hardware performance counters
Recently Published Documents


TOTAL DOCUMENTS

80
(FIVE YEARS 29)

H-INDEX

14
(FIVE YEARS 2)

2022 ◽  
Vol 14 (1) ◽  
pp. 24
Author(s):  
Hui Yan ◽  
Chaoyuan Cui

Cache side channel attacks, as a type of cryptanalysis, seriously threaten the security of the cryptosystem. These attacks continuously monitor the memory addresses associated with the victim’s secret information, which cause frequent memory access on these addresses. This paper proposes CacheHawkeye, which uses the frequent memory access characteristic of the attacker to detect attacks. CacheHawkeye monitors memory events by CPU hardware performance counters. We proved the effectiveness of CacheHawkeye on Flush+Reload and Flush+Flush attacks. In addition, we evaluated the accuracy of CacheHawkeye under different system loads. Experiments demonstrate that CacheHawkeye not only has good accuracy but can also adapt to various system loads.


2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Yingying Wen ◽  
Guanjie Cheng ◽  
Bo Lin ◽  
Jianwei Yin

Performance profiling for the system is necessary and has already been widely supported by hardware performance counters (HPC). HPC is based on the registers to count the number of events in a time interval and uses system interruption to read the number from registers to a recording file. The profiled result approximates the actual running states and is not accurate since the profiling technique uses sampling to capture the states. We do not know the actual running states before, which makes the validation on profiling results complex. Jianwei YinSome experiments-based analysis compared the running results of benchmarks running on different systems to improve the confidence of the profiling technique. But they have not explained why the sampling technique can represent the actual running states. We use the probability theory to prove that the expectation value of events profiled is an unbiased estimation of the actual states, and its variance is small enough. For knowing the actual running states, we design a simulation to generate the running states and get the profiled results. We refer to the applications running on production data centers to choose the parameters for our simulation settings. Comparing the actual running states and the profiled results shows they are similar, which proves our probability analysis is correct and improves our confidence in profiling accuracy.


2021 ◽  
Author(s):  
Juan-David Guerrero-Balaguera ◽  
Josie E. Rodriguez Condia ◽  
Matteo Sonza Reorda

2021 ◽  
Vol 20 (5s) ◽  
pp. 1-26
Author(s):  
Abraham Peedikayil Kuruvila ◽  
Anushree Mahapatra ◽  
Ramesh Karri ◽  
Kanad Basu

Micro-architectural footprints can be used to distinguish one application from another. Most modern processors feature hardware performance counters to monitor the various micro-architectural events when an application is executing. These ready-made hardware performance counters can be used to create program fingerprints and have been shown to successfully differentiate between individual applications. In this paper, we demonstrate how ready-made hardware performance counters, due to their coarse-grain nature (low sampling rate and bundling of similar events, e.g., number of instructions instead of number of add instructions), are insufficient to this end. This observation motivates exploration of tailor-made hardware performance counters to capture fine-grain characteristics of the programs. As a case study, we evaluate both ready-made and tailor-made hardware performance counters using post-quantum cryptographic key encapsulation mechanism implementations. Machine learning models trained on tailor-made hardwareperformance counter streams demonstrate that they can uniquely identify the behavior of every post-quantum cryptographic key encapsulation mechanism algorithm with at least 98.99% accuracy.


2021 ◽  
Author(s):  
Bhargav Achary Dandpati Kumar ◽  
Sai Chandra Teja R ◽  
Sparsh Mittal ◽  
Biswabandan Panda ◽  
C. Krishna Mohan

Author(s):  
Jiří Filipovič ◽  
Jana Hozzová ◽  
Amin Nezarat ◽  
Jaroslav Ol'ha ◽  
Filip Petrovič

Sign in / Sign up

Export Citation Format

Share Document