论文标题
量子算法以找到未知的标签
A Quantum Algorithm To Locate Unknown Hashgrams
论文作者
论文摘要
近年来，量子计算已经迅速发展，并且在各个领域，尤其是在网络安全领域中显示出显着的好处。用于定位识别恶意软件的最频繁哈希和$ n $克的软件的组合可以从量子算法中受益匪浅。通过将哈希表和$ n $ grams加载到量子计算机中，我们可以加快将$ n $ grams映射到其哈希的过程。第一阶段是使用千克查找大型恶意软件语料库的顶部$ K $ hashes和$ n $ grams。从这里开始，将所得的哈希表加载到量子模拟器中。然后在纠缠键和值对的每个排列中使用量子搜索算法以找到所需的哈希值。这样可以防止一个人必须重新计算一组$ n $ grams的哈希斯，这可能需要$ o O（mn）$时间，而量子算法可以在桌面查找中占用$ o（\ sqrt {n}）$，以找到所需的hash值。
Quantum computing has evolved quickly in recent years and is showing significant benefits in a variety of fields, especially in the realm of cybersecurity. The combination of software used to locate the most frequent hashes and $n$-grams that identify malicious software could greatly benefit from a quantum algorithm. By loading the table of hashes and $n$-grams into a quantum computer we can speed up the process of mapping $n$-grams to their hashes. The first phase will be to use KiloGram to find the top-$k$ hashes and $n$-grams for a large malware corpus. From here, the resulting hash table is then loaded into a quantum simulator. A quantum search algorithm is then used search among every permutation of the entangled key and value pairs to find the desired hash value. This prevents one from having to re-compute hashes for a set of $n$-grams, which can take on average $O(MN)$ time, whereas the quantum algorithm could take $O(\sqrt{N})$ in the number of table lookups to find the desired hash values.
