Routine based OS-aware microprocessor resource adaptation for run-time operating system power saving

Author(s):  
Tao Li ◽  
L.K. John
2021 ◽  
Vol 54 (6) ◽  
pp. 1-36
Author(s):  
Shufan Fei ◽  
Zheng Yan ◽  
Wenxiu Ding ◽  
Haomeng Xie

Trusted Execution Environments (TEEs) have been widely used in many security-critical applications. The popularity of TEEs derives from its high security and trustworthiness supported by secure hardware. Intel Software Guard Extensions (SGX) is one of the most representative TEEs that creates an isolated environment on an untrusted operating system, thus providing run-time protection for the execution of security-critical code and data. However, Intel SGX is far from the acme of perfection. It has become a target of various attacks due to its security vulnerabilities. Researchers and practitioners have paid attention to the security vulnerabilities of SGX and investigated optimization solutions in real applications. Unfortunately, existing literature lacks a thorough review of security vulnerabilities of SGX and their countermeasures. In this article, we fill this gap. Specifically, we propose two sets of criteria for estimating security risks of existing attacks and evaluating defense effects brought by attack countermeasures. Furthermore, we propose a taxonomy of SGX security vulnerabilities and shed light on corresponding attack vectors. After that, we review published attacks and existing countermeasures, as well as evaluate them by employing our proposed criteria. At last, on the strength of our survey, we propose some open challenges and future directions in the research of SGX security.


2019 ◽  
Vol 10 (1) ◽  
pp. 1251-1257
Author(s):  
Abhinandan H Patil

Evolving multi-parameter, multi-configuration systems require regression test suite that can be customized. This is in terms of run time. Run time can be customized by generating the combinations using combinatorial techniques. For systems like Contiki operating system, the test cases need to be executed in its simulator Cooja. Executing test cases in a simulator requires functional test cases to be generated from the combinatorial parameter combinations obtained. In this work we present a methodology to generate the functional test cases. We present Functional Test Case Generator for Contiki and Cooja (FTCGCC), which is a tool developed using our methodology. We demonstrate use of our tool by generating customizable regression test suite for Contiki and Cooja using code coverage as criteria. FTCGCC is developed for the test case generation when target System Under Test is IoT operating system Contiki and its simulator Cooja.


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