Visible to the public Biblio

Filters: Keyword is IPC  [Clear All Filters]
2021-01-28
Siddiquie, K., Shafqat, N., Masood, A., Abbas, H., Shahid, W. b.  2020.  Profiling Vulnerabilities Threatening Dual Persona in Android Framework. 2019 International Conference on Advances in the Emerging Computing Technologies (AECT). :1—6.

Enterprises round the globe have been searching for a way to securely empower AndroidTM devices for work but have spurned away from the Android platform due to ongoing fragmentation and security concerns. Discrepant vulnerabilities have been reported in Android smartphones since Android Lollipop release. Smartphones can be easily hacked by installing a malicious application, visiting an infectious browser, receiving a crafted MMS, interplaying with plug-ins, certificate forging, checksum collisions, inter-process communication (IPC) abuse and much more. To highlight this issue a manual analysis of Android vulnerabilities is performed, by using data available in National Vulnerability Database NVD and Android Vulnerability website. This paper includes the vulnerabilities that risked the dual persona support in Android 5 and above, till Dec 2017. In our security threat analysis, we have identified a comprehensive list of Android vulnerabilities, vulnerable Android versions, manufacturers, and information regarding complete and partial patches released. So far, there is no published research work that systematically presents all the vulnerabilities and vulnerability assessment for dual persona feature of Android's smartphone. The data provided in this paper will open ways to future research and present a better Android security model for dual persona.

2020-08-03
Si, Wen-Rong, Fu, Chen-Zhao, Gao, Kai, Zhang, Jia-Min, He, Lin, Bao, Hai-Long, Wu, Xin-Ye.  2019.  Research on a General Fast Analysis Algorithm Model for Pd Acoustic Detection System: The Algorithm Model Design and Its Application. 2019 International Conference on Smart Grid and Electrical Automation (ICSGEA). :22–26.
Nowadays, the detection of acoustical emission is widely used for fault diagnosis of gas insulated substations (GIS) in normal operation and factory tests, which is called 'non-conventional' method recommended in the standard IEC TS 62478-2016 and GIGRE D1.33 444. In this paper, to develop a data analyzer for acoustic detection (AD) system to make an assistant diagnosis for technical personnel or equipment operation and maintenance personnel, based on the previous research on the experimental research, pattern identification with phase compensation and the software development, the algorithm model design and its application is given in detail. For the acoustical emission signals (n, ti, qi), the BP artificial neural network optimized by genetic algorithm (GA-BP) is used as a classifier based on the fingerprint consisting of several statistic operators, which are derivate form typical 2D histograms of PRPD with identification with phase compensation (IPC). Experimental results show that the comprehensive algorithm model designed for identification is practical and effective.