|
Showing 1 - 6 of
6 matches in All Departments
A critical challenge in deep learning is the vulnerability of deep
learning networks to security attacks from intelligent cyber
adversaries. Even innocuous perturbations to the training data can
be used to manipulate the behaviour of deep networks in unintended
ways. In this book, we review the latest developments in
adversarial attack technologies in computer vision; natural
language processing; and cybersecurity with regard to
multidimensional, textual and image data, sequence data, and
temporal data. In turn, we assess the robustness properties of deep
learning networks to produce a taxonomy of adversarial examples
that characterises the security of learning systems using game
theoretical adversarial deep learning algorithms. The
state-of-the-art in adversarial perturbation-based privacy
protection mechanisms is also reviewed. We propose new adversary
types for game theoretical objectives in non-stationary
computational learning environments. Proper quantification of the
hypothesis set in the decision problems of our research leads to
various functional problems, oracular problems, sampling tasks, and
optimization problems. We also address the defence mechanisms
currently available for deep learning models deployed in real-world
environments. The learning theories used in these defence
mechanisms concern data representations, feature manipulations,
misclassifications costs, sensitivity landscapes, distributional
robustness, and complexity classes of the adversarial deep learning
algorithms and their applications. In closing, we propose future
research directions in adversarial deep learning applications for
resilient learning system design and review formalized learning
assumptions concerning the attack surfaces and robustness
characteristics of artificial intelligence applications so as to
deconstruct the contemporary adversarial deep learning designs.
Given its scope, the book will be of interest to Adversarial
Machine Learning practitioners and Adversarial Artificial
Intelligence researchers whose work involves the design and
application of Adversarial Deep Learning.
|
You may like...
Merry Christmas
Mariah Carey, Walter Afanasieff, …
CD
R118
R58
Discovery Miles 580
|