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Stack canaries remain a widely deployed defense against memory corruption attacks. Despite their practical usefulness, canaries are vulnerable to memory disclosure and brute-forcing attacks. We propose PCan, a new approach based on ARMv8.3-A pointer authentication (PA), that uses dynamically-generated canaries to mitigate these weaknesses and show that it provides more fine-grained protection with minimal performance overhead.
A popular run-time attack technique is to compromise the control-flow integrity of a program by modifying function return addresses on the stack. So far, shadow stacks have proven to be essential for comprehensively preventing return address manipula
Machine learning (ML) applications are increasingly prevalent. Protecting the confidentiality of ML models becomes paramount for two reasons: (a) a model can be a business advantage to its owner, and (b) an adversary may use a stolen model to find tr
Our behavior (the way we talk, walk, or think) is unique and can be used as a biometric trait. It also correlates with sensitive attributes like emotions. Hence, techniques to protect individuals privacy against unwanted inferences are required. To c
Recently, a number of existing blockchain systems have witnessed major bugs and vulnerabilities within smart contracts. Although the literature features a number of proposals for securing smart contracts, these proposals mostly focus on proving the c
Ever since Machine Learning as a Service (MLaaS) emerges as a viable business that utilizes deep learning models to generate lucrative revenue, Intellectual Property Right (IPR) has become a major concern because these deep learning models can easily