Author Description

Real-time malware analysis requires processing large amounts of data storage to look for suspicious files. This is a time consuming process that (requires a large amount of processing power) often affecting other applications running on a personal computer. This research investigates the viability of using Graphic Processing Units (GPUs), present in many personal computers, to distribute the workload normally precessed by the standard Central Processing Unit (CPU). Three experiments are conducted using an industry standard GPU, the NVIDIA GeForce 9500 GT card. Experimental results show that a GPU can calculate a MD5 signature hash and scan a database of malicious signatures 82% faster then a CPU for files between 0 - 96 kB. If the file size is increased to 97 - 192 kB the GPU is 85% faster than the CPU. This demonstrates that the GPU can provide a greater performance increase over a CPU.These results could help achieve faster anti-malware products, faster network intrusion detection system response times, and faster firewall applications. This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work. This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work. As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made gen