Many kinds of channel currents are especially weak and the background noise dominates in the patch clamp recordings. This makes the threshold detection fail during estimating of the transition probabilities. So direct...Many kinds of channel currents are especially weak and the background noise dominates in the patch clamp recordings. This makes the threshold detection fail during estimating of the transition probabilities. So direct fitting of the patch clamp recording, not of the histogram coming from the recordings, is a desirable way to estimate the transition probabilities. Iterative batch EM algorithm based on hidden markov model has been used in this field but which has the "curse of dimensionality" and besides cant keep tracking the varying of the parameters. A new on line sequential iterative one is proposed here, which needs fewer computational efforts and can adaptively keep tracking the varying of parameters. Simulations suggest its robust, effective and convenient.展开更多
An adaptive statistic model for mobile communication channel is studied and simulated in this paper. According to the model parameters, an error sequence describing the long burst error characteristics of the mobile c...An adaptive statistic model for mobile communication channel is studied and simulated in this paper. According to the model parameters, an error sequence describing the long burst error characteristics of the mobile communication channel is generated on a computer. A test method using threshold technique is presented to verify the accuracy of the adaptive channel model.展开更多
计算机网络缓存侧信道能够间接体现计算机内部状态以及数据传输情况,其受攻击时,用户端信息数据存在泄露风险,因此提出一种基于马尔科夫的计算机网络缓存侧信道攻击检测方法。构建隐马尔科夫模型,对计算机网络缓存侧信道状态改变的概率...计算机网络缓存侧信道能够间接体现计算机内部状态以及数据传输情况,其受攻击时,用户端信息数据存在泄露风险,因此提出一种基于马尔科夫的计算机网络缓存侧信道攻击检测方法。构建隐马尔科夫模型,对计算机网络缓存侧信道状态改变的概率进行计算。通过Baum‐Welch算法估计隐马尔科夫模型最优参数,并计算缓存侧信道状态观测序列输出概率。比较缓存侧信道观测序列输出概率与设定的阈值,判断该序列为计算机网络缓存侧信道攻击信号的可能性,并引入平均信息熵判断计算机缓存侧信道状态是否存在异常,完成计算机网络缓存侧信道攻击检测。通过实验验证得出,该方法用于计算机网络缓存侧信道攻击检测的准确率高,误报率低,在遭受DDoS攻击(Distributed denial of service)时的检测时间较短,对计算机网络缓存侧信道攻击的防御与保护产生了积极影响。展开更多
Protocol tunneling is widely used to add security and/or privacy to Internet applications. Recent research has exposed side channel vulnerabilities that leak information about tunneled protocols. We first discuss the ...Protocol tunneling is widely used to add security and/or privacy to Internet applications. Recent research has exposed side channel vulnerabilities that leak information about tunneled protocols. We first discuss the timing side channels that have been found in protocol tunneling tools. We then show how to infer Hidden Markov models (HMMs) of network protocols from timing data and use the HMMs to detect when protocols are active. Unlike previous work, the HMM approach we present requires no a priori knowledge of the protocol. To illustrate the utility of this approach, we detect the use of English or Italian in interactive SSH sessions. For this example application, keystroke-timing data associates inter-packet delays with keystrokes. We first use clustering to extract discrete information from continuous timing data. We use discrete symbols to infer a HMM model, and finally use statistical tests to determine if the observed timing is consistent with the language typing statistics. In our tests, if the correct window size is used, fewer than 2% of data windows are incorrectly identified. Experimental verification shows that on-line detection of language use in interactive encrypted protocol tunnels is reliable. We compare maximum likelihood and statistical hypothesis testing for detecting protocol tunneling. We also discuss how this approach is useful in monitoring mix networks like The Onion Router (Tor).展开更多
文摘Many kinds of channel currents are especially weak and the background noise dominates in the patch clamp recordings. This makes the threshold detection fail during estimating of the transition probabilities. So direct fitting of the patch clamp recording, not of the histogram coming from the recordings, is a desirable way to estimate the transition probabilities. Iterative batch EM algorithm based on hidden markov model has been used in this field but which has the "curse of dimensionality" and besides cant keep tracking the varying of the parameters. A new on line sequential iterative one is proposed here, which needs fewer computational efforts and can adaptively keep tracking the varying of parameters. Simulations suggest its robust, effective and convenient.
基金National Natural Science Foundation of China(No.69372004)
文摘An adaptive statistic model for mobile communication channel is studied and simulated in this paper. According to the model parameters, an error sequence describing the long burst error characteristics of the mobile communication channel is generated on a computer. A test method using threshold technique is presented to verify the accuracy of the adaptive channel model.
文摘计算机网络缓存侧信道能够间接体现计算机内部状态以及数据传输情况,其受攻击时,用户端信息数据存在泄露风险,因此提出一种基于马尔科夫的计算机网络缓存侧信道攻击检测方法。构建隐马尔科夫模型,对计算机网络缓存侧信道状态改变的概率进行计算。通过Baum‐Welch算法估计隐马尔科夫模型最优参数,并计算缓存侧信道状态观测序列输出概率。比较缓存侧信道观测序列输出概率与设定的阈值,判断该序列为计算机网络缓存侧信道攻击信号的可能性,并引入平均信息熵判断计算机缓存侧信道状态是否存在异常,完成计算机网络缓存侧信道攻击检测。通过实验验证得出,该方法用于计算机网络缓存侧信道攻击检测的准确率高,误报率低,在遭受DDoS攻击(Distributed denial of service)时的检测时间较短,对计算机网络缓存侧信道攻击的防御与保护产生了积极影响。
文摘Protocol tunneling is widely used to add security and/or privacy to Internet applications. Recent research has exposed side channel vulnerabilities that leak information about tunneled protocols. We first discuss the timing side channels that have been found in protocol tunneling tools. We then show how to infer Hidden Markov models (HMMs) of network protocols from timing data and use the HMMs to detect when protocols are active. Unlike previous work, the HMM approach we present requires no a priori knowledge of the protocol. To illustrate the utility of this approach, we detect the use of English or Italian in interactive SSH sessions. For this example application, keystroke-timing data associates inter-packet delays with keystrokes. We first use clustering to extract discrete information from continuous timing data. We use discrete symbols to infer a HMM model, and finally use statistical tests to determine if the observed timing is consistent with the language typing statistics. In our tests, if the correct window size is used, fewer than 2% of data windows are incorrectly identified. Experimental verification shows that on-line detection of language use in interactive encrypted protocol tunnels is reliable. We compare maximum likelihood and statistical hypothesis testing for detecting protocol tunneling. We also discuss how this approach is useful in monitoring mix networks like The Onion Router (Tor).
