Artificial intelligence design implementation di ali muhammad (3 risultati)
- Brossura
Da: preigu, Osnabrück, Germaniapreigu
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 43,35
EUR 70,00 spedizioneSpedito da Germania a U.S.A.Quantità: 5 disponibili
Taschenbuch. Condizione: Neu. Artificial Intelligence | Design and Implementation of Entropy Based Artificially Immune Malware Detection System | Muhammad Ali (u. a.) | Taschenbuch | 76 S. | Englisch | 2011 | LAP LAMBERT Academic Publishing | EAN 9783845429991 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengeriche…r Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
- Brossura
Da: Mispah books, Redhill, SURRE, Regno UnitoMispah books
Contatta il venditoreVenditore con 4 stelleCondizione: Nuovo
EUR 183,60
EUR 29,32 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 1 disponibili
paperback. Condizione: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.
- Brossura
- Print on Demand
Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 49,00
EUR 60,66 spedizioneSpedito da Germania a U.S.A.Quantità: 1 disponibili
Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Many Malware detection systems these days are using signature based techniques to detect malwares and viruses. The zero day or new infected files are not detected by these signature based Anti Viruses and their signature is generated on…ly after they have done their damage. Hence it becomes very important for a user to constantly update the antivirus software. To overcome these problems, we have proposed a solution based on Artificial Intelligence techniques. So the clients will not require frequent updates and probability of detecting zero day infections will rise abruptly. This project is based on implementing data mining algorithms mainly C4.5 Decision Tree learner. We have generated a dataset on the basis of already known malicious executable files. A C4.5 decision tree is generated based on the generated dataset and the unknown executables are passed through the tree to classify the executable as a malicious or a benign file. The purpose is to get rid of the manual signature based Malware detection systems that require constant updated signatures and making systems artificially immune to unknown and zero day malicious executables.
