Scalable, graph-based network vulnerability analysis

Ammann, Paul; Wijesekera, Duminda; Kaushik, Saket

doi:10.1145/586139.586140

Cited by 324 publications

(284 citation statements)

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“…Attack graph [1,2,4,10] and attack tree [8,9] representations have been proposed in network vulnerability management to demonstrate such causeconsequence relationships. The nodes in these data structures usually represent a certain network state of interest to an attacker, with edges connecting them to indicate the causeconsequence relationship.…”

Section: Attack Tree Modelmentioning

confidence: 99%

“…Although different attack scenarios are easily perceived in attack graphs, they can potentially suffer from a state space explosion problem. Ammann et al [1] identified this problem and propose an alternative formulation with the assumption of monotonicity. The monotonicity property states that the consequence of an attack is always preserved once achieved.…”

Section: Attack Tree Modelmentioning

confidence: 99%

“…A security manager can estimate the expected number of attack from the organization-based historical data or public historical data. 1 Step 3 Assess a single value function, V i j (x i j ), for each possible consequence. The purpose of this function is to normalize different unit measures so that the values can be summed together under a single standard scale.…”

Section: Evaluating Potential Damagementioning

confidence: 99%

“…Researchers have proposed building security models for networked systems using paradigms like attack graphs [1][2][3][4][5] and attack trees [6][7][8][9], and then finding attack paths in these models to determine the scenarios that could lead to damage. However, determining possible attack paths, although useful, does not help the system administrators much.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Optimal security hardening on attack tree models of networks: a cost-benefit analysis

Dewri

Ray

Poolsappasit

et al. 2012

Int. J. Inf. Secur.

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Researchers have previously looked into the problem of determining whether a given set of security hardening measures can effectively make a networked system secure. However, system administrators are often faced with a more challenging problem since they have to work within a fixed budget which may be less than the minimum cost of system hardening. An attacker, on the other hand, explores alternative attack scenarios to inflict the maximum damage possible when the security controls are in place, very often rendering the optimality of the controls invalid. In this work, we develop a systematic approach to perform a cost-benefit analysis on the problem of optimal security hardening under such conditions. Using evolutionary paradigms such as multi-objective optimization and competitive co-evolution, we model the attacker-defender interaction as an "arms race", and explore how security controls can be placed in a network to induce a maximum return on investment.

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Section: Attack Tree Modelmentioning

confidence: 99%

Section: Attack Tree Modelmentioning

confidence: 99%

Section: Evaluating Potential Damagementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Optimal security hardening on attack tree models of networks: a cost-benefit analysis

Dewri

Ray

Poolsappasit

et al. 2012

Int. J. Inf. Secur.

View full text Add to dashboard Cite

show abstract

“…Moreover, model checkers used for graph generation have state space explosion problem and do not handle a realistic set of exploits even for a moderate sized network. To improve the complexity of graph generation, some of the approaches [1,9,10] introduced an explicit assumption of monotonicity. This means once an attacker has gained certain level of privileges on a particular host, he does not have to regain them in the near future.…”

Section: Introductionmentioning

confidence: 99%

A planner-based approach to generate and analyze minimal attack graph

Ghosh

2010

Appl Intell

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In the present scenario, even well administered networks are susceptible to sophisticated cyber attacks. Such attack combines vulnerabilities existing on different systems/services and are potentially more harmful than single point attacks. One of the methods for analyzing such security vulnerabilities in an enterprise network is the use of attack graph. It is a complete graph which gives a succinct representation of different attack scenarios, depicted by attack paths. An attack path is a logical succession of exploits, where each exploit in the series satisfies the preconditions for subsequent exploits and makes a causal relationship among them. Thus analysis of the attack graph may help in assessing network security from hackers' perspective. One of the intrinsic problems with the generation and analysis of such a complete attack graph is its scalability. In this work, an approach based on Planner, a special purpose search algorithm from artificial intelligence domain, has been proposed for time-efficient, scalable representation of the attack graphs. Further, customized algorithms have been developed for automatic generation of attack paths (using Planner as a low-level module). The analysis shows that generation of attack graph using the customized algorithms can be done in polynomial time. A case study has also been presented to demonstrate the efficacy of the proposed methodology.

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GraphBAD: A general technique for anomaly detection in security information and event management

Parkinson

Vallati

Crampton

et al. 2018

Concurrency and Computation

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The reliance on expert knowledge-required for analysing security logs and performing security audits-has created an unhealthy balance, where many computer users are not able to correctly audit their security configurations and react to potential security threats. The decreasing cost of IT and the increasing use of technology in domestic life are exacerbating this problem, where small companies and home IT users are not able to afford the price of experts for auditing their system configuration. In this paper, we present GraphBAD, a graph-based analysis tool that is able to analyse security configurations in order to identify anomalies that could lead to potential security risks. GraphBAD, which does not require any prior domain knowledge, generates graph-based models from security configuration data and, by analysing such models, is able to propose mitigation plans that can help computer users in increasing the security of their systems. A large experimental analysis, conducted on both publicly available (the well-known KDD dataset) and synthetically generated testing sets (file system permissions), demonstrates the ability of GraphBAD in correctly identifying security configuration anomalies and suggesting appropriate mitigation plans. KEYWORDSanomaly detection, graph structure, log files, security auditing, SIEM INTRODUCTIONAuditing security configurations is the process of searching for anomalies that potentially expose a vulnerability of a considered system. The term Security Information and Event Management (SIEM) is often used to describe the process of monitoring audit logs and security configurations to identify vulnerabilities. Given the complexity of the task, there is a heavy reliance on expert knowledge, which is required for understanding the different security configurations. This reliance has two main drawbacks: first, expert knowledge can be incomplete or erroneous; second, the high cost of security experts makes it infeasible for many users to correctly configure the security of their Information Technology (IT) systems. Therefore, in many cases, unseen weaknesses, which can be exploited, will remain in the configuration. Clearly, auditing security configurations is a critical problem for organisations that significantly rely on their IT infrastructure for undertaking business. For this reason, many companies frequently employ a third party security auditing company to examine their IT infrastructure to identify weaknesses and suggest suitable mitigation plans (named as penetration testing 1,2 ). Although businesses are prepared to pay a premium for maintaining their security, the average home IT user or small companies are left to maintain their own IT security. Furthermore, the decreasing cost of IT and the increasing use of technology in domestic life are exacerbating this problem.These limitations are heightened by the following factors. (i) The complexity of computational infrastructure-the cyber-physical platform on which security is attained-is increasing, and the technological landscape i...

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Scalable, graph-based network vulnerability analysis

Cited by 324 publications

References 0 publications

Optimal security hardening on attack tree models of networks: a cost-benefit analysis

Optimal security hardening on attack tree models of networks: a cost-benefit analysis

A planner-based approach to generate and analyze minimal attack graph

GraphBAD: A general technique for anomaly detection in security information and event management

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