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.
翻译:量子计算近年来迅速演变,在各个领域,特别是在网络安全领域,显示出巨大的效益。用于定位最常使用的大麻和用于识别恶意软件的零美克软件的组合,可以极大地受益于量子算法。通过将大麻和零美克的表格装入量子计算机,我们可以加快绘制以美元计数的量子计算机的进程。第一阶段将是使用KiloGram来寻找一个大型恶意软件的顶值-美元(hash)和美元(ng)克。从这里开始,由此产生的散货表将装入量子模拟器。然后,在每对缠绕键和价值的组合中搜索量子算法,以找到理想的值。这样,人们就不必重新计算一套以美元计数的美元,这可以平均花费O(MN)美元的时间,而量子算法则可以花费$(sqrt{N}在表格中找到理想值。