基于旅行推销员非确定性多项式困难问题的集中式僵尸网络检测，TSP-NP技术
Detecting Centralized Architecture-Based Botnets using Travelling Salesperson Non-Deterministic Polynomial-Hard problem, TSP-NP Technique
摘要：
僵尸网络在网络空间中构成的威胁每天都在继续增长，并且很难检测或渗透机器人的愤世嫉俗。这是由于这样一个事实，即僵尸网络开发人员每天都在不断改变传播和攻击技术。目前，这些攻击大多集中在窃取计算能量，窃取个人信息和分布式拒绝服务（DDoS）攻击。在本文中，作者提出了一种新的技术，使用非确定性多项式时间硬度（NP难问题）的基础上的旅行推销员的人（TSP），描绘了一个给定的机器人，bj，能够访问网络环境中的每个主机，NE，然后它返回到僵尸主机，在指令（命令）的形式，通过最佳最小化的主机（可能）被攻击。鉴于bj代表一段恶意代码和TSP-NP困难问题，这是组合优化的一部分，作者提出了这是一个有效的方法检测僵尸网络。值得注意的是，本研究的重点基本上是集中式僵尸网络架构。这种整体方法表明，僵尸网络检测的准确性可以在一定程度上提高，并可能降低误报的机会。然而，本文也讨论了可能的适用性和实施。
英文摘要：
The threats posed by botnets in the cyberspace continue to grow each day and it has become very hard to detect or infiltrate the cynicism of bots. This, is owing to the fact, that, the botnet developers each day, keep changing the propagation and attack techniques. Currently, most of these attacks have been centered on stealing computing energy, theft of personal information and Distributed Denial of Service (DDoS) attacks. In this paper, the authors propose a novel technique that uses the Non-Deterministic Polynomial-Time Hardness (NP-Hard Problem) based on the Traveling Salesperson Person (TSP) that depicts that a given bot, bj, is able to visit each host on a network environment, NE, and then it returns to the botmaster, in form of instruction(command), through optimal minimization of the hosts that are (may) be attacked. Given that bj represents a piece of malicious code and TSP-NP Hard Problem, which forms part of combinatorial optimization, the authors present this as an effective approach for the detection of the botnet. It is worth noting that the concentration of this study is basically on the centralized botnet architecture. This holistic approach shows that botnet detection accuracy can be increased with a degree of certainty and potentially decrease the chances of false positives. Nevertheless, a discussion on the possible applicability and implementation has also been given in this paper.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
