Skip to main content

Survivability analysis of a computer system under an advanced persistent threat attack

Publication ,  Conference
Rodríguez, RJ; Chang, X; Li, X; Trivedi, KS
Published in: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
January 1, 2016

Computer systems are potentially targeted by cybercriminals by means of specially crafted malicious software called Advanced Persistent Threats (APTs). As a consequence, any security attribute of the computer system may be compromised: disruption of service (availability), unauthorized data modification (integrity), or exfiltration of sensitive data (confidentiality). An APT starts with the exploitation of software vulnerability within the system. Thus, vulnerability mitigation strategies must be designed and deployed in a timely manner to reduce the window of exposure of vulnerable systems. In this paper, we evaluate the survivability of a computer system under an APT attack using a Markov model. Generation and solution of the Markov model are facilitated by means of a high-level formalism based on stochastic Petri nets. Survivability metrics are defined to quantify security attributes of the system from the public announcement of a software vulnerability and during the system recovery. The proposed model and metrics not only enable us to quantitatively assess the system survivability in terms of security attributes but also provide insights on the cost/revenue tradeoffs of investment efforts in system recovery such as vulnerability mitigation strategies. Sensitivity analysis through numerical experiments is carried out to study the impact of key parameters on system secure survivability.

Duke Scholars

Published In

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

DOI

EISSN

1611-3349

ISSN

0302-9743

Publication Date

January 1, 2016

Volume

9987 LNCS

Start / End Page

134 / 149

Related Subject Headings

  • Artificial Intelligence & Image Processing
  • 46 Information and computing sciences
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Rodríguez, R. J., Chang, X., Li, X., & Trivedi, K. S. (2016). Survivability analysis of a computer system under an advanced persistent threat attack. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9987 LNCS, pp. 134–149). https://doi.org/10.1007/978-3-319-46263-9_9
Rodríguez, R. J., X. Chang, X. Li, and K. S. Trivedi. “Survivability analysis of a computer system under an advanced persistent threat attack.” In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9987 LNCS:134–49, 2016. https://doi.org/10.1007/978-3-319-46263-9_9.
Rodríguez RJ, Chang X, Li X, Trivedi KS. Survivability analysis of a computer system under an advanced persistent threat attack. In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2016. p. 134–49.
Rodríguez, R. J., et al. “Survivability analysis of a computer system under an advanced persistent threat attack.” Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9987 LNCS, 2016, pp. 134–49. Scopus, doi:10.1007/978-3-319-46263-9_9.
Rodríguez RJ, Chang X, Li X, Trivedi KS. Survivability analysis of a computer system under an advanced persistent threat attack. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2016. p. 134–149.

Published In

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

DOI

EISSN

1611-3349

ISSN

0302-9743

Publication Date

January 1, 2016

Volume

9987 LNCS

Start / End Page

134 / 149

Related Subject Headings

  • Artificial Intelligence & Image Processing
  • 46 Information and computing sciences