面向智能汽车的信息安全漏洞评分模型

随着汽车智能化、网联化的发展,汽车中集成了越来越多的电子器件,数量庞大的硬件、固件和软件中隐藏着各种设计缺陷和漏洞,这从根本上导致了智能汽车信息安全问题。大量汽车漏洞的披露,严重影响了汽车安全,制约了智能汽车的广泛应用。漏洞管理是降低漏洞危害、改善汽车安全的有效手段。在漏洞管理流程中,漏洞评估是决定漏洞处置优先级的重要一环。但是,现有的漏洞评分系统不能合理地评估智能汽车安全漏洞。为了解决智能汽车漏洞评估不合理的问题,提出面向智能汽车的信息安全漏洞评分模型。基于通用漏洞评分系统（CVSS）漏洞评分原理,根据智能汽车的特点,优化了CVSS的攻击向量和攻击复杂度,并添加了财产安全、隐私安全、功能安全和生命安全4个指标来刻画漏洞可能对智能汽车造成的影响;结合机器学习的方法,对CVSS评分公式参数进行了调整,以使其更好地刻画智能汽车信息安全漏洞特点,适应调整后的指标权重。通过实例评估和统计系统特征分布发现,模型拥有更好的多样性和更稳定连续的特征分布,表明模型可以更好地对不同漏洞进行评分;并且基于模型评估得到的漏洞评分,应用层次分析法给出整车脆弱性评估,表征整车风险水平。所提模型相比现有模型可以更...     

基于依赖关系图和通用漏洞评分系统的网络安全度量

管理人员通常使用一些网络安全指标作为度量网络安全的重要依据。通用漏洞评分系统（CVSS）是目前人们普遍认同的网络度量方式之一。针对现有的基于CVSS的网络安全度量无法精确测量网络受到攻击的概率和影响两方面得分的问题，提出一种基于依赖关系图和CVSS的改进基础度量算法。首先发掘攻击图中漏洞节点的依赖关系，构建依赖关系图；然后根据依赖关系修改CVSS中漏洞的基础度量算法；最后聚合整个攻击图中的漏洞得分，得到网络受到攻击的概率及影响两方面的得分。采用模拟攻击者进行仿真实验，结果表明，该算法在算法精确度和可信度方面明显优于汇总CVSS分数算法，更加接近实际仿真结果。     

一种基于攻击图的漏洞风险评估方法

传统的安全漏洞评估方法只是孤立地对单个漏洞进行评估,评估结果不能反映出漏洞对整个网络的影响程度。针对这个问题,提出了一种新的漏洞风险评估方法。该方法根据攻击图中漏洞间的依赖关系与漏洞的CVSS评分,首先计算出漏洞被利用的可能性与被利用后对整个网络的危害程度,并在此基础上计算出漏洞具有的风险值。由该方法计算出的漏洞风险能够准确地反映出漏洞对整个网络的影响程度,并通过实验证明了该方法的准确性与有效性。     

Measuring and ranking attacks based on vulnerability analysis

As the number of software vulnerabilities increases, the research on software vulnerabilities becomes a focusing point in information security. A vulnerability could be exploited to attack the information asset with the weakness related to the vulnerability. However, multiple attacks may target one software product at the same time, and it is necessary to rank and prioritize those attacks in order to establish a better defense. This paper proposes a similarity measurement to compare and categorize vulnerabilities, and a set of security metrics to rank attacks based on vulnerability analysis. The vulnerability information is retrieved from a vulnerability management ontology integrating commonly used standards like CVE (http://www.cve.mitre.org/), CWE (http://www.cwe.mitre.org/), CVSS (http://www.first.org/cvss/), and CAPEC (http://www.capec.mitre.org/). This approach can be used in many areas of vulnerability management to secure information systems and e-business, such as vulnerability classification, mitigation and patching, threat detection and attack prevention.     

改进漏洞基础评分指标权重分配方法

针对通用漏洞评分系统（CVSS）的基础评分指标权重分配过多依赖专家经验导致客观性不足的问题,提出一种漏洞威胁基础评分指标权重分配方法。首先,对评分要素的相对重要性进行排序;然后,采用指标权重组合最优搜索方法搜索权重组合方案;最后,结合灰色关联度分析方法,将基于专家经验决策的多个权重分配方案作为输入,获得权重组合方案。实验结果表明,与CVSS相比,从定量角度对比分析,所提方法评分结果分值分布比CVSS更为平缓连续,有效地避免了过多极端值的出现,并且评分分值分布的离散化更能客观有效地区分不同漏洞威胁的严重性;从定性角度对比分析,与CVSS中绝大多数漏洞（92.9%）被定为中高严重级别相比,所提方法在漏洞严重等级分配上实现了更为均衡的特征分布。     

动静态特征结合的漏洞风险评估及缓解方法

针对如何提高漏洞风险评估的准确性进行了研究,提出一种动静态特征结合的漏洞风险评估及缓解方法。通过将传统风险评估方法中常用的来源于通用漏洞评分系统（CVSS）的攻击复杂度、影响程度、攻击向量等固定属性作为静态特征,将防御能力、漏洞修复情况、攻击者的攻击能力等随时间推移可能发生变化的属性作为动态特征,两者结合对漏洞的风险程度进行更加全面的评估。给出了在实际应用中各特征的量化计算方法,以及漏洞修复策略的推荐方法。以单个漏洞的风险评估过程和多个漏洞的风险评估结果为例,将评估结果与CVSS评分进行对比实验。结果表明该方法能结合具体的网络环境给出更加准确的漏洞风险评估结果及合理的漏洞修复策略,验证了该方法的可行性和有效性。     

CVSS环境指标变量对系统安全的影响研究

通用漏洞评分体系(CVSS)分三个层次对漏洞的威胁进行评估,特定系统的安全性反映在最终的环境分层面上。在CVSS的三组指标变量中,仅环境指标变量取决于特定组织机构、特定系统,难以自动获取,是用户实施安全风险管理和控制策略中关键的和最困难的环节。在分析CVSS计算方法基础上,研究环境指标变量对最终CVSS总分的影响,给出了环境指标向量对CVSS环境分影响的总体估计式,同时给出了环境向量各分量单独影响的估计式。实验表明,本文在CVSS环境指标变量的总体影响和分项指标影响两方面,实现了精度提升,进入了实际标准完全可接受的范围。     

基于攻击图的网络安全度量研究

随着现代社会对网络系统依赖程度的日益增强,网络安全问题受到普遍关注。网络安全度量是指在理解网络环境的基础之上,建立合适指标体系和度量方法,评估网络的安全性。本文采用攻击图这种网络脆弱性分析技术,在对目标网络和攻击者建模的基础之上,根据两者之间的相互关系生成攻击图模型,分析不同的攻击路径。借鉴CVSS对单一漏洞的量化指标,以及节点间概率转换关系,提出攻击伸缩性机理。结合CVSS指标和攻击图,计算攻击伸缩性数值,并以此作为网络安全度量的方法,最后总结了当前网络安全度量的发展现状以及面临的挑战。     

面向漏洞生命周期的安全风险度量方法

为了反映信息系统安全漏洞的风险随时间动态变化的规律,构建基于吸收Markov链的漏洞生命周期模型,计算先验历史漏洞信息作为模型输入,构造漏洞生命周期的状态转移概率矩阵,在时间维度上利用矩阵对状态演化过程进行推导.借鉴通用漏洞评分标准分析漏洞威胁影响,给出安全漏洞的时间维度风险量化方法,并对漏洞生命周期各状态发生概率的演化规律进行总结和分析.最后以典型APT攻击场景中“WannaCry”勒索病毒的漏洞利用过程为例,验证了模型及方法的合理性和有效性.     

Do bugs foreshadow vulnerabilities? An in-depth study of the chromium project

As developers face an ever-increasing pressure to engineer secure software, researchers are building an understanding of security-sensitive bugs (i.e. vulnerabilities). Research into mining software repositories has greatly increased our understanding of software quality via empirical study of bugs. Conceptually, however, vulnerabilities differ from bugs: they represent an abuse of functionality as opposed to insufficient functionality commonly associated with traditional, non-security bugs. We performed an in-depth analysis of the Chromium project to empirically examine the relationship between bugs and vulnerabilities. We mined 374,686 bugs and 703 post-release vulnerabilities over five Chromium releases that span six years of development. We used logistic regression analysis, ranking analysis, bug type classifications, developer experience, and vulnerability severity metrics to examine the overarching question: are bugs and vulnerabilities in the same files? While we found statistically significant correlations between pre-release bugs and post-release vulnerabilities, we found the association to be weak. Number of features, source lines of code, and pre-release security bugs are, in general, more closely associated with post-release vulnerabilities than any of our non-security bug categories. In further analysis, we examined sub-types of bugs, such as stability-related bugs, and the associations did not improve. Even the files with the most severe vulnerabilities (by measure of CVSS or bounty payouts) did not show strong correlations with number of bugs. These results indicate that bugs and vulnerabilities are empirically dissimilar groups, motivating the need for security engineering research to target vulnerabilities specifically.     

基于关联性的漏洞评估方法

为了更加有效地评估漏洞威胁, 在原有的基于关联性漏洞评估方法的基础上, 从漏洞的可利用性出发, 分析了通用漏洞评估系统（CVSS）作为漏洞可利用性评价指标的缺点。在改进CVSS评价指标的基础上, 提出了更为合理的漏洞可利用性评估体系, 并改进了原有的漏洞评估方法。该方法能够有效地挖掘漏洞自身特点, 科学地进行漏洞评估, 并通过实验验证了该方法的合理性和有效性。     

Analyses of two end-user software vulnerability exposure metrics (extended version)

Understanding the exposure risk of software vulnerabilities is an important part of the software ecosystem. Reliable software vulnerability metrics allow end-users to make informed decisions regarding the risk posed by the choice of one software package versus another. In this article, we develop and analyze two new security metrics: median active vulnerabilities (MAV) and vulnerability free days (VFD). Both metrics take into account both the rate of vulnerability discovery and the rate at which vendors produce corresponding patches. We examine how our metrics are computed from publicly available data sets and then demonstrate their use in a case study with various vendors and products. Finally, we discuss the use of the metrics by various software stakeholders and how end-users can benefit from their use.     

收益与代价相结合的漏洞修复模型

漏洞修复是增强网络安全性的重要方法,选择性地修复网络中漏洞具有现实意义.提出一种收益与代价相结合的漏洞修复模型BCVRM.漏洞修复收益评价算法基于简化的攻击图生成算法,对比漏洞修复前后网络整体及相关各类型主机安全状态的提升,给出漏洞修复的总收益.漏洞修复代价评分系统基于CVSS对漏洞属性信息的描述,给出单个漏洞修复代价的评分规则,然后结合漏洞所属主机类型及漏洞分布情况给出网络漏洞修复代价.实例网络分析表明,该模型能够为网络管理人员提供一个切实可行的网络漏洞修复策略.     

基于攻防树的APT风险分析方法

针对目前缺少APT攻击中系统威胁风险评估理论模型的问题,提出了一种基于攻防树的网络攻击风险分析方法。将APT攻击过程分为攻击阶段与防护阶段,定义不同阶段内的参数计算方法,首先通过漏洞收集和攻击事件捕获构建攻击行为节点,并将防护对策映射为防护行为节点;其次形式化定义了漏洞成功利用概率、攻击成本、防护成本和系统损失度等参数,利用ADTool工具生成攻防树和节点参数值;然后引入攻击回报与防护回报的概念,作为系统风险分析的依据;最后构建了基于攻防树的攻击风险分析框架,并通过一个APT攻击实例对框架效果进行了验证。计算结果表明,可通过攻击回报等参数数值的变化评估采取防护对策的效果。该方法对攻防双方策略互相影响的场景描述更加贴近实际,实现了系统威胁风险度分析与防护策略效果评估的目的。     

Impact Metrics of Security Vulnerabilities: Analysis and Weighing

ABSTRACT

The number of vulnerabilities discovered and reported during the recent decades is enormous, making an improved ranking and prioritization of vulnerabilities’ severity a major issue for information technology (IT) management. Although several methodologies for ranking and scoring vulnerabilities have been proposed, the Common Vulnerability Scoring System (CVSS) is the open standard with wide acceptance from the information security community. Recently, the Weighted Impact Vulnerability Scoring System (WIVSS) has been proposed as an alternative scoring methodology, which assigns different weights to impact factors of vulnerability in order to achieve higher diversity of values and thus improvement in flexibility of ranking in comparison to CVSS. The purpose of this paper is to expand the idea of WIVSS by defining the sets of weights which provide higher diversity of values. For this reason, an algorithm that finds all the possible combinations of optimal weights within a specified range and under certain constrains is presented. The algorithm results in 14 different combinations of impact weights that are applied to a sample of 20,496 vulnerabilities and statistically analyzed for associations among impact factors. The results suggest that one specific combination of impact weights can achieve highest diversity of values.     

一种通用漏洞评级方法

漏洞是网络安全事件的主要根源,漏洞的大量存在及其带来的危害使漏洞评级变得尤为重要。该文分析目前著名安全机构和生产厂商对漏洞进行评级的特点,介绍通用缺陷评估系统(CVSS)及其存在的缺点,在CVSS的基础上提出一种更完善的定量评级方法CVRS,通过评估实例说明了CVRS的有效性和优越性。     

ROI-Driven Cyber Risk Mitigation Using Host Compliance and Network Configuration

Automated cyber security configuration synthesis is the holy grail of cyber risk management. The effectiveness of cyber security is highly dependent on the appropriate configuration hardening of heterogeneous, yet interdependent, network security devices, such as firewalls, intrusion detection systems, IPSec gateways, and proxies, to minimize cyber risk. However, determining cost-effective security configuration for risk mitigation is a complex decision-making process because it requires considering many different factors including end-hosts’ security weaknesses based on compliance checking, threat exposure due to network connectivity, potential impact/damage, service reachability requirements according to business polices, acceptable usability due to security hardness, and budgetary constraints. Although many automated techniques and tools have been proposed to scan end-host vulnerabilities and verify the policy compliance, existing approaches lack metrics and analytics to identify fine-grained network access control based on comprehensive risk analysis using both the hosts’ compliance reports and network connectivity. In this paper, we present new metrics and a formal framework for automatically assessing the global enterprise risk and determining the most cost-effective security configuration for risk mitigation considering both the end-host security compliance and network connectivity. Our proposed metrics measure the global enterprise risk based on the end-host vulnerabilities and configuration weaknesses, collected through compliance scanning reports, their inter-dependencies, and network reachability. We then use these metrics to automatically generate a set of host-based vulnerability fixes and network access control decisions that mitigates the global network risk to satisfy the desired Return on Investment of cyber security. We solve the problem of cyber risk mitigation based on advanced formal methods using Satisfiability Module Theories, which has shown scalability with large-size networks.     

Modeling discovery and removal of security vulnerabilities in software system using priority queueing models

This paper aims to model the discovery and removal of software vulnerabilities based on queueing theory. The probabilistic characteristics of the arrival and service processes are the core elements of queueing theory. Discovering and removing software vulnerabilities corresponds arrival and service processes in queueing models, respectively. Vulnerabilities can be classified into groups depending upon its severity levels measured by CVSS (common vulnerability scoring system). Groups with higher severity levels are fixed more quickly than groups with lower severity levels. Priority queueing models can be used and give various performance indices: the number of unfixed vulnerabilities at arbitrary instances and waiting time before getting fixed. Moreover, the service rate to prevent the number or accumulated degree of vulnerabilities from exceeding the predetermined level can be estimated.     

数值稳定性相关漏洞隐患的自动化检测方法

安全漏洞检测是保障软件安全性的重要手段.随着互联网的发展,黑客的攻击手段日趋多样化,且攻击技术不断翻新,使软件安全受到了新的威胁.本文描述了当前软件中实际存在的一种新类型的安全漏洞隐患,我们称之为数值稳定性相关的安全漏洞隐患.由于黑客可以利用该类漏洞绕过现有的防护措施,且已有的数值稳定性分析方法很难检测到该类漏洞的存在,因而这一新类型的漏洞隐患十分危险.面对这一挑战,本文首先从数值稳定性引起软件行为改变的角度定义了数值稳定性相关的安全漏洞隐患,并给出了对应的自动化检测方法.该方法基于动静态相结合的程序分析与符号执行技术,通过数值变量符号式提取、静态攻击流程分析、以及高精度动态攻击验证三个步骤,来检测和分析软件中可能存在的数值稳定性相关安全漏洞.我们在业界多个著名开源软件上进行了实例研究,实验结果表明,本文方法能够有效检测到实际软件中真实存在的数值稳定性相关漏洞隐患.     

基于流量分析的软件升级漏洞自动检测方法

软件升级过程中,缺乏对升级信息或升级包的认证可能会导致基于中间人攻击的远程代码执行漏洞。为此,提出一种升级漏洞自动检测方法。该方法通过提取升级过程中的网络流量,对升级机制自动画像,将其与漏洞特征向量匹配,预判升级漏洞;在模拟验证环境中,利用画像信息实施中间人攻击,验证检测结果。基于该方法设计了升级漏洞自动分析与验证系统,对 184 个 Windows 应用软件样本进行测试,检测出 117个样本的升级漏洞,证明了本方法的有效性。