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Security and Privacy Challenges in Cloud Computing Environments
TLDR
This article explores the roadblocks and solutions to providing a trustworthy cloud computing environment and suggests a number of approaches that could be considered.
CryptoDL: Deep Neural Networks over Encrypted Data
TLDR
New techniques to adopt deep neural networks within the practical limitation of current homomorphic encryption schemes are developed and show that CryptoDL provides efficient, accurate and scalable privacy-preserving predictions.
Towards active detection of identity clone attacks on online social networks
TLDR
A detection framework that is focused on discovering suspicious identities and then validating them and two approaches based on attribute similarity and similarity of friend networks are proposed.
SecureCloud: Towards a Comprehensive Security Framework for Cloud Computing Environments
TLDR
This paper proposes a comprehensive security framework for cloud computing environments and discusses challenges, existing solutions, approaches, and future work needed to provide a trustworthy cloud computing environment.
Deep Neural Networks Classification over Encrypted Data
TLDR
The issue of privacy preserving classification in a Machine Learning as a Service (MLaaS) settings and focus on convolutional neural networks (CNN) is addressed and new techniques to run CNNs over encrypted data are developed.
Privacy-preserving Machine Learning as a Service
TLDR
It is shown that it is feasible and practical to train neural networks using encrypted data and to make encrypted predictions, and also return the predictions in an encrypted form, and it is demonstrated that it provides accurate privacy-preserving training and classification.
StateMiner: an efficient similarity-based approach for optimal mining of role hierarchy
TLDR
This paper formally defines the problem of mining role hierarchy with minimal perturbation and presents StateMiner, a heuristic solution to find an RBAC state as similar as possible to both the existing state and the optimal state.
DCDIDP: A distributed, collaborative, and data-driven intrusion detection and prevention framework for cloud computing environments
TLDR
A distributed, Collaborative, and Data-driven Intrusion Detection and Prevention system (DCDIDP) to provide a holistic IDPS for all cloud service providers which collaborate with other peers in a distributed manner at different architectural levels to respond to attacks.
Inside the Mind of the Insider: Towards Insider Threat Detection Using Psychophysiological Signals
TLDR
The use of human bio-signals to detect the malicious activities and its applicability for insider threats detection are examined to show that human brain and heart signals can reveal valuable knowledge about the malicious behaviors and could be an effective solution for detecting insider threats.
Brain Computer Interface (BCI) Applications: Privacy Threats and Countermeasures
TLDR
First comprehensive analysis of BCI App stores including software development kits (SDKs), application programming interfaces (APIs), and BCI applications w.r.t privacy issues shows that most applications have unrestricted access to users' brainwave signals and can easily extract private information about their users without them even noticing.
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