Главная
Study mode:
on
1
Intro
2
Traditional Computing Systems
3
Modern Computing Systems Heterogeneous
4
Microarchitectural Attacks: Co-location
5
An Example: Side channel on Cache (Prime+Probe Attack)
6
GPUs are everywhere!
7
CPU vs. GPU
8
GPU Architecture
9
GPU Programming Model: CUDA
10
Covert Channel on GPUs?
11
Graphics/CUDA-Graphics Attack Overview
12
Attack1: Website Fingerprinting
13
GPU Memory Allocation Trace
14
Attack 2: Inter-keystroke timing
15
Security Issue
16
Temporal Partitioning
17
Spatial Partitioning
18
GPUGuard: Enable Intra-SM Sharing Securely
19
Integrated GPUs vs. Discrete GPUs
20
Security of Integrated CPU-GPU systems
21
Intel Integrated CPU-GPU
22
Main Challenges
23
Cache based covert channel
24
Remote Cross-Component Attacks
25
Defenses
26
Security of Heterogeneous Systems
27
Conclusion
Description:
Explore the security challenges of heterogeneous computing systems in this 38-minute lecture by Hoda Naghibijouybari, Assistant Professor in the Department of Computer Science at Binghamton University. Delve into the evolution from traditional to modern heterogeneous systems, focusing on microarchitectural attacks and side-channel vulnerabilities. Examine GPU architecture, the CUDA programming model, and specific security threats like website fingerprinting and inter-keystroke timing attacks. Learn about defense mechanisms, including temporal and spatial partitioning, and the GPUGuard solution. Compare integrated and discrete GPUs, analyzing their unique security implications. Gain insights into the complexities of securing CPU-GPU systems, remote cross-component attacks, and potential defense strategies for heterogeneous computing environments.

Security of Heterogeneous Systems

CAE in Cybersecurity Community
Add to list