2007
DOI: 10.1016/j.cose.2006.11.008
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Masquerade detection by boosting decision stumps using UNIX commands

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Cited by 10 publications
(4 citation statements)
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“…In a number of previous studies [6,12,13,[15][16][17] based on SEA data sets, Uniqueness, IPAM and other methods have been used for masquerade detection, and the performances of these methods have been investigated. In the present study, the results of these studies are directly compared with the detection accuracy of the N -Gram_STF-IDF method under the updated and non-updated conditions.…”
Section: Comparison Of Intrusion Detection Performance Between N -Gramentioning
confidence: 99%
See 1 more Smart Citation
“…In a number of previous studies [6,12,13,[15][16][17] based on SEA data sets, Uniqueness, IPAM and other methods have been used for masquerade detection, and the performances of these methods have been investigated. In the present study, the results of these studies are directly compared with the detection accuracy of the N -Gram_STF-IDF method under the updated and non-updated conditions.…”
Section: Comparison Of Intrusion Detection Performance Between N -Gramentioning
confidence: 99%
“…Accordingly, data mining methods have also been proposed for anomaly detection in sequential data. The Boosting Decision Stumps method [16]was further proposed in order to improve efficiency by filtering and assembling multiple rules based upon which to draw a final conclusion. The main advantage of data mining methods is that extracted patterns or rules can be interpreted by the security administrator.…”
Section: Related Researchmentioning
confidence: 99%
“…It also uses three parameters as input variables. The first variable is the selection threshold "θ", the second variable is a time period "tp" and the third variable is the sincerity/purity index [53]. Thus, a Dstump, statistical data continues until a limited period of time.…”
Section: Decision Stump (Dstump)mentioning
confidence: 99%
“…Jian et al . 22 propose a rule‐based approach, which compares n‐grams of command sequence using a technique known as boosting decision stumps (BDS). A compression‐ based classification algorithm called Normalized Compression Distance (NCD) is used by Bertacchini and Benitez 23 for masquerade detection.…”
Section: Masquerade Detection Approachesmentioning
confidence: 99%