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Resurrecting Anti-Malware Through Collaboration.

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Titel: Resurrecting Anti-Malware Through Collaboration.
Autoren: Corregedor, Manuel, Solms, Sebastiaan Von
Quelle: Proceedings of the European Conference on e-Learning (ECEL); 2015, p337-345, 9p
Schlagwörter: ANTI-malware (Computer software), MALWARE, SOCIAL networks, VIRTUAL machine systems, COMPUTER operating systems
Abstract: A number of reports indicate that malware infection rates continue to increase, additionally, the reports also indicate that malware is becoming increasingly advanced. The spread of malware has grown to such an extent that a number of security experts have declared that anti-virus is dead. We propose an architecture called Collab-AV that can be used to address the anti-malware product vulnerabilities. The Collab-AV architecture is based on the principle of collaboration between different sources of information and different existing anti-malware vendors thus following a "strength in numbers" philosophy. The Collab-AV architecture is essentially divided into three layers as follows: Collab-AV Remote Layer: Represents all the components of Collab-AV that exist outside of the users' environment i.e. external to the user's computer. This layer is responsible for providing Collab-AV with actionable threat intelligence by gathering and utilising information gathered from the following sources: malware hash registries, benign software hash registries, threat information sources and trusted Collab-AV Peers. Collab-AV Local Layer: Contains the most important sub-systems of Collab-AV that execute on the user's computer. The sub-systems are collectively responsible for ensuring that the user is protected from malware infections by utilising the information gathered from the Collab-AV Remote layer and information gathered from the user's computer. Collab-AV Evaluation Layer: The purpose of this layer is to evaluate Collab-AV by continuously testing it for new vulnerabilities. The objectives of this layer can be achieved by using the evaluation framework we defined in our previous work or by integrating evaluations by third parties such as AV-Comparatives. The outputs of the evaluations will be used to guide future improvements on Collab-AV. The Collab-AV architecture has been designed to work with existing anti-malware products as opposed to replacing them while ensuring increased detection rates, trust, scalability and privacy. [ABSTRACT FROM AUTHOR]
Copyright of Proceedings of the European Conference on e-Learning (ECEL) is the property of Academic Conferences and Publishing International Ltd. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Resurrecting Anti-Malware Through Collaboration.
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  Data: Proceedings of the European Conference on e-Learning (ECEL); 2015, p337-345, 9p
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  Data: <searchLink fieldCode="DE" term="%22ANTI-malware+%28Computer+software%29%22">ANTI-malware (Computer software)</searchLink><br /><searchLink fieldCode="DE" term="%22MALWARE%22">MALWARE</searchLink><br /><searchLink fieldCode="DE" term="%22SOCIAL+networks%22">SOCIAL networks</searchLink><br /><searchLink fieldCode="DE" term="%22VIRTUAL+machine+systems%22">VIRTUAL machine systems</searchLink><br /><searchLink fieldCode="DE" term="%22COMPUTER+operating+systems%22">COMPUTER operating systems</searchLink>
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  Data: A number of reports indicate that malware infection rates continue to increase, additionally, the reports also indicate that malware is becoming increasingly advanced. The spread of malware has grown to such an extent that a number of security experts have declared that anti-virus is dead. We propose an architecture called Collab-AV that can be used to address the anti-malware product vulnerabilities. The Collab-AV architecture is based on the principle of collaboration between different sources of information and different existing anti-malware vendors thus following a "strength in numbers" philosophy. The Collab-AV architecture is essentially divided into three layers as follows: Collab-AV Remote Layer: Represents all the components of Collab-AV that exist outside of the users' environment i.e. external to the user's computer. This layer is responsible for providing Collab-AV with actionable threat intelligence by gathering and utilising information gathered from the following sources: malware hash registries, benign software hash registries, threat information sources and trusted Collab-AV Peers. Collab-AV Local Layer: Contains the most important sub-systems of Collab-AV that execute on the user's computer. The sub-systems are collectively responsible for ensuring that the user is protected from malware infections by utilising the information gathered from the Collab-AV Remote layer and information gathered from the user's computer. Collab-AV Evaluation Layer: The purpose of this layer is to evaluate Collab-AV by continuously testing it for new vulnerabilities. The objectives of this layer can be achieved by using the evaluation framework we defined in our previous work or by integrating evaluations by third parties such as AV-Comparatives. The outputs of the evaluations will be used to guide future improvements on Collab-AV. The Collab-AV architecture has been designed to work with existing anti-malware products as opposed to replacing them while ensuring increased detection rates, trust, scalability and privacy. [ABSTRACT FROM AUTHOR]
– Name: Abstract
  Label:
  Group: Ab
  Data: <i>Copyright of Proceedings of the European Conference on e-Learning (ECEL) is the property of Academic Conferences and Publishing International Ltd. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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      – Code: eng
        Text: English
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      Pagination:
        PageCount: 9
        StartPage: 337
    Subjects:
      – SubjectFull: ANTI-malware (Computer software)
        Type: general
      – SubjectFull: MALWARE
        Type: general
      – SubjectFull: SOCIAL networks
        Type: general
      – SubjectFull: VIRTUAL machine systems
        Type: general
      – SubjectFull: COMPUTER operating systems
        Type: general
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      – TitleFull: Resurrecting Anti-Malware Through Collaboration.
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            NameFull: Corregedor, Manuel
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            NameFull: Solms, Sebastiaan Von
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            – D: 01
              M: 01
              Text: 2015
              Type: published
              Y: 2015
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            – TitleFull: Proceedings of the European Conference on e-Learning (ECEL)
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