Libros sobre el tema "Security of machine learning classifiers"

Learning kernel classifiers: Theory and algorithms. Cambridge, Mass: MIT Press, 2002.

Chen, Xiaofeng, Willy Susilo y Elisa Bertino, eds. Cyber Security Meets Machine Learning. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-6726-5.

Chen, Xiaofeng, Hongyang Yan, Qiben Yan y Xiangliang Zhang, eds. Machine Learning for Cyber Security. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-62223-7.

Chen, Xiaofeng, Hongyang Yan, Qiben Yan y Xiangliang Zhang, eds. Machine Learning for Cyber Security. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-62460-6.

Chen, Xiaofeng, Hongyang Yan, Qiben Yan y Xiangliang Zhang, eds. Machine Learning for Cyber Security. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-62463-7.

Chen, Xiaofeng, Xinyi Huang y Jun Zhang, eds. Machine Learning for Cyber Security. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-30619-9.

Xu, Yuan, Hongyang Yan, Huang Teng, Jun Cai y Jin Li, eds. Machine Learning for Cyber Security. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-20102-8.

Xu, Yuan, Hongyang Yan, Huang Teng, Jun Cai y Jin Li, eds. Machine Learning for Cyber Security. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-20096-0.

Xu, Yuan, Hongyang Yan, Huang Teng, Jun Cai y Jin Li, eds. Machine Learning for Cyber Security. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-20099-1.

Dolev, Shlomi, Oded Margalit, Benny Pinkas y Alexander Schwarzmann, eds. Cyber Security Cryptography and Machine Learning. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-78086-9.

Wang, Gang, Arridhana Ciptadi y Ali Ahmadzadeh, eds. Deployable Machine Learning for Security Defense. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-87839-9.

Halak, Basel, ed. Machine Learning for Embedded System Security. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-94178-9.

Dolev, Shlomi, Jonathan Katz y Amnon Meisels, eds. Cyber Security, Cryptology, and Machine Learning. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-07689-3.

Dinur, Itai, Shlomi Dolev y Sachin Lodha, eds. Cyber Security Cryptography and Machine Learning. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-94147-9.

Wang, Gang, Arridhana Ciptadi y Ali Ahmadzadeh, eds. Deployable Machine Learning for Security Defense. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-59621-7.

Dolev, Shlomi, Vladimir Kolesnikov, Sachin Lodha y Gera Weiss, eds. Cyber Security Cryptography and Machine Learning. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-49785-9.

Dolev, Shlomi y Sachin Lodha, eds. Cyber Security Cryptography and Machine Learning. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-60080-2.

Dolev, Shlomi, Danny Hendler, Sachin Lodha y Moti Yung, eds. Cyber Security Cryptography and Machine Learning. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-20951-3.

-P, Tsai Jeffrey J., ed. Intrusion detection: A machine learning approach. London: Imperial College Press, 2011.

Thomas, Tony, Athira P. Vijayaraghavan y Sabu Emmanuel. Machine Learning Approaches in Cyber Security Analytics. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-1706-8.

Krishna, P. Venkata, Sasikumar Gurumoorthy y Mohammad S. Obaidat. Social Network Forensics, Cyber Security, and Machine Learning. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-1456-8.

Maloof, Marcus A., ed. Machine Learning and Data Mining for Computer Security. London: Springer-Verlag, 2006. http://dx.doi.org/10.1007/1-84628-253-5.

Network anomaly detection: A machine learning perspective. Boca Raton: CRC Press, Taylor & Francis Group, 2014.

Tanwar, Sarvesh, Sumit Badotra y Ajay Rana. Machine Learning, Blockchain, and Cyber Security in Smart Environments. Boca Raton: Chapman and Hall/CRC, 2022. http://dx.doi.org/10.1201/9781003240310.

Bhattacharjee, Arup, Samir Kr Borgohain, Badal Soni, Gyanendra Verma y Xiao-Zhi Gao, eds. Machine Learning, Image Processing, Network Security and Data Sciences. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-6315-7.

Bhattacharjee, Arup, Samir Kr Borgohain, Badal Soni, Gyanendra Verma y Xiao-Zhi Gao, eds. Machine Learning, Image Processing, Network Security and Data Sciences. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-6318-8.

Mena, Jesus. Machine learning forensics for law enforcement, security, and intelligence. Boca Raton, FL: Taylor & Francis, 2011.

Doriya, Rajesh, Badal Soni, Anupam Shukla y Xiao-Zhi Gao, eds. Machine Learning, Image Processing, Network Security and Data Sciences. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-5868-7.

Khare, Nilay, Deepak Singh Tomar, Mitul Kumar Ahirwal, Vijay Bhaskar Semwal y Vaibhav Soni, eds. Machine Learning, Image Processing, Network Security and Data Sciences. Cham: Springer Nature Switzerland, 2022. http://dx.doi.org/10.1007/978-3-031-24352-3.

Khare, Nilay, Deepak Singh Tomar, Mitul Kumar Ahirwal, Vijay Bhaskar Semwal y Vaibhav Soni, eds. Machine Learning, Image Processing, Network Security and Data Sciences. Cham: Springer Nature Switzerland, 2022. http://dx.doi.org/10.1007/978-3-031-24367-7.

Yu, Philip S. Machine Learning in Cyber Trust: Security, Privacy, and Reliability. Boston, MA: Springer-Verlag US, 2009.

Lecuyer, Mathias. Security, Privacy, and Transparency Guarantees for Machine Learning Systems. [New York, N.Y.?]: [publisher not identified], 2019.

Shi, Kevin. Cryptographic approaches to security and optimization in machine learning. [New York, N.Y.?]: [publisher not identified], 2020.

Machine learning forensics for law enforcement, security, and intelligence. Boca Raton, FL: Taylor & Francis, 2011.

Herbrich, Ralf. Learning Kernel Classifiers: Theory and Algorithms. MIT Press, 2018.

Herbrich, Ralf. Learning Kernel Classifiers: Theory and Algorithms. MIT Press, 2022.

Herbrich, Ralf y Francis Bach. Learning Kernel Classifiers: Theory and Algorithms. MIT Press, 2001.

Herbrich, Ralf. Learning Kernel Classifiers: Theory and Algorithms (Adaptive Computation and Machine Learning). The MIT Press, 2001.

(Editor), Peter J. Bartlett, Bernhard Schölkopf (Editor), Dale Schuurmans (Editor) y Alex J. Smola (Editor), eds. Advances in Large-Margin Classifiers (Neural Information Processing). The MIT Press, 2000.

Mooney, Raymond J. Machine Learning. Editado por Ruslan Mitkov. Oxford University Press, 2012. http://dx.doi.org/10.1093/oxfordhb/9780199276349.013.0020.

Vidales, A. Machine Learning with Matlab. Supervised Learning: Knn Classifiers, Ensemble Learning, Random Forest, Boosting and Bagging. Independently Published, 2019.

Joseph, Anthony D., Blaine Nelson, J. D. Tygar y Benjamin I. P. Rubinstein. Adversarial Machine Learning. Cambridge University Press, 2019.

Joseph, Anthony D., Blaine Nelson, Benjamin I. P. Rubinstein y J. D. Tygar. Adversarial Machine Learning. Cambridge University Press, 2019.

Chen, Xiaofeng, Elisa Bertino y Willy Susilo. Cyber Security Meets Machine Learning. Springer Singapore Pte. Limited, 2021.

Chen, Xiaofeng, Elisa Bertino y Willy Susilo. Cyber Security Meets Machine Learning. Springer, 2022.

Nautiyal, Lata. Machine Learning for Cyber Security. de Gruyter GmbH, Walter, 2022.

Nautiyal, Lata. Machine Learning for Cyber Security. de Gruyter GmbH, Walter, 2022.

Halak, Basel. Machine Learning for Embedded System Security. Springer International Publishing AG, 2022.

AI, Machine Learning and Deep Learning: A Security Perspective. Taylor & Francis Group, 2023.

AI, Machine Learning and Deep Learning: A Security Perspective. Taylor & Francis Group, 2023.