Catálogo de publicaciones - libros
Matematica e Cultura
Michele Emmer (eds.)
Resumen/Descripción – provisto por la editorial
No disponible.
Palabras clave – provistas por la editorial
No disponibles.
Disponibilidad
| Institución detectada | Año de publicación | Navegá | Descargá | Solicitá |
|---|---|---|---|---|
| No detectada | 2006 | SpringerLink |
Información
Tipo de recurso:
libros
ISBN impreso
978-88-470-0464-1
ISBN electrónico
978-88-470-0465-8
Editor responsable
Springer Nature
País de edición
Reino Unido
Fecha de publicación
2006
Información sobre derechos de publicación
© Springer-Verlag Italia 2006
Cobertura temática
Tabla de contenidos
Per Mario Merz
Jannis Kounellis
Short sequences of system calls have been proven to be a good signature description for anomalous intrusion detection. The signature provides clear separation between different kinds of programs. This paper extends these works by applying fuzzy neural network (FNN) to solve the sharp boundary problem and decide whether a sequence is “normal” or “abnormal”. By using threat level of system calls to label the sequences the proposed FNN improves the accuracy of anomaly detection.
- omaggio a Mario Merz | Pp. 3-4
L’Eclissi
Manuela Gandini
Short sequences of system calls have been proven to be a good signature description for anomalous intrusion detection. The signature provides clear separation between different kinds of programs. This paper extends these works by applying fuzzy neural network (FNN) to solve the sharp boundary problem and decide whether a sequence is “normal” or “abnormal”. By using threat level of system calls to label the sequences the proposed FNN improves the accuracy of anomaly detection.
- omaggio a Mario Merz | Pp. 5-5
Merz e Fibonacci, proliferazioni vitali tra matematica e arte contemporanea
Giovanni Maria Accame
Short sequences of system calls have been proven to be a good signature description for anomalous intrusion detection. The signature provides clear separation between different kinds of programs. This paper extends these works by applying fuzzy neural network (FNN) to solve the sharp boundary problem and decide whether a sequence is “normal” or “abnormal”. By using threat level of system calls to label the sequences the proposed FNN improves the accuracy of anomaly detection.
- omaggio a Mario Merz | Pp. 7-14
Il cinema secondo Fibonacci
Davide Ferrario
Short sequences of system calls have been proven to be a good signature description for anomalous intrusion detection. The signature provides clear separation between different kinds of programs. This paper extends these works by applying fuzzy neural network (FNN) to solve the sharp boundary problem and decide whether a sequence is “normal” or “abnormal”. By using threat level of system calls to label the sequences the proposed FNN improves the accuracy of anomaly detection.
- omaggio a Mario Merz | Pp. 15-20
PDEs, Images and Videotapes
Maurizio Falcone
Short sequences of system calls have been proven to be a good signature description for anomalous intrusion detection. The signature provides clear separation between different kinds of programs. This paper extends these works by applying fuzzy neural network (FNN) to solve the sharp boundary problem and decide whether a sequence is “normal” or “abnormal”. By using threat level of system calls to label the sequences the proposed FNN improves the accuracy of anomaly detection.
- matematica e immagini | Pp. 23-34
Matematica in volo con Solar Impulse
Alfio Quarteroni; Gilles Fourestey; Nicola Parolini; Christophe Prud’homme; Gianluigi Rozza
Short sequences of system calls have been proven to be a good signature description for anomalous intrusion detection. The signature provides clear separation between different kinds of programs. This paper extends these works by applying fuzzy neural network (FNN) to solve the sharp boundary problem and decide whether a sequence is “normal” or “abnormal”. By using threat level of system calls to label the sequences the proposed FNN improves the accuracy of anomaly detection.
- matematica e immagini | Pp. 35-48
Il gioco delle coppie
Marco Li Calzi; M. Cristina Molinari
Short sequences of system calls have been proven to be a good signature description for anomalous intrusion detection. The signature provides clear separation between different kinds of programs. This paper extends these works by applying fuzzy neural network (FNN) to solve the sharp boundary problem and decide whether a sequence is “normal” or “abnormal”. By using threat level of system calls to label the sequences the proposed FNN improves the accuracy of anomaly detection.
- matematica e felicità | Pp. 51-58
Una matematica per la psicanalisi. L’intuizionismo di Brouwer da Cartesio a Lacan
Antonello Sciacchitano
Short sequences of system calls have been proven to be a good signature description for anomalous intrusion detection. The signature provides clear separation between different kinds of programs. This paper extends these works by applying fuzzy neural network (FNN) to solve the sharp boundary problem and decide whether a sequence is “normal” or “abnormal”. By using threat level of system calls to label the sequences the proposed FNN improves the accuracy of anomaly detection.
- matematica e psicanalisi | Pp. 61-69
Motori di Ricerca Web e specchi della Società
Massimo Marchiori
Short sequences of system calls have been proven to be a good signature description for anomalous intrusion detection. The signature provides clear separation between different kinds of programs. This paper extends these works by applying fuzzy neural network (FNN) to solve the sharp boundary problem and decide whether a sequence is “normal” or “abnormal”. By using threat level of system calls to label the sequences the proposed FNN improves the accuracy of anomaly detection.
- matematica e applicazioni | Pp. 73-82
Matematica e cellule: brevi racconti tra chemiotassi, neuroni e qualche divagazione
Giovanni Naldi
Short sequences of system calls have been proven to be a good signature description for anomalous intrusion detection. The signature provides clear separation between different kinds of programs. This paper extends these works by applying fuzzy neural network (FNN) to solve the sharp boundary problem and decide whether a sequence is “normal” or “abnormal”. By using threat level of system calls to label the sequences the proposed FNN improves the accuracy of anomaly detection.
- matematica e applicazioni | Pp. 83-97