Skip to main content
Top

2015 | OriginalPaper | Chapter

The AC-Index: Fast Online Detection of Correlated Alerts

Authors : Andrea Pugliese, Antonino Rullo, Antonio Piccolo

Published in: Security and Trust Management

Publisher: Springer International Publishing

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

We propose an indexing technique for alert correlation that supports DFA-like patterns with user-defined correlation functions. Our AC-Index supports (i) the retrieval of the top-k (possibly non-contiguous) sub-sequences, ranked on the basis of an arbitrary user-provided severity function, (ii) the concurrent retrieval of sub-sequences that match any pattern in a given set, (iii) the retrieval of partial occurrences of the patterns, and (iv) the online processing of streaming logs. The experimental results confirm that, although the supported model is very expressive, the AC-Index is able to guarantee a very high efficiency of the retrieval process.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Footnotes
1
Some past works assume aciclicity of the patterns because, in many practical cases, (i) the attacker’s control over the network increases monotonically, i.e., the attacker need not relinquish resources already gained during the attack, and (ii) the “criticality” associated with a sequence of alerts does not change when the sequence contains a portion that is repeated multiple times as it matches a cycle in the pattern. In such cases, the overall sequence is equivalent to the one obtained after removing the portion matching the cycle. We do not make this assumption as it would reduce the expressiveness of the model and it is not required by the AC-Index.
 
2
Note that a security expert may want to discard \(O_2\) and \(O_4\) because they are prefixes of \(O_1\) and \(O_3\) respectively.
 
3
For simplicity of presentation, the run with all parameters set to default values is reported as three separate runs (6, 9, and 14) in Fig. 7.
 
Literature
1.
go back to reference Agrawal, J., Diao, Y., Gyllstrom, D., Immerman, N.: Efficient pattern matching over event streams. In: SIGMOD (2008) Agrawal, J., Diao, Y., Gyllstrom, D., Immerman, N.: Efficient pattern matching over event streams. In: SIGMOD (2008)
2.
go back to reference Albanese, M., Jajodia, S., Pugliese, A., Subrahmanian, V.S.: Scalable analysis of attack scenarios. In: Atluri, V., Diaz, C. (eds.) ESORICS 2011. LNCS, vol. 6879, pp. 416–433. Springer, Heidelberg (2011) CrossRef Albanese, M., Jajodia, S., Pugliese, A., Subrahmanian, V.S.: Scalable analysis of attack scenarios. In: Atluri, V., Diaz, C. (eds.) ESORICS 2011. LNCS, vol. 6879, pp. 416–433. Springer, Heidelberg (2011) CrossRef
3.
go back to reference Albanese, M., Pugliese, A., Subrahmanian, V.S.: Fast activity detection: Indexing for temporal stochastic automaton-based activity models. IEEE Trans. Knowl. Data Eng. 25(2), 360–373 (2013)CrossRef Albanese, M., Pugliese, A., Subrahmanian, V.S.: Fast activity detection: Indexing for temporal stochastic automaton-based activity models. IEEE Trans. Knowl. Data Eng. 25(2), 360–373 (2013)CrossRef
4.
go back to reference Babenko, A., Mariani, L., Pastore, F.: Ava: automated interpretation of dynamically detected anomalies. In: ISSTA (2009) Babenko, A., Mariani, L., Pastore, F.: Ava: automated interpretation of dynamically detected anomalies. In: ISSTA (2009)
5.
go back to reference Bass, T.: Intrusion detection systems and multisensor data fusion. Commun. ACM 43(4), 99–105 (2000)CrossRef Bass, T.: Intrusion detection systems and multisensor data fusion. Commun. ACM 43(4), 99–105 (2000)CrossRef
6.
go back to reference Branch, J., Bivens, A., Lee, T.K.: Denial of service intrusion detection using time dependent deterministic finite automata. In: Graduate Research Conference (2002) Branch, J., Bivens, A., Lee, T.K.: Denial of service intrusion detection using time dependent deterministic finite automata. In: Graduate Research Conference (2002)
7.
go back to reference Creech, G., Hu, J.: A semantic approach to host-based intrusion detection systems using contiguousand discontiguous system call patterns. IEEE Trans. Comput. 63(4), 807–819 (2014)MathSciNetCrossRef Creech, G., Hu, J.: A semantic approach to host-based intrusion detection systems using contiguousand discontiguous system call patterns. IEEE Trans. Comput. 63(4), 807–819 (2014)MathSciNetCrossRef
8.
go back to reference Cuppens, F., Miege, A.: Alert correlation in a cooperative intrusion detection framework. In: S&P (2002) Cuppens, F., Miege, A.: Alert correlation in a cooperative intrusion detection framework. In: S&P (2002)
9.
go back to reference Demers, A., Gehrke, J., Hong, M., Riedewald, M., White, W.: Towards expressive publish/subscribe systems. In: Ioannidis, Y., Scholl, M.H., Schmidt, J.W., Matthes, F., Hatzopoulos, M., Böhm, K., Kemper, A., Grust, T., Böhm, C. (eds.) EDBT 2006. LNCS, vol. 3896, pp. 627–644. Springer, Heidelberg (2006) CrossRef Demers, A., Gehrke, J., Hong, M., Riedewald, M., White, W.: Towards expressive publish/subscribe systems. In: Ioannidis, Y., Scholl, M.H., Schmidt, J.W., Matthes, F., Hatzopoulos, M., Böhm, K., Kemper, A., Grust, T., Böhm, C. (eds.) EDBT 2006. LNCS, vol. 3896, pp. 627–644. Springer, Heidelberg (2006) CrossRef
10.
go back to reference Demers, A.J., Gehrke, J., Panda, B., Riedewald, M., Sharma, V., White, W.M.: Cayuga: a general purpose event monitoring system. In: CIDR (2007) Demers, A.J., Gehrke, J., Panda, B., Riedewald, M., Sharma, V., White, W.M.: Cayuga: a general purpose event monitoring system. In: CIDR (2007)
11.
go back to reference Garcia-Teodoro, P., Díaz-Verdejo, J.E., Maciá-Fernández, G., Vázquez, E.: Anomaly-based network intrusion detection: techniques, systems and challenges. Comput. Secur. 28(1–2), 18–28 (2009)CrossRef Garcia-Teodoro, P., Díaz-Verdejo, J.E., Maciá-Fernández, G., Vázquez, E.: Anomaly-based network intrusion detection: techniques, systems and challenges. Comput. Secur. 28(1–2), 18–28 (2009)CrossRef
12.
go back to reference Gyllstrom, D., Agrawal, J., Diao, Y., Immerman, N.: On supporting kleene closure over event streams. In: ICDE (2008) Gyllstrom, D., Agrawal, J., Diao, Y., Immerman, N.: On supporting kleene closure over event streams. In: ICDE (2008)
13.
go back to reference Kosoresow, A.P., Hofmeyr, S.A.: Intrusion detection via system call traces. IEEE Softw. 14(5), 35–42 (1997)CrossRef Kosoresow, A.P., Hofmeyr, S.A.: Intrusion detection via system call traces. IEEE Softw. 14(5), 35–42 (1997)CrossRef
14.
go back to reference Kruegel, C., Valeur, F., Vigna, G.: Intrusion Detection and Correlation - Challenges and Solutions. Advances in Information Security. Springer, New York (2005) MATH Kruegel, C., Valeur, F., Vigna, G.: Intrusion Detection and Correlation - Challenges and Solutions. Advances in Information Security. Springer, New York (2005) MATH
15.
go back to reference Kumar, S., Spafford, E.H.: A pattern matching model for misuse intrusion detection. In: National Computer Security Conference (1994) Kumar, S., Spafford, E.H.: A pattern matching model for misuse intrusion detection. In: National Computer Security Conference (1994)
16.
go back to reference Lippmann, R., Haines, J.W., Fried, D.J., Korba, J., Das, K.: The 1999 DARPA off-line intrusion detection evaluation. Comp. Netw. 34(4), 579–595 (2000)CrossRef Lippmann, R., Haines, J.W., Fried, D.J., Korba, J., Das, K.: The 1999 DARPA off-line intrusion detection evaluation. Comp. Netw. 34(4), 579–595 (2000)CrossRef
17.
go back to reference Liu, J., Li, R., Liu, Y., Zhang, Z.: Multi-sensor data fusion based on correlation function and fuzzy integration function. Syst. Eng. Electron. 28(7), 1006–1009 (2006)MATH Liu, J., Li, R., Liu, Y., Zhang, Z.: Multi-sensor data fusion based on correlation function and fuzzy integration function. Syst. Eng. Electron. 28(7), 1006–1009 (2006)MATH
18.
go back to reference Mao, C.H., Pao, H.K., Faloutsos, C., Lee, H.M.: Sbad: Sequence based attack detection via sequence comparison. In: PSDML (2010) Mao, C.H., Pao, H.K., Faloutsos, C., Lee, H.M.: Sbad: Sequence based attack detection via sequence comparison. In: PSDML (2010)
19.
go back to reference Michael, C., Ghosh, A.: Using finite automata to mine execution data for intrusion detection: a preliminary report. In: Debar, H., Mé, L., Wu, S.F. (eds.) RAID 2000. LNCS, vol. 1907, p. 66. Springer, Heidelberg (2000) CrossRef Michael, C., Ghosh, A.: Using finite automata to mine execution data for intrusion detection: a preliminary report. In: Debar, H., Mé, L., Wu, S.F. (eds.) RAID 2000. LNCS, vol. 1907, p. 66. Springer, Heidelberg (2000) CrossRef
20.
go back to reference Molinaro, C., Moscato, V., Picariello, A., Pugliese, A., Rullo, A., Subrahmanian, V.S.: Padua: parallel architecture to detect unexplained activities. ACM Trans. Internet Techn. 14(1), 3 (2014)CrossRef Molinaro, C., Moscato, V., Picariello, A., Pugliese, A., Rullo, A., Subrahmanian, V.S.: Padua: parallel architecture to detect unexplained activities. ACM Trans. Internet Techn. 14(1), 3 (2014)CrossRef
21.
go back to reference Ning, P., Cui, Y., Reeves, D.S., Xu, D.: Techniques and tools for analyzing intrusion alerts. ACM Trans. Inf. Syst. Secur. 7(2), 274–318 (2004)CrossRef Ning, P., Cui, Y., Reeves, D.S., Xu, D.: Techniques and tools for analyzing intrusion alerts. ACM Trans. Inf. Syst. Secur. 7(2), 274–318 (2004)CrossRef
22.
go back to reference Ou, X., Govindavajhala, S., Appel, A.W.: Mulval: a logic-based network security analyzer. In: USENIX (2005) Ou, X., Govindavajhala, S., Appel, A.W.: Mulval: a logic-based network security analyzer. In: USENIX (2005)
23.
go back to reference Patcha, A., Park, J.M.: An overview of anomaly detection techniques: existing solutions and latest technological trends. Comp. Netw. 51(12), 3448–3470 (2007)CrossRef Patcha, A., Park, J.M.: An overview of anomaly detection techniques: existing solutions and latest technological trends. Comp. Netw. 51(12), 3448–3470 (2007)CrossRef
24.
go back to reference Paxson, V.: Bro: a system for detecting network intruders in real-time. Comp. Netw. 31(23–24), 2435–2463 (1999)CrossRef Paxson, V.: Bro: a system for detecting network intruders in real-time. Comp. Netw. 31(23–24), 2435–2463 (1999)CrossRef
25.
go back to reference Piciarelli, C., Micheloni, C., Foresti, G.L.: Trajectory-based anomalous event detection. IEEE Trans. Circuits Syst. Video Techn. 18(11), 1544–1554 (2008)CrossRef Piciarelli, C., Micheloni, C., Foresti, G.L.: Trajectory-based anomalous event detection. IEEE Trans. Circuits Syst. Video Techn. 18(11), 1544–1554 (2008)CrossRef
26.
go back to reference Ren, H., Stakhanova, N., Ghorbani, A.A.: An online adaptive approach to alert correlation. In: Kreibich, C., Jahnke, M. (eds.) DIMVA 2010. LNCS, vol. 6201, pp. 153–172. Springer, Heidelberg (2010) CrossRef Ren, H., Stakhanova, N., Ghorbani, A.A.: An online adaptive approach to alert correlation. In: Kreibich, C., Jahnke, M. (eds.) DIMVA 2010. LNCS, vol. 6201, pp. 153–172. Springer, Heidelberg (2010) CrossRef
27.
go back to reference Roesch, M.: Snort: Lightweight intrusion detection for networks. In: LISA (1999) Roesch, M.: Snort: Lightweight intrusion detection for networks. In: LISA (1999)
28.
go back to reference Roschke, S., Cheng, F., Meinel, C.: A new alert correlation algorithm based on attack graph. In: Herrero, Á., Corchado, E. (eds.) CISIS 2011. LNCS, vol. 6694, pp. 58–67. Springer, Heidelberg (2011) CrossRef Roschke, S., Cheng, F., Meinel, C.: A new alert correlation algorithm based on attack graph. In: Herrero, Á., Corchado, E. (eds.) CISIS 2011. LNCS, vol. 6694, pp. 58–67. Springer, Heidelberg (2011) CrossRef
29.
go back to reference Sadoddin, R., Ghorbani, A.: Alert correlation survey: framework and techniques. In: PST (2006) Sadoddin, R., Ghorbani, A.: Alert correlation survey: framework and techniques. In: PST (2006)
30.
go back to reference Sekar, R., Bendre, M., Dhurjati, D., Bollineni, P.: A fast automaton-based method for detecting anomalous program behaviors. In: S&P (2001) Sekar, R., Bendre, M., Dhurjati, D., Bollineni, P.: A fast automaton-based method for detecting anomalous program behaviors. In: S&P (2001)
31.
go back to reference Sheikhan, M., Jadidi, Z.: Misuse detection using hybrid of association rule mining and connectionist modeling. World Appl. Sci. J. 7, 31–37 (2009) Sheikhan, M., Jadidi, Z.: Misuse detection using hybrid of association rule mining and connectionist modeling. World Appl. Sci. J. 7, 31–37 (2009)
32.
go back to reference Shon, T., Moon, J.: A hybrid machine learning approach to network anomaly detection. Inf. Sci. 177(18), 3799–3821 (2007)CrossRef Shon, T., Moon, J.: A hybrid machine learning approach to network anomaly detection. Inf. Sci. 177(18), 3799–3821 (2007)CrossRef
33.
go back to reference Valdes, A., Skinner, K.: Probabilistic alert correlation. In: Lee, W., Mé, L., Wespi, A. (eds.) RAID 2001. LNCS, vol. 2212, p. 54. Springer, Heidelberg (2001) CrossRef Valdes, A., Skinner, K.: Probabilistic alert correlation. In: Lee, W., Mé, L., Wespi, A. (eds.) RAID 2001. LNCS, vol. 2212, p. 54. Springer, Heidelberg (2001) CrossRef
34.
go back to reference Valeur, F., Vigna, G., Krügel, C., Kemmerer, R.A.: A comprehensive approach to intrusion detection alert correlation. IEEE Trans. Dependable Sec. Comput. 1(3), 146–169 (2004)CrossRef Valeur, F., Vigna, G., Krügel, C., Kemmerer, R.A.: A comprehensive approach to intrusion detection alert correlation. IEEE Trans. Dependable Sec. Comput. 1(3), 146–169 (2004)CrossRef
35.
go back to reference Vigna, G., Kemmerer, R.A.: Netstat: A network-based intrusion detection system. J. Comput. Secur. 7(1), 37–71 (1999)CrossRef Vigna, G., Kemmerer, R.A.: Netstat: A network-based intrusion detection system. J. Comput. Secur. 7(1), 37–71 (1999)CrossRef
36.
go back to reference Wang, L., Liu, A., Jajodia, S.: Using attack graphs for correlating, hypothesizing, and predicting intrusion alerts. Comput. Commun. 29(15), 2917–2933 (2006)CrossRef Wang, L., Liu, A., Jajodia, S.: Using attack graphs for correlating, hypothesizing, and predicting intrusion alerts. Comput. Commun. 29(15), 2917–2933 (2006)CrossRef
Metadata
Title
The AC-Index: Fast Online Detection of Correlated Alerts
Authors
Andrea Pugliese
Antonino Rullo
Antonio Piccolo
Copyright Year
2015
DOI
https://doi.org/10.1007/978-3-319-24858-5_7

Premium Partner