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2019-03-18
Condé, R. C. R., Maziero, C. A., Will, N. C..  2018.  Using Intel SGX to Protect Authentication Credentials in an Untrusted Operating System. 2018 IEEE Symposium on Computers and Communications (ISCC). :00158–00163.
An important principle in computational security is to reduce the attack surface, by maintaining the Trusted Computing Base (TCB) small. Even so, no security technique ensures full protection against any adversary. Thus, sensitive applications should be designed with several layers of protection so that, even if a layer might be violated, sensitive content will not be compromised. In 2015, Intel released the Software Guard Extensions (SGX) technology in its processors. This mechanism allows applications to allocate enclaves, which are private memory regions that can hold code and data. Other applications and even privileged code, like the OS kernel and the BIOS, are not able to access enclaves' contents. This paper presents a novel password file protection scheme, which uses Intel SGX to protect authentication credentials in the PAM authentication framework, commonly used in UNIX systems. We defined and implemented an SGX-enabled version of the pam\_unix.so authentication module, called UniSGX. This module uses an SGX enclave to handle the credentials informed by the user and to check them against the password file. To add an extra security layer, the password file is stored using SGX sealing. A threat model was proposed to assess the security of the proposed solution. The obtained results show that the proposed solution is secure against the threat model considered, and that its performance overhead is acceptable from the user point of view. The scheme presented here is also suitable to other authentication frameworks.
2017-12-12
Chow, J., Li, X., Mountrouidou, X..  2017.  Raising flags: Detecting covert storage channels using relative entropy. 2017 IEEE International Conference on Intelligence and Security Informatics (ISI). :25–30.

This paper focuses on one type of Covert Storage Channel (CSC) that uses the 6-bit TCP flag header in TCP/IP network packets to transmit secret messages between accomplices. We use relative entropy to characterize the irregularity of network flows in comparison to normal traffic. A normal profile is created by the frequency distribution of TCP flags in regular traffic packets. In detection, the TCP flag frequency distribution of network traffic is computed for each unique IP pair. In order to evaluate the accuracy and efficiency of the proposed method, this study uses real regular traffic data sets as well as CSC messages using coding schemes under assumptions of both clear text, composed by a list of keywords common in Unix systems, and encrypted text. Moreover, smart accomplices may use only those TCP flags that are ever appearing in normal traffic. Then, in detection, the relative entropy can reveal the dissimilarity of a different frequency distribution from this normal profile. We have also used different data processing methods in detection: one method summarizes all the packets for a pair of IP addresses into one flow and the other uses a sliding moving window over such a flow to generate multiple frames of packets. The experimentation results, displayed by Receiver Operating Characteristic (ROC) curves, have shown that the method is promising to differentiate normal and CSC traffic packet streams. Furthermore the delay of raising an alert is analyzed for CSC messages to show its efficiency.