DocumentCode :
182020
Title :
Performance Measures of Behavior-Based Signatures: An Anti-malware Solution for Platforms with Limited Computing Resource
Author :
Hughes, Kit ; Yanzhen Qu
Author_Institution :
Colorado Tech. Univ., Colorado Springs, CO, USA
fYear :
2014
fDate :
8-12 Sept. 2014
Firstpage :
303
Lastpage :
309
Abstract :
The signature-based malware-detection method is the most popular one used in anti-malware software. However, given advanced malware capabilities, the database of traditional signature-based antimalware software is becoming bloated to support identification of every variant. The increase in signatures slows the detection process and, in some cases, exceeds the resource availability of the platforms that need it most. With the expansion of the smaller platforms with limited computing resources, such as some mobile devices and various types of sensor networks, including Internet-of-Things (IoT), anti-malware´s capability needs to be refined to support these platforms. Behavior-based signatures might provide that much-needed reduction in the number of signatures found in a signature set while retaining the full spectrum of malware variants.
Keywords :
Internet of Things; digital signatures; invasive software; Internet-of-Things; behavior-based signatures; limited computing resources; mobile devices; performance measures; sensor networks; signature-based antimalware software; signature-based malware-detection method; Analytical models; Databases; Equations; Malware; Mathematical model; Software; Telecommunication traffic; anti-malware; behavior-based signatures; speed comparisons;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Availability, Reliability and Security (ARES), 2014 Ninth International Conference on
Conference_Location :
Fribourg
Type :
conf
DOI :
10.1109/ARES.2014.47
Filename :
6980296
Link To Document :
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