MHIDCA: MULTI LEVEL HYBRID INTRUSION DETECTION AND CONTINUOUS AUTHENTICATION FOR MANET SECURITY

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

MIRZAGHOLI SOHEILA; FAEZ KARIM

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: JOURNAL OF COMPUTER AND ROBOTICS Year:2016 | Volume:9 | Issue:1 Page(s): 1-11

Download Full-Text

View:

398

Download:

166

Cites:

Information Journal Paper

Title

MHIDCA: MULTI LEVEL HYBRID INTRUSION DETECTION AND CONTINUOUS AUTHENTICATION FOR MANET SECURITY

Author(s)

MIRZAGHOLI SOHEILA | FAEZ KARIM | Issue Writer Certificate

Keywords

SECURITY

MOBILE AD-HOC NETWORKS

AUTHENTICATION

INTRUSION DETECTION

HIDDEN MARKOV MODEL

Abstract

Mobile ad-hoc networks have attracted a great deal of attentions over the past few years. Considering their applications, the SECURITY issue has a great significance in them. SECURITY scheme utilization that includes prevention and detection has the worth of consideration. In this paper, a method is presented that includes a multi-level SECURITY scheme to identify intrusion by sensors and authenticates using biosensors. Optimizing AUTHENTICATION and INTRUSION DETECTION combination, we formulate the problem as a partially observable distributed stochastic system. In order to reduce the computation time, the parallel forward algorithm of HIDDEN MARKOV MODEL has been used. Due to the possibility of misdetection of the sensor and in order to increase the accuracy of observations, more than one sensor is selected in every step, the observations obtained from the sensors are combined for more accurate identification, and the system decides about the SECURITY status based on combined observations of the sensors. Bayesian theory has been used in sensors evidence fusion brought by increased accuracy and network SECURITY, which will be observed in the simulations. The use of this theory causes the increase of accuracy and SECURITY on networks.

Multimedia

No record.

Cites

No record.

References

Cite

APA: Copy

MIRZAGHOLI, SOHEILA, & FAEZ, KARIM. (2016). MHIDCA: MULTI LEVEL HYBRID INTRUSION DETECTION AND CONTINUOUS AUTHENTICATION FOR MANET SECURITY. JOURNAL OF COMPUTER AND ROBOTICS, 9(1), 1-11. SID. https://sid.ir/paper/698308/en

Vancouver: Copy

MIRZAGHOLI SOHEILA, FAEZ KARIM. MHIDCA: MULTI LEVEL HYBRID INTRUSION DETECTION AND CONTINUOUS AUTHENTICATION FOR MANET SECURITY. JOURNAL OF COMPUTER AND ROBOTICS[Internet]. 2016;9(1):1-11. Available from: https://sid.ir/paper/698308/en

IEEE: Copy

SOHEILA MIRZAGHOLI, and KARIM FAEZ, “MHIDCA: MULTI LEVEL HYBRID INTRUSION DETECTION AND CONTINUOUS AUTHENTICATION FOR MANET SECURITY,” JOURNAL OF COMPUTER AND ROBOTICS, vol. 9, no. 1, pp. 1–11, 2016, [Online]. Available: https://sid.ir/paper/698308/en

Related Journal Papers

No record.

Related Seminar Papers

No record.

Related Plans

No record.

Recommended Workshops