以可控飞行撞地(CFIT,controlled flight into terrain)事件类型信息为研究对象,依照基元事件分析法分析CFIT事件演化过程,建立了事件后果层—飞机状态层—诱发因素层三层贝叶斯网络结构模型。以2017—2019年中国民航收集的CFIT事件和...以可控飞行撞地(CFIT,controlled flight into terrain)事件类型信息为研究对象,依照基元事件分析法分析CFIT事件演化过程,建立了事件后果层—飞机状态层—诱发因素层三层贝叶斯网络结构模型。以2017—2019年中国民航收集的CFIT事件和航空安全网(ASN,Aviation Safety Network)近20年(2000—2019年)CFIT事件数据为样本,利用样本统计数据确立网络节点参数,采用GeNIe软件选取贝叶斯网络已知节点与目标节点进行量化分析,得到目标节点可能性排序、最大可能性目标节点及影响强度;最终得出该类事件的关键风险环节,即飞行高度控制、机组丧失情景意识、飞行保障及相应节点的量化结果,为加强此类事件风险控制提供数据支持。展开更多
In this paper, we propose a theoretical-information Confidential Procedure Model (CPM) to quantify confidentiality (or information leakage). The advantages of the CPM model include the following: 1) confidentiality lo...In this paper, we propose a theoretical-information Confidential Procedure Model (CPM) to quantify confidentiality (or information leakage). The advantages of the CPM model include the following: 1) confidentiality loss is formalized as a dynamic procedure, instead of a static function, and described via the "waterfall" diagram; 2) confidentiality loss is quantified in a relative manner, i.e., taken as a quantitative metric, the ratio of the conditional entropy being reserved after observing the entropy of the original full confidential information; 3) the optimal attacks including exhaustive attacks as well as all possible attacks that have (or have not even) been discovered, are taken into account when defining the novel concept of the confidential degree. To elucidate the proposed model, we analyze the information leakage in side-channel attacks and the anonymity of DC-net in a quantitative manner.展开更多
This paper aims to find a practical way of quantitatively representing the privacy of network data. A method of quantifying the privacy of network data anonymization based on similarity distance and entropy in the sce...This paper aims to find a practical way of quantitatively representing the privacy of network data. A method of quantifying the privacy of network data anonymization based on similarity distance and entropy in the scenario involving multiparty network data sharing with Trusted Third Party (TTP) is proposed. Simulations are then conducted using network data from different sources, and show that the measurement indicators defined in this paper can adequately quantify the privacy of the network. In particular, it can indicate the effect of the auxiliary information of the adversary on privacy.展开更多
基金supported by the National Natural Science Foundation of China under Grants No.61172085,No.61272536,No.11061130539,No.61103221,No.61271118,No.61021004
文摘In this paper, we propose a theoretical-information Confidential Procedure Model (CPM) to quantify confidentiality (or information leakage). The advantages of the CPM model include the following: 1) confidentiality loss is formalized as a dynamic procedure, instead of a static function, and described via the "waterfall" diagram; 2) confidentiality loss is quantified in a relative manner, i.e., taken as a quantitative metric, the ratio of the conditional entropy being reserved after observing the entropy of the original full confidential information; 3) the optimal attacks including exhaustive attacks as well as all possible attacks that have (or have not even) been discovered, are taken into account when defining the novel concept of the confidential degree. To elucidate the proposed model, we analyze the information leakage in side-channel attacks and the anonymity of DC-net in a quantitative manner.
基金supported by the National Key Basic Research Program of China (973 Program) under Grant No. 2009CB320505the Fundamental Research Funds for the Central Universities under Grant No. 2011RC0508+2 种基金the National Natural Science Foundation of China under Grant No. 61003282China Next Generation Internet Project "Research and Trial on Evolving Next Generation Network Intelligence Capability Enhancement"the National Science and Technology Major Project "Research about Architecture of Mobile Internet" under Grant No. 2011ZX03002-001-01
文摘This paper aims to find a practical way of quantitatively representing the privacy of network data. A method of quantifying the privacy of network data anonymization based on similarity distance and entropy in the scenario involving multiparty network data sharing with Trusted Third Party (TTP) is proposed. Simulations are then conducted using network data from different sources, and show that the measurement indicators defined in this paper can adequately quantify the privacy of the network. In particular, it can indicate the effect of the auxiliary information of the adversary on privacy.
