Kniha Host-Based Multivariate Statistical Computer Operating Process Anomaly Intrusion Detection System Glen R Shilland

Host-Based Multivariate Statistical Computer Operating Process Anomaly Intrusion Detection System

Jazyk: Angličtina
Vazba: Brožovaná
Vydavatel: Biblioscholar
Dostupnost: Skladem u dodavatele
Odesíláme za 9-15 dnů
410
Most intrusion detection systems rely on signature matching of known malware or anomaly discriminati...

Informace o knize

Jazyk
Angličtina
Vazba
Kniha - Brožovaná
Vydáno
2012
Stránek
146
EAN
9781288417391
ISBN
9781288417391
Enbook ID
08251240
Vydavatel
Hmotnost
272
Rozměry
189 x 246 x 8

Kompletní popis

Most intrusion detection systems rely on signature matching of known malware or anomaly discrimination by data mining historical network traffic. This renders defended systems vulnerable to new or polymorphic code and deceptive attacks that do not trigger anomaly alarms. A lightweight, self-aware intrusion detection system (IDS) is essential for the security of government and commercial networks, especially mobile, ad-hoc networks (MANETs) with relatively limited processing power. This research proposes a host-based, anomaly discrimination IDS using operating system process parameters to measure the "health" of individual systems. Principal Component Analysis (PCA) is employed for feature set selection and dimensionality reduction, while Mahalanobis Distance (MD) and is used to classify legitimate and illegitimate activity. This combination of statistical methods provides an efficient computer operating process anomaly intrusion detection system (PAIDS) that maximizes detection rate and minimizes false positive rate, while updating its sense of "self" in near-real-time.

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