Second bloom of fruit trees refers to the flowering and fruit-bearing of fruit trees after autumn harvest, which seriously influences the yield and economic benefits of fruit trees. By analyzing the causes of second b...Second bloom of fruit trees refers to the flowering and fruit-bearing of fruit trees after autumn harvest, which seriously influences the yield and economic benefits of fruit trees. By analyzing the causes of second bloom, remedies are given to make scientific preventive measures and realize high-quality and high-yield cultivation of fruit trees.展开更多
可变长地址是未来网络领域的重要研究内容之一。针对传统路由查找算法在面向可变长地址时查找效率低的问题,提出一种基于平衡二叉树AVL(Adelson-Velskii and Landis)树和Bloom过滤器的适用于可变长地址的高效路由查找算法,简称为AVL-Bl...可变长地址是未来网络领域的重要研究内容之一。针对传统路由查找算法在面向可变长地址时查找效率低的问题,提出一种基于平衡二叉树AVL(Adelson-Velskii and Landis)树和Bloom过滤器的适用于可变长地址的高效路由查找算法,简称为AVL-Bloom算法。首先,针对可变长地址灵活可变且无界的特点,利用多个片外哈希表分别存储前缀比特位数相同的路由条目及其下一跳信息,同时应用片上Bloom过滤器加速搜索可能匹配的路由前缀;其次,为了解决基于哈希技术的路由查找算法在查找最长前缀路由时需多次哈希对比的问题,引入AVL树技术,即通过AVL树组织每组路由前缀集合的Bloom过滤器及其哈希表,优化路由前缀长度的查询顺序,并减少哈希计算次数进而降低查询时间;最后,在3种不同的可变长地址数据集上将所提算法与METrie(Multi-Entrance-Trie)和COBF(Controlled prefix and One-hashing Bloom Filter)这两种传统路由查找算法进行对比实验。实验结果表明,AVL-Bloom算法的查询时间明显少于METrie和COBF算法,分别减少了将近83%和64%;同时,AVL-Bloom算法在路由表项数变化较大的情况下也能维持稳定的查找性能,适用于可变长地址的路由查找转发。展开更多
随着基于区块链的农产品溯源系统迅速发展,区块链查询能力面临着巨大挑战。对于供应链参与方来说,区块链中保存的数据多为编码或序列化的数据,使得供应链参与方的审计和监督等存在多条件查询的工作变得十分困难。通常情况下,原生区块链...随着基于区块链的农产品溯源系统迅速发展,区块链查询能力面临着巨大挑战。对于供应链参与方来说,区块链中保存的数据多为编码或序列化的数据,使得供应链参与方的审计和监督等存在多条件查询的工作变得十分困难。通常情况下,原生区块链并未提供满足多条件查询的查询方式。因此,为了实现多条件查询并提高查询效率,本研究提出一种农产品溯源数据多条件查询优化方法。首先,该方法采用一种优化的Merkle树结构(n-Tree)对交易信息进行重构,从而提供更高效的条件验证能力。其次,通过自适应多条件区块布隆过滤器判断交易信息中查询条件的存在性,进而快速过滤区块。最后,提出一种应用TWTN-Heap(Time weight and transaction number based heap)结构的索引构建方法,以区块权重为序构建主条件相关的区块号索引列表。产品数据的查询过程包括遍历区块号索引列表、过滤非相关区块以及验证特定查询条件,从而获得条件查询结果。实验结果表明,本研究提出的产品数据条件查询优化方法能够有效地解决农产品供应链面临的条件查询问题,同时保证查询时间消耗维持在15 ms左右,查询效率较默克尔语义字典树(Merkle semantic trie, MST)方法提高60.9%,较原始遍历(Orignal traverse, OT)方法提高87.7%。展开更多
Outsourcing decision tree models to cloud servers can allow model providers to distribute their models at scale without purchasing dedicated hardware for model hosting.However,model providers may be forced to disclose...Outsourcing decision tree models to cloud servers can allow model providers to distribute their models at scale without purchasing dedicated hardware for model hosting.However,model providers may be forced to disclose private model details when hosting their models in the cloud.Due to the time and monetary investments associated with model training,model providers may be reluctant to host their models in the cloud due to these privacy concerns.Furthermore,clients may be reluctant to use these outsourced models because their private queries or their results may be disclosed to the cloud servers.In this paper,we propose BloomDT,a privacy-preserving scheme for decision tree inference,which uses Bloom filters to hide the original decision tree's structure,the threshold values of each node,and the order in which features are tested while maintaining reliable classification results that are secure even if the cloud servers collude.Our scheme's security and performance are verified through rigorous testing and analysis.展开更多
文摘Second bloom of fruit trees refers to the flowering and fruit-bearing of fruit trees after autumn harvest, which seriously influences the yield and economic benefits of fruit trees. By analyzing the causes of second bloom, remedies are given to make scientific preventive measures and realize high-quality and high-yield cultivation of fruit trees.
文摘可变长地址是未来网络领域的重要研究内容之一。针对传统路由查找算法在面向可变长地址时查找效率低的问题,提出一种基于平衡二叉树AVL(Adelson-Velskii and Landis)树和Bloom过滤器的适用于可变长地址的高效路由查找算法,简称为AVL-Bloom算法。首先,针对可变长地址灵活可变且无界的特点,利用多个片外哈希表分别存储前缀比特位数相同的路由条目及其下一跳信息,同时应用片上Bloom过滤器加速搜索可能匹配的路由前缀;其次,为了解决基于哈希技术的路由查找算法在查找最长前缀路由时需多次哈希对比的问题,引入AVL树技术,即通过AVL树组织每组路由前缀集合的Bloom过滤器及其哈希表,优化路由前缀长度的查询顺序,并减少哈希计算次数进而降低查询时间;最后,在3种不同的可变长地址数据集上将所提算法与METrie(Multi-Entrance-Trie)和COBF(Controlled prefix and One-hashing Bloom Filter)这两种传统路由查找算法进行对比实验。实验结果表明,AVL-Bloom算法的查询时间明显少于METrie和COBF算法,分别减少了将近83%和64%;同时,AVL-Bloom算法在路由表项数变化较大的情况下也能维持稳定的查找性能,适用于可变长地址的路由查找转发。
文摘随着基于区块链的农产品溯源系统迅速发展,区块链查询能力面临着巨大挑战。对于供应链参与方来说,区块链中保存的数据多为编码或序列化的数据,使得供应链参与方的审计和监督等存在多条件查询的工作变得十分困难。通常情况下,原生区块链并未提供满足多条件查询的查询方式。因此,为了实现多条件查询并提高查询效率,本研究提出一种农产品溯源数据多条件查询优化方法。首先,该方法采用一种优化的Merkle树结构(n-Tree)对交易信息进行重构,从而提供更高效的条件验证能力。其次,通过自适应多条件区块布隆过滤器判断交易信息中查询条件的存在性,进而快速过滤区块。最后,提出一种应用TWTN-Heap(Time weight and transaction number based heap)结构的索引构建方法,以区块权重为序构建主条件相关的区块号索引列表。产品数据的查询过程包括遍历区块号索引列表、过滤非相关区块以及验证特定查询条件,从而获得条件查询结果。实验结果表明,本研究提出的产品数据条件查询优化方法能够有效地解决农产品供应链面临的条件查询问题,同时保证查询时间消耗维持在15 ms左右,查询效率较默克尔语义字典树(Merkle semantic trie, MST)方法提高60.9%,较原始遍历(Orignal traverse, OT)方法提高87.7%。
基金supported by collaborative research funding from the National Research Council of Canada's Aging in Place Challenge Program.
文摘Outsourcing decision tree models to cloud servers can allow model providers to distribute their models at scale without purchasing dedicated hardware for model hosting.However,model providers may be forced to disclose private model details when hosting their models in the cloud.Due to the time and monetary investments associated with model training,model providers may be reluctant to host their models in the cloud due to these privacy concerns.Furthermore,clients may be reluctant to use these outsourced models because their private queries or their results may be disclosed to the cloud servers.In this paper,we propose BloomDT,a privacy-preserving scheme for decision tree inference,which uses Bloom filters to hide the original decision tree's structure,the threshold values of each node,and the order in which features are tested while maintaining reliable classification results that are secure even if the cloud servers collude.Our scheme's security and performance are verified through rigorous testing and analysis.
