An Attack Graph Based Approach for Threat Identification of an Enterprise Network

An Attack Graph Based Approach for Threat Identification of an Enterprise Network

Somak Bhattacharya (Indian Institute of Technology, Kharagpur, India), Samresh Malhotra (Indian Institute of Technology, Kharagpur, India) and S. K. Ghosh (Indian Institute of Technology, Kharagpur, India)
DOI: 10.4018/978-1-60566-326-5.ch002
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Abstract

As networks continue to grow in size and complexity, automatic assessment of the security vulnerability becomes increasingly important. The typical means by which an attacker breaks into a network is through a series of exploits, where each exploit in the series satisfies the pre-condition for subsequent exploits and makes a causal relationship among them. Such a series of exploits constitutes an attack path where the set of all possible attack paths form an attack graph. Attack graphs reveal the threat by enumerating all possible sequences of exploits that can be followed to compromise a given critical resource. The contribution of this chapter is to identify the most probable attack path based on the attack surface measures of the individual hosts for a given network and also identify the minimum possible network securing options for a given attack graph in an automated fashion. The identified network securing options are exhaustive and the proposed approach aims at detecting cycles in forward reachable attack graphs. As a whole, the chapter deals with identification of probable attack path and risk mitigation which may facilitate in improving the overall security of an enterprise network.
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Introduction

With the increased reliance and dependence on networks, the threats that an enterprise faces, both external as well as internal, has also increased phenomenally. A security administrator is always faced with the challenge of identifying these threats, and in retrospect, securing the organization’s network. The classical approach of identifying the vulnerabilities of individual hosts using commercially available tools, like the Retina and Nessus, does not take into account vulnerability interactions. These vulnerability interrelationships are very important to get a holistic view of network security from the security administrator’s point of view. The vulnerability interactions are best captured by an attack graph, which helps in identifying all the possible ways in which an attacker can reach a critical resource on the network.

The attack graph generation is a first step towards threat identification of an enterprise network. There are two basic approaches of generating an attack graph, namely the state based approach (Ammann et al., 2002; Philips et al., 1998) and host based approach (Ammann et al., 2005; Ingols et al., 2006). Several previous approaches (Ammann et al., 2002; Li et al., 2006) have used the combination of a forward and backward chaining algorithm to identify an attack graph. The state based approach gives information at a more granular level whereas its representation soon becomes very large and complex even for a moderate size network (Sheyner et al., 2002). On the other hand, in a host based attack graph each node will be identified as a network entity and the edges will be privileges obtained after applying exploits among them. The host based approach gives a compact representation which may be useful for a visual representation and handle scalability at the cost of abstracting several low level details related to exploit correlation, vulnerability and attacker privileges. For example, obtaining user level privilege on a host, say host 1, and escalation of that privilege to the super user level can be treated as two distinguished states in a state based approach. On the other hand, a host based approach combines all such individual privileges and retains the highest level privilege as a graph edge. Availability of the low level details in a state based attack graph makes it convenient for proper risk management.

The proposed approach uses the state based forward chaining algorithm (Ammann et al., 2002) to generate an attack graph with necessary exploits. The necessary exploits are the set of exploits, subset of which will be actually used by the attacker to obtain the goal. Therefore, the forward reachable attack graph may contain redundancies. The run time complexity of such forward chaining algorithm can be represented by the polynomial O (|A|2. E) (Ammann et al., 2002), where A is the number of network conditions and E is the number of exploits. Each vertex in the generated attack graph is used to represent network state and the corresponding exploits, the edges are used to represent the causal relationship among network states and exploits. The proposed approach in Ammann et al. (2002) does a backward search to generate attack graph with sufficient exploits from the forward reachable attack graph. Our proposed approach differs from Ammann et al. (2002) in that it works in two dimensions. On one hand it identifies the most probable attack path(s) based on the attack surface measure of the individual hosts, independent of the vulnerabilities or the exploits that may exist and on the other hand that for identifying the actual exploit correlation for risk mitigation rather than generating an attack graph it uses a forward reachable graph and thus identifies all the possible network securing options.

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Table of Contents
Foreword
Merrill Warkentin
Preface
Kenneth J. Knapp
Acknowledgment
Kenneth J. Knapp
Chapter 1
Jaziar Radianti, Jose J. Gonzalez
This chapter discusses the possible growth of black markets (BMs) for software vulnerabilities and factors affecting their spread. It is difficult... Sample PDF
Dynamic Modeling of the Cyber Security Threat Problem: The Black Market for Vulnerabilities
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Chapter 2
Somak Bhattacharya, Samresh Malhotra, S. K. Ghosh
As networks continue to grow in size and complexity, automatic assessment of the security vulnerability becomes increasingly important. The typical... Sample PDF
An Attack Graph Based Approach for Threat Identification of an Enterprise Network
$37.50
Chapter 3
Robert F. Mills, Gilbert L. Peterson, Michael R. Grimaila
The purpose of this chapter is to introduce the insider threat and discuss methods for preventing, detecting, and responding to the threat. Trusted... Sample PDF
Insider Threat Prevention, Detection and Mitigation
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Chapter 4
Richard T. Gordon, Allison S. Gehrke
This chapter describes a methodology for assessing security infrastructure effectiveness utilizing formal mathematical models. The goal of this... Sample PDF
An Autocorrelation Methodology for the Assessment of Security Assurance
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Chapter 5
Ken Webb
This chapter results from a qualitative research study finding that a heightened risk for management has emerged from a new security environment... Sample PDF
Security Implications for Management from the Onset of Information Terrorism
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Chapter 6
Yves Barlette, Vladislav V. Fomin
This chapter introduces major information security management methods and standards, and particularly ISO/IEC 27001 and 27002 standards. A... Sample PDF
The Adoption of Information Security Management Standards: A Literature Review
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Chapter 7
Peter R. Marksteiner
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Data Smog, Techno Creep and the Hobbling of the Cognitive Dimension
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Chapter 8
John W. Bagby
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Chapter 9
Indira R. Guzman, Kathryn Stam, Shaveta Hans, Carole Angolano
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Human Factors in Security: The Role of Information Security Professionals within Organizations
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Chapter 10
Nikolaos Bekatoros HN, Jack L. Koons III, Mark E. Nissen
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Chapter 11
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An Approach to Managing Identity Fraud
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Chapter 12
Alanah Davis, Gert-Jan de Vreede, Leah R. Pietron
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Chapter 13
Dean A. Jones, Linda K Nozick, Mark A. Turnquist, William J. Sawaya
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Chapter 15
Gregory B. White, Mark L. Huson
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Chapter 16
Doug White, Alan Rea
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Chapter 17
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Chapter 18
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