开更多
To address the challenges posed by tunnel construction in the alpine region,silica fume mixed concrete is commonly used as a construction material.The correlation between silica fume content and the lining life requir...To address the challenges posed by tunnel construction in the alpine region,silica fume mixed concrete is commonly used as a construction material.The correlation between silica fume content and the lining life requires immediate investigation.In view of this phenomenon,the durability of unit lining concrete is predicted by analyzing three key indicators:carbonation depth,relative dynamic elastic modulus,and residual quality.This prediction is achieved by integrating the Entropy Weight Method,Grey theory life prediction model and BP artificial neural networks using data from tests and predictions of these indicators.Then,the Entropy Weight-Grey theory-BP Network Model is compared with other methods to analyze the predicted life.Finally,verify the sci-entificity of this model,and the optimum silica fume content of unit concrete lining is verified.The results showed,1)The addition of silica fume will accelerate the carbonization of unit concrete lining,and slow down the freeze-thaw cycle and sulfate erosion.2)The utilization of artificial neural networks is essential for enhancing the realism of the data,as it emphasizes the significance of silica fume content.3)Silica fume content of 10%results in the longest life and is the most suitable for lining construction.4)A comparison between single-factor and multi-factor predictions indicates that the multi-factor approach yields a longer maximum life.This improvement can be attributed to the inclusion of additional factors,such as freeze-thaw cycles and carbonation,which enhance the predicted life when employing these methods.In conclusion,the Entropy Weight-Grey Theory-BP Network life prediction Model is well-suited for tunnel lining in the alpine sulfate area of northwest China.展开更多
智慧园区新兴业务的信息采集及实时控制需要严格的时间同步作为前提,虚假数据注入攻击(false data injection attack,FDIA)对时间同步精度的影响不可忽视。如何通过电力线通信(power line communication,PLC)实现安全准确时间同步成为...智慧园区新兴业务的信息采集及实时控制需要严格的时间同步作为前提,虚假数据注入攻击(false data injection attack,FDIA)对时间同步精度的影响不可忽视。如何通过电力线通信(power line communication,PLC)实现安全准确时间同步成为当前研究的重要问题。该文首先构建考虑FDIA的PLC赋能智慧园区时间同步网络,通过改进卡尔曼滤波修正时间同步误差;其次,以误差最小化为目标,建立站点时间同步问题;最后,提出基于改进深度Q网络的时间同步路由选择算法。所提算法能够根据FDIA概率动态学习时间同步路由选择策略,从而提高对未知状态的泛化能力。仿真验证表明,所提方法不仅能够显著提升FDIA检测的安全性能,同时可有效改善时间同步精度。展开更多
基金Supported by the Natural Science Foundation of Jiangsu Province (Key Program) (BK2011023)
文摘In 2010,Lee et al proposed two simple and efficient three-party password-authenticated key exchange protocols that had been proven secure in the random oracle model.They argued that the two protocols could resist offline dictionary attacks.Indeed,the provable approach did not provide protection against off-line dictionary attacks.This paper shows that the two protocols are vulnerable to off-line dictionary attacks in the presence of an inside attacker because of an authentication flaw.This study conducts a detailed analysis on the flaw in the protocols and also shows how to eliminate the security flaw.
基金supported by the Science and Technology Project of the State Grid Corporation of China under Grant Number 5400202199541A-0-5-ZN。
文摘Power Line Communications-Artificial Intelligence of Things(PLC-AIo T)combines the low cost and high coverage of PLC with the learning ability of Artificial Intelligence(AI)to provide data collection and transmission capabilities for PLC-AIo T devices in smart parks.With the development of smart parks,their emerging services require secure and accurate time synchronization of PLC-AIo T devices.However,the impact of attackers on the accuracy of time synchronization cannot be ignored.To solve the aforementioned problems,we propose a tampering attack-aware Deep Q-Network(DQN)-based time synchronization algorithm.First,we construct an abnormal clock source detection model.Then,the abnormal clock source is detected and excluded by comparing the time synchronization information between the device and the gateway.Finally,the proposed algorithm realizes the joint guarantee of high accuracy and low delay for PLC-AIo T in smart parks by intelligently selecting the multi-clock source cooperation strategy and timing weights.Simulation results show that the proposed algorithm has better time synchronization delay and accuracy performance.
文摘The number and creativity of side channel attacks have increased dramatically in recent years. Of particular interest are attacks leveraging power line communication to 1) gather information on power consumption from the victim and 2) exfiltrate data from compromised machines. Attack strategies of this nature on the greater power grid and building infrastructure levels have been shown to be a serious threat. This project further explores this concept of a novel attack vector by creating a new type of penetration testing tool: an USB power adapter capable of remote monitoring of device power consumption and communicating through powerline communications.
基金funded by the Technology Funding Scheme of China Construction Second Engineering Bureau LTD(2020ZX150002)the National Natural Science Foundation Project of China(12262018).
文摘To address the challenges posed by tunnel construction in the alpine region,silica fume mixed concrete is commonly used as a construction material.The correlation between silica fume content and the lining life requires immediate investigation.In view of this phenomenon,the durability of unit lining concrete is predicted by analyzing three key indicators:carbonation depth,relative dynamic elastic modulus,and residual quality.This prediction is achieved by integrating the Entropy Weight Method,Grey theory life prediction model and BP artificial neural networks using data from tests and predictions of these indicators.Then,the Entropy Weight-Grey theory-BP Network Model is compared with other methods to analyze the predicted life.Finally,verify the sci-entificity of this model,and the optimum silica fume content of unit concrete lining is verified.The results showed,1)The addition of silica fume will accelerate the carbonization of unit concrete lining,and slow down the freeze-thaw cycle and sulfate erosion.2)The utilization of artificial neural networks is essential for enhancing the realism of the data,as it emphasizes the significance of silica fume content.3)Silica fume content of 10%results in the longest life and is the most suitable for lining construction.4)A comparison between single-factor and multi-factor predictions indicates that the multi-factor approach yields a longer maximum life.This improvement can be attributed to the inclusion of additional factors,such as freeze-thaw cycles and carbonation,which enhance the predicted life when employing these methods.In conclusion,the Entropy Weight-Grey Theory-BP Network life prediction Model is well-suited for tunnel lining in the alpine sulfate area of northwest China.
文摘智慧园区新兴业务的信息采集及实时控制需要严格的时间同步作为前提,虚假数据注入攻击(false data injection attack,FDIA)对时间同步精度的影响不可忽视。如何通过电力线通信(power line communication,PLC)实现安全准确时间同步成为当前研究的重要问题。该文首先构建考虑FDIA的PLC赋能智慧园区时间同步网络,通过改进卡尔曼滤波修正时间同步误差;其次,以误差最小化为目标,建立站点时间同步问题;最后,提出基于改进深度Q网络的时间同步路由选择算法。所提算法能够根据FDIA概率动态学习时间同步路由选择策略,从而提高对未知状态的泛化能力。仿真验证表明,所提方法不仅能够显著提升FDIA检测的安全性能,同时可有效改善时间同步精度。
