Accelerating Malware Detection via a Graphics Processing Unit, Nicholas S Kovach (9781025079950) — Readings Books
Accelerating Malware Detection via a Graphics Processing Unit
Hardback

Accelerating Malware Detection via a Graphics Processing Unit

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This title is printed to order. This book may have been self-published. If so, we cannot guarantee the quality of the content. In the main most books will have gone through the editing process however some may not. We therefore suggest that you be aware of this before ordering this book. If in doubt check either the author or publisher’s details as we are unable to accept any returns unless they are faulty. Please contact us if you have any questions.

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 generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.

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Format
Hardback
Publisher
Hutson Street Press
Date
22 May 2025
Pages
98
ISBN
9781025079950

This title is printed to order. This book may have been self-published. If so, we cannot guarantee the quality of the content. In the main most books will have gone through the editing process however some may not. We therefore suggest that you be aware of this before ordering this book. If in doubt check either the author or publisher’s details as we are unable to accept any returns unless they are faulty. Please contact us if you have any questions.

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 generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.

Read More
Format
Hardback
Publisher
Hutson Street Press
Date
22 May 2025
Pages
98
ISBN
9781025079950