计算机病毒的传播模型及防范策略探析

随着我国科学技术的发展和网络技术的进步,计算机作为一门重要的生活和工作的工具广泛的应用到人们的生活中。计算机在为人们带了诸多便利的同时也容易受到许多病毒的侵害,从而给人们的工作和生活带了严重的影响。本文将对计算机病毒的危害、计算机病毒的传播模型进行分析,然后探究计算机病毒的防范措施,从而为计算机用户安全的使用计算机提供科学的依据。     

计算机病毒网络传播模型稳定性与控制

本文首先分析了计算机病毒网络传播模型的稳定性,例如SIS模型、SIR模型、SEIR模型等,随后文章有提出了促进计算机网络病毒传播有效控制的具体措施,包括电子邮件控制法、局域网中的病毒控制措施、互联网中的病毒控制方法等,希望能给相关人士提供一些参考.     

一类改进的计算机病毒传播模型

通过分析以前模型的不足,结合现实情况,参考生物数学中的传染病模型,提出了一种有反病毒措施的计算机病毒传播时滞模型.通过同以往模型的数值解比较,发现本模型更能反映实际网络中病毒的传播情况,通过本模型能更好地理解和预测现实计算机网络中病毒传播的规模与速度.     

计算机病毒传播模型的分析

在计算机病毒实例分析的基础上,对计算机病毒的实现原理进行了形式化的抽象,同时对计算机反病毒技术作了相关解释,并说明了计算机反病毒技术的发展方向。     

一类具有个体差异性和非近邻传播特性的SIRS计算机病毒传播模型

已有的SIRS模型认为感染个体被治愈后具有免疫能力,没有考虑个体之间的差异性以及实际节点之间的拓扑关系划分的不确定性。针对上述的不足,结合实际网络传播情况,分别引入直接免疫概率α、被治愈但不具有免疫力的概率μ2以及非相邻节点感染概率β1。提出一类具有个体差异性和非近邻传播特性的SIRS模型,该模型充分考虑了网络中节点在病毒免疫过程中存在的差异性以及非近邻传播特性对病毒传播的影响。数值模拟得到的结果和理论分析表明,通过增加网络中的直接免疫强度以及抑制非近邻传播的发生能够有效控制病毒的传播。     

计算机病毒网络传播模型稳定性与控制研究

随着计算机的不断普及,网络病毒也越来越成为危害网络信息安全的一大隐患。介绍了计算机病毒中的4种经典病毒模型,从局域网、广域网、电子邮件3个方面来分析控制计算机网络病毒传播的措施和方法。     

基于社交网络的农业科技信息传播博弈模型探析

实施乡村振兴战略和推进农业农村现代化,离不开农业科技成果的推广应用。“互联网+”时代,社交网络为传播手段对农业科技信息推广十分有利。博弈论为农业科技信息竞争提供理论依据,协助农业科技信息传播主体在“市场争夺战”博弈中做出决策。因此,在社交网络环境下,分析社交网络、博弈论与农业科技信息服务的关系,基于社交网络构建农业科技信息竞争策略博弈模型、分析农业科技信息博弈均衡、收益函数等,揭示影响农业科技信息的因素和农业科技信息传播各主体间的利益关系,协助传播主体、传播受体做出最佳决策,实现社交网络下的农业科技信息传播水平的提升。     

改进的SIR计算机病毒传播模型

通过分析已有网络病毒模型的不足,结合现实情况,根据生物学中的传染病模型提出了一种改进的具有预先免疫措施的SIR计算机病毒传播模型,该模型充分考虑了网络中节点数量变化对病毒传播的影响。此外,利用微分方程理论分析了模型的动力学行为。数值模拟结果表明,提高预先免疫率和控制节点流动可以有效控制病毒在网络中的传播。     

Game Theory and Decision Theory in Multi-Agent Systems

In the last few years, there has been increasing interest from the agent community in the use of techniques from decision theory and game theory. Our aims in this article are firstly to briefly summarize the key concepts of decision theory and game theory, secondly to discuss how these tools are being applied in agent systems research, and finally to introduce this special issue of Autonomous Agents and Multi-Agent Systems by reviewing the papers that appear.     

测控装备面向协同智能诊断系统应用研究

随着测控装备集成度的提高,单一的诊断模式已很难准确定位装备出现的故障,需要多个领域知识共同对诊断对象进行决策融合.本文根据某型测控装备实际,设计了以故障树诊断为基础的专家系统,结合博弈论相关理论对多个知识库进行诊断结果的融合.最终将诊断结果纳入装备的日常维护保养,提高了装备的综合保障能力.     

A novel computer virus propagation model and its dynamics

By taking into account the fact that, in general, a computer immediately possesses infectivity as soon as it is infected, a novel computer virus propagation model, known as the SLBS model, is established. It is proved that the dynamic behaviour of the model is determined by a threshold R ₀. Specifically, the virus-free equilibrium is globally asymptotically stable if R ₀≤1, whereas the virulent equilibrium is globally asymptotically stable if 1<R ₀≤4. It is conjectured that the virulent equilibrium is also globally asymptotically stable if R ₀>4. These results suggest some effective strategies for eradicating computer viruses distributed in the Internet.     

Using Hypergames to Increase Planned Payoff and Reduce Risk

Hypergames are an emerging tool for combining decision theoretic and game theoretic information. We explain a new approach to the standard two-player zero-sum single-stage normal game that maximizes expected gain while quantifying possible loss. A DTGT agent can use this formulation to select a plan based on its assessment of an opponent's intent, its assessment of an opponent's unpredictability and its utility model of the situation.     

《计算机病毒》教学游戏的设计

针对中小学信息技术课程当中计算机病毒知识抽象导致教学困难的问题,设计了一款游戏,让学生在直观形象的场景中学习和体验计算机病毒的特征和危害,达到寓教于乐的目的.     

Satisficing Equilibria: A Non-Classical Theory of Games and Decisions

Satisficing, or being good enough, is the fundamental obligation of rational decision makers. We cannot rationally choose an option, even when we do not know of anything better, unless we know it is good enough. Unfortunately, we are not often in the position of knowing that there could be no better option, and hence that the option must be good enough. A complete search through all logical possibilities is often impractical, particularly in multi-agent contexts, due to excessive computational difficulty, modeling complexity, and uncertainty. It can be equally impractical, if it is even possible, to determine the cost of the additional required search to find an option that is good enough. In a departure from the traditional notion of satisficing as a species of bounded rationality, satisficing is here redefined in terms of a notion of intrinsic rationality. Epistemic utility theory serves as the philosophical foundation of a new praxeological decision-making paradigm of satisficing equilibria that is applicable to both single- and multiple-agent scenarios. All interagent relationships are modeled by an interdependence function that explicitly accommodates both self and group interest, from which multilateral and unilateral selectability and rejectability mass functions can be derived and compared via the praxeic likelihood ratio test.     

Arguments against the possibility of perfect rationality

Many different arguments against the possibility of perfect rationality have appeared in the literature, and these target several different conceptions of perfect rationality. It is not clear how these different conceptions of perfect rationality are related, nor is it clear how the arguments showing their impossibility are related, and it is especially unclear what the impossibility results show when taken together. This paper gives an exposition of the different conceptions of perfect rationality, an the various sorts of argument against them; clarifies which conceptions of perfect rationality are targeted by which arguments; and finally attempts to systematize the results available to date.     

知识驱动的游戏攻略自动标注算法

为了帮助用户快速检索感兴趣的游戏攻略,提出了知识驱动的游戏攻略自动标注算法。首先,对每款游戏的多个资讯网站进行融合,自动构建游戏领域知识库;然后,再通过游戏领域词汇发现算法和决策树分类模型,抽取游戏攻略中的游戏术语;由于游戏术语在攻略中大多以简称的形式存在,故最后将攻略中游戏术语和知识库进行链接得到该术语所对应的全称即语义标签对攻略进行标注。在多款游戏上的实验结果表明,所提出的游戏攻略标注方法的准确率高达90%。同时,游戏领域词汇发现算法与其他术语抽取方法n-gram语言模型相比取得了更好的效果。     

机器博弈研究面临的各种挑战

让计算机学会下棋打牌,尤其和人类的精英对决,这是机器博弈领域长期的奋斗目标,也是人工智能学科极富挑战性的研究课题.为能在这一新兴的研究领域取得更快更多突破性进展,有力发挥机器博弈的"果蝇"作用,有必要很好地明确机器博弈研究当前面临哪些挑战性问题.从学术观念、实战博弈、理论发展、军事应用、国际接轨、普及提高及学生创新性培养等多角度阐述当前在机器博弈领域急需解决的主要问题,以期有更多的青年学者能够投身到这一极富挑战性的研究领域.     

计算机网络病毒传播模型SIRH

计算机网络病毒传播模型是研究计算机网络病毒的手段和工具。SIR模型是仿照生物流行病传播机制而建立的病毒传播模型。本文从计算机网络病毒传播的实际情况出发,通过分析SIR模型的不足,提出了一种在计算机网络中具有病毒防范、病毒免疫措施的网络病毒传播模型。SIRH考虑了网络病毒重复感染这种人为因素对网络病毒传播的影响。仿真实验验证了SIRH的有效合理性。