SCIATool: A Tool for Analyzing SELinux Policies Based on Access Control Spaces, Information Flows and CPNs

  • Gaoshou ZhaiEmail author
  • Tao Guo
  • Jie Huang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9473)


Although security policies configuration is crucial for operating systems to constrain applications’ operations and to protect the confidentiality and integrity of sensitive resources inside the systems, it is an intractable work for security administrators to accomplish correctly and consistently solely by hands. Thus policies analysis methods are becoming research hotspots. A great deal of such researches are focused on SELinux, which is a security-enhanced module of open-source and popular Linux. Among various analysis methods for SELinux policies, those based on access control spaces, information flows and colored Petri-nets (CPNs) can be thought as the three most valuable methods and they can be exploited together and complementarily. In this paper, a prototype of SELinux policies Configuration Integrated Analysis Tool, i.e. SCIATool, is designed and implemented by integrating these three methods together. Test results are provided and further researches as to construct a computer-aided configuration tool for SELinux policies are discussed.


Security policies configuration Analysis method Access control spaces Information flows Colored Petri-nets SELinux 



The research presented in this paper was performed with the support of the Fundamental Research Funds for the Central Universities (No. 2009JBM019). This paper was also supported by the State Scholarship Fund of China Scholarship Council (File No. 201307095025).


  1. 1.
    Smalley, S., Vance, C., Salamon, W.: Implementing SELinux as a linux security module. NAI labs report #01-043 (2006)Google Scholar
  2. 2.
    Smalley. S.: Configuring the SELinux policy. NAI Labs Report #02-007 (2005)Google Scholar
  3. 3.
    Jaeger, T., Zhang, X., Edwards, A.: Policy management using access control space. ACM Trans. Inf. Syst. Secur. 6(3), 327–364 (2003)CrossRefGoogle Scholar
  4. 4.
    Zanin, G., Mancini, L.V.: Towards a formal model for security policies specification and validation in the SELinux system. In: Proceedings of the 9th ACM Symposium on Access Control Models and Technologies, pp. 136–145. Association for Computing Machinery (ACM), New York (2004)Google Scholar
  5. 5.
    Zhai, Gaoshou, Tong, Wu: Algorithms for automatic analysis of SELinux security policy. Int. J. Secur. Appl. 7(1), 71–84 (2013)Google Scholar
  6. 6.
    Zhai, Gaoshou, Tong, Wu: Automatic analysis method for SELinux security policy. Int. J. Secur. Appl. 6(2), 229–234 (2012)Google Scholar
  7. 7.
    Guttman, J.D., Herzog, A.L., Ramsdell, J.D.: Information flow in operating systems: eager formal methods. In: Workshop on Issues in the Theory of Security (WITS 2003). IFIP WG 1.7, ACM SIGPLAN and GI FoMSESS. Warsaw, Poland (2003)Google Scholar
  8. 8.
    Guttman, J.D., Herzog, A.L., Ramsdell, J.D., Skorupka, C.W.: Verifying information flow goals in security-enhanced linux. J. Comput. Secur. 13, 115–134 (2005)Google Scholar
  9. 9.
    Chen, Y.-M., Kao, Y.-W.: Information flow query and verification for security policy of security-enhanced linux. In: Yoshiura, H., Sakurai, K., Rannenberg, K., Murayama, Y., Kawamura, S.-I. (eds.) IWSEC 2006. LNCS, vol. 4266, pp. 389–404. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  10. 10.
    Gu, L., Guo, Y., Yang, Y., Bao, F., Mei, H.: Modeling TCG-based secure systems with colored petri nets. In: Chen, L., Yung, M. (eds.) INTRUST 2010. LNCS, vol. 6802, pp. 67–86. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  11. 11.
    Ahn, G.J., Xu, W., Zhang, X.: Systematic policy analysis for high-assurance services in SELinux. In: Proceedings of 2008 IEEE Workshop on Policies for Distributed Systems and Networks, pp. 3–10. IEEE Computer Society (2008)Google Scholar
  12. 12.
    Guo, Tao, Zhai, Gaoshou: Automatic analysis of SELinux security policies based on colored petri-net (in Chinese). Inf. Secur. Technol. 4(11), 35–40 (2013)Google Scholar
  13. 13.
    Jaeger, T., Sailer, R., Zhang, X.: Analyzing integrity protection in the SELinux example policy. In: Proceedings of the 12th USENIX Security Symposium, pp. 59–74. Washington, D.C., USA (2003)Google Scholar
  14. 14.
    Jaeger, T., Sailer, R., Zhang, X.: Resolving constraint conflicts. In: SACMAT 2004, pp. 105–114. Yorktown Heights, New York, USA (2004)Google Scholar
  15. 15.
    Guttman, J.D., Herzog, A.L., Ramsdell, J.D.: SLAT: information flow in security enhanced linux. Included in the SLAT distribution, available from (2003)
  16. 16.
    Sarna-Starosta, B., Stoller, S.D.: Policy analysis for security-enhanced linux. In: Proceedings of the Workshop on Issues in the Theory of Security (WITS 2004), pp. 1–12. IFIP WG 1.7, ACM SIGPLAN and GI FoMSESS. Barcelona, Spain (2004)Google Scholar
  17. 17.
    Hicks, B., Rueda, S., St. Clair, L., Jaeger, T., McDaniel, P.: A logical specification and analysis for SELinux MLS policy. ACM Trans. Inf. Syst. Secur. 13(3), 26 (2010)CrossRefGoogle Scholar
  18. 18.
    Kissinger, A., Hale, J.C.: Lopol: a deductive database approach to policy analysis and rewriting. In: Proceedings of the Second Annual Security-enhanced Linux Symposium. Baltimore, Maryland, USA (2006)Google Scholar
  19. 19.
    Singh, A., Amakrishnan, C.R., Ramakrishnan, I.V.: Security policy analysis using deductive spreadsheets. In: FMSE 2007, pp. 42–50. Fairfax, Virginia, USA (2007)Google Scholar
  20. 20.
    Amthor, P., Kühnhauser, W.E., Pölck, A.: Model-based safety analysis of SELinux security policies. In: 2011 5th International Conference on Network and System Security (NSS), pp. 208–215. IEEE Press, New York (2011)Google Scholar
  21. 21.
    Marouf, S., Phuong, D.M., Shehab, M.: A learning-based approach for SELinux policy optimization with type mining. In: Proceedings of the Sixth Annual Workshop on Cyber Security and Information Intelligence Research (CSIIRW 2010). ACM, New York (2010)Google Scholar
  22. 22.
    Tresys Technology: SETools—policy analysis tools for SELinux.
  23. 23.
    Wenjuan, X., Shehab, M., Ahn, G.-J.: Visualization-based policy analysis for SELinux: framework and user study. Int. J. Inf. Secur. 12, 155–171 (2013)CrossRefGoogle Scholar
  24. 24.
    Clemente, P., Kaba, B., Rouzaud-Cornabas, J., Alexandre, M., Aujay, G.: SPTrack: visual analysis of information flows within SELinux policies and attack logs. In: Huang, R., Ghorbani, A.A., Pasi, G., Yamaguchi, T., Yen, N.Y., Jin, B. (eds.) AMT 2012. LNCS, vol. 7669, pp. 596–605. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  25. 25.
    Marouf, S., Shehab, M.: SEGrapher: visualization-based SELinux policy analysis. In: 2011 4th Symposium on Configuration Analytics and Automation (SAFECONFIG), pp. 1–8. Arlington, VA. IEEE Press, New York (2011)Google Scholar
  26. 26.
    Amthor, P., Kuhnhauser, W.E., Polck, A.: WorSE: a workbench for model-based security engineering. Comput. Secur. 42, 40–55 (2014)CrossRefGoogle Scholar
  27. 27.
    Athey, J., Ashworth, C., Mayer, F., Miner, D.: Towards Intuitive tools for managing SELinux: hiding the details but retaining the power. Tresys Technology. Accessed 12 March 2007
  28. 28.
    MacMillan, K., Brindle, J., Mayer, F., Caplan, D., Tang, J.: Design and Implementation of the SELinux policy management server. Tresys Technology. Accessed 1 March 2006
  29. 29.
    Singh, S.: Automatic verification of security policy implementations. Doctoral Dissertation in Computer Science, University of Illinois at Urbana-Champaign (2012)Google Scholar
  30. 30.
    Nakamura, Y., Sameshima, Y., Yamauchi, T.: SELinux security policy configuration system with higher level language. J. Inf. Process. 18, 201–212 (2010)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.School of Computer and Information TechnologyBeijing Jiaotong UniversityBeijingChina
  2. 2.Henan Center of Patent Examination Cooperation of the Patent Office SPIOHenanChina

Personalised recommendations