Personnaliser

OK

Network Intrusion Detection using Deep Learning - Kim, Kwangjo

Note : 0

0 avis
  • Soyez le premier à donner un avis

Vous en avez un à vendre ?

Vendez-le-vôtre

39,90 €

Occasion · Comme Neuf

  • Ou 9,98 € /mois

  • 2,00 € offerts
    LIVRAISON RAPIDE

    Ce vendeur propose la livraison entre 2 et 5 jours

    • Livraison : 3,99 €
    • Livré entre le 27 et le 30 avril
    Voir les modes de livraison

    gigaben63

    PRO Vendeur favori

    4,9/5 sur + de 1 000 ventes

    Livraison rapide, bien emballé, service client soigné.Pour tout renseignement complémentaire, n'hésitez pas à nous contacter.

    Publicité
     
    Vous avez choisi le retrait chez le vendeur à
    • Payez directement sur Rakuten (CB, PayPal, 4xCB...)
    • Récupérez le produit directement chez le vendeur
    • Rakuten vous rembourse en cas de problème

    Gratuit et sans engagement

    Félicitations !

    Nous sommes heureux de vous compter parmi nos membres du Club Rakuten !

    En savoir plus

    Retour

    Horaires

        Note :


        Avis sur Network Intrusion Detection Using Deep Learning de Kim, Kwangjo Format Broché  - Livre Technologie

        Note : 0 0 avis sur Network Intrusion Detection Using Deep Learning de Kim, Kwangjo Format Broché  - Livre Technologie

        Les avis publiés font l'objet d'un contrôle automatisé de Rakuten.


        Présentation Network Intrusion Detection Using Deep Learning de Kim, Kwangjo Format Broché

         - Livre Technologie

        Livre Technologie - Kim, Kwangjo - 30/09/2018 - Broché - Langue : Anglais

        . .

      • Auteur(s) : Kim, Kwangjo - Tanuwidjaja, Harry Chandra - Aminanto, Muhamad Erza
      • Editeur : Springer Singapore
      • Langue : Anglais
      • Parution : 30/09/2018
      • Format : Moyen, de 350g à 1kg
      • Nombre de pages : 100
      • Expédition : 166
      • Dimensions : 23.5 x 15.5 x 0.6
      • ISBN : 9811314438



      • Résumé :
        This book presents recent advances in intrusion detection systems (IDSs) using state-of-the-art deep learning methods. It also provides a systematic overview of classical machine learning and the latest developments in deep learning. In particular, it discusses deep learning applications in IDSs in different classes: generative, discriminative, and adversarial networks. Moreover, it compares various deep learning-based IDSs based on benchmarking datasets. The book also proposes two novel feature learning models: deep feature extraction and selection (D-FES) and fully unsupervised IDS. Further challenges and research directions are presented at the end of the book. Offering a comprehensive overview of deep learning-based IDS, the book is a valuable reerence resource for undergraduate and graduate students, as well as researchers and practitioners interested in deep learning and intrusion detection. Further, the comparison of various deep-learning applications helps readers gain a basic understanding of machine learning, and inspires applications in IDS and other related areas in cybersecurity....

        Biographie:
        Kwangjo Kim is a Fellow of the International Association for Cryptologic Research (IACR). He received B.Sc. and M.Sc. degrees in Electronic Engineering from Yonsei University, Seoul, Korea, in 1980 and 1983, respectively, and a Ph.D. from the Division of Electrical and Computer Engineering, Yokohama National University, Japan, in 1991. He was a Visiting Professor at the MIT and the UC at San Diego USA, in 2005 and the Khalifa University of Science, Technology and Research, Abu Dhabi, UAE, in 2012 and an Education Specialist at the Bandung Institute of Technology, Bandung, Indonesia, in 2013. He is currently a Full Professor at the School of Computing and Graduate School of Information Security, Korea Advanced Institute of Science and Technology, Daejeon, the Korean representative to IFIP TC-11 and the honorary President of the Korea Institute of Information Security and Cryptography (KIISC). His current research interests include the theory and practices of cryptology and information security. Prof. Kim served as a Board Member of the IACR from 2000 to 2004, Chairperson of the Asiacrypt Steering Committee from 2005 to 2008 and President of KIISC in 2009. He is also a member of IEICE, IEEE, ACM and KIISC. Muhamad Erza Aminanto received B.S. and M.S. degrees in Electrical Engineering from Bandung Institute of Technology (ITB), Indonesia in 2013 and 2014, respectively. He is pursuing his Ph.D in the School of Computing at Korea Advanced Institute of Science and Technology (KAIST), South Korea. His current research interests include machine-learning, intrusion detection systems and big data analytics. His recent work entitled Deep Abstraction and Weighted Feature Selection for Wi-Fi Impersonation Detection was published with Kwangjo Kim in IEEE Transactions of Information Forensics and Security (IF:4.332) in 2017. Harry Chandra Tanuwidajaja received B.S. and M.S. degrees in Electrical Engineering from the Bandung Institute of Technology (ITB), Indonesia in 2013 and 2015, respectively. He is pursuing his Ph.D in the School of Computing at the Korea Advanced Institute of Science and Technology (KAIST), South Korea. His current research interests include malware detection, machine-learning, and intrusion detection systems...

        Sommaire:
        Kwangjo Kim, received his B.Sc. and M.Sc. degrees in Electronic Engineering from Yonsei University, Seoul, Korea, in 1980 and 1983, respectively, and his Ph.D. degree from the Division of Electrical and Computer Engineering, Yokohama National University, Yokohama, Japan, in 1991. He was a Visiting Professor at the Massachusetts Institute of Technology, Cambridge, USA and the University of California at San Diego, La Jolla, USA, in 2005 and the Khalifa University of Science, Technology and Research, Abu Dhabi, UAE, in 2012. He was also an education specialist at the Bandung Institute of Technology, Indonesia, in 2013. He is currently a Professor at the Graduate School of Information Security, School of Computing, Korea Advanced Institute of Science and Technology (KAIST), and was the Korean representative to IFIP TC-11 and the honourable President of the Korea Institute of Information Security and Cryptology (KIISC). His current research interests include the theory of cryptology andinformation security and their applications. Prof. Kim served as a board member of the International Association for Cryptologic Research (IACR) from 2000 to 2004, the chairperson of the Asiacrypt Steering Committee from 2005 to 2008, and the president of KIISC in 2009. He is the first Korean Fellow of the IACR, a member of IEEEE, ACM and IEICE, and a member of the IACR Fellow Selection Committee. Moreover, he is the general chair of Asiacrypt2020 and PQCrypto2021 (including CHES2014). He serves as an editor-in-chief of the online journal Cryptography and an editor of the Journal of Mathematical Cryptology. Harry Chandra Tanuwidjaja, received his B.S. and M.S. degrees in Electrical Engineering from the Bandung Institute of Technology (ITB), Indonesia in 2013 and 2015, respectively, and his Ph.D. degree from School of Computing, Korea Advanced Institute of Science and Technology (KAIST), South Korea. His research interests include malware detection, machine-learning, privacy-preserving, and intrusion-detection systems. Currently, he is working as a fixed term researcher for Cybersecurity Laboratory, National Institute of Information and Communications Technology (NICT), Tokyo, Japan (starting from July 2021)....

        Détails de conformité du produit

        Consulter les détails de conformité de ce produit (

        Personne responsable dans l'UE

        )
        Le choixNeuf et occasion
        Minimum5% remboursés
        La sécuritéSatisfait ou remboursé
        Le service clientsÀ votre écoute
        LinkedinFacebookTwitterInstagramYoutubePinterestTiktok
        visavisa
        mastercardmastercard
        klarnaklarna
        paypalpaypal
        floafloa
        americanexpressamericanexpress
        Rakuten Logo
        • Rakuten Kobo
        • Rakuten TV
        • Rakuten Viber
        • Rakuten Viki
        • Plus de services
        • À propos de Rakuten
        Rakuten.com