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Is a demonstration of the research project on fast large scale search, retrieval and classification of malware/goodware using techniques from signal processing and machine learning. Submit a Windows executable and retrieve the top similar matches. You may also search for existing or analysed malware using an executable's MD5 hash. Submit a Binary for Analysis. Win32 exe; 10MB max). This project is being supported by a grant from ONR. N00014-11-10111. We would also like to thank UCSB Seclab.

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Home - SARVAM | sarvam.ece.ucsb.edu Reviews

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Is a demonstration of the research project on fast large scale search, retrieval and classification of malware/goodware using techniques from signal processing and machine learning. Submit a Windows executable and retrieve the top similar matches. You may also search for existing or analysed malware using an executable's MD5 hash. Submit a Binary for Analysis. Win32 exe; 10MB max). This project is being supported by a grant from ONR. N00014-11-10111. We would also like to thank UCSB Seclab.

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Home - SARVAM | sarvam.ece.ucsb.edu Reviews

https://sarvam.ece.ucsb.edu

Is a demonstration of the research project on fast large scale search, retrieval and classification of malware/goodware using techniques from signal processing and machine learning. Submit a Windows executable and retrieve the top similar matches. You may also search for existing or analysed malware using an executable's MD5 hash. Submit a Binary for Analysis. Win32 exe; 10MB max). This project is being supported by a grant from ONR. N00014-11-10111. We would also like to thank UCSB Seclab.

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sarvam.ece.ucsb.edu

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About - SARVAM

http://sarvam.ece.ucsb.edu/about

Distribution of the Confidence of Uploaded Samples. SARVAM uses a simple yet effective method for visualizing and classifying malware using image processing techniques. Malware binaries are visualized as gray-scale images, with the observation that for many malware families, the images belonging to the same family appear very similar in layout and texture. Users can upload new binaries and obtain the top matches using signal processing algorithms. Example of similarity in Malware. Lakshmanan Nataraj, Vin...

2

Home - SARVAM

http://sarvam.ece.ucsb.edu/home

Is a demonstration of the research project on fast large scale search, retrieval and classification of malware/goodware using techniques from signal processing and machine learning. Submit a Windows executable and retrieve the top similar matches. You may also search for existing or analysed malware using an executable's MD5 hash. Submit a Binary for Analysis. Win32 exe; 10MB max). This project is being supported by a grant from ONR. N00014-11-10111. We would also like to thank UCSB Seclab.

3

Links - SARVAM

http://sarvam.ece.ucsb.edu/links

Offers a free service for scanning suspicious files using several antivirus engines. Other Malware Analysis Services. Allows you to analyze suspicious files and extract information on their process and network behavior while being executed. Is a tool for analyzing the behavior of Windows PE-executables with special focus on the analysis of malware. Software used by SARVAM. Is a DSL for quickly creating web applications in Ruby with minimal effort. Python Imaging Library (PIL). Contact: B.S Manjunath.

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mypacketstream.blogspot.com

Computer Malicious Adversaries: June 2012

http://mypacketstream.blogspot.com/2012_06_01_archive.html

A blog which records my journey on researching computer security issues. Wednesday, June 27, 2012. Malware Similarities Detection Via Visualization. A UCSB researcher has came up with an idea to detect the similarities of malware binaries by using visualization of malware. By comparing the pattern of the similarities, a research could save some time analyzing the a new malware by the existing, stored pattern. You can check the project and upload your sample here. Links to this post. Tuesday, June 19, 2012.

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sarvam.ece.ucsb.edu

Home - SARVAM

Is a demonstration of the research project on fast large scale search, retrieval and classification of malware/goodware using techniques from signal processing and machine learning. Submit a Windows executable and retrieve the top similar matches. You may also search for existing or analysed malware using an executable's MD5 hash. Submit a Binary for Analysis. Win32 exe; 10MB max). This project is being supported by a grant from ONR. N00014-11-10111. We would also like to thank UCSB Seclab.

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Skip to: page content. Links on this page. Sarvam Machines Automation and Robotic Technologies. A company in the business of design, manufacturing engineering, Product design and development, Process re-engineering and Automation. Customer need level or higher quality products and services. Reliable expertise at affordable prices. Feel Free to mail our Company on any queries and suggestions at mail@sarvam.net. 2014 Sarvam Machines Automation and Robotic Technologies.

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