DOGANA | aDvanced sOcial enGineering And vulNerability Assesment Framework

Summary
"The advent of Social Networks has made both companies and public bodies tremendously exposed to the so-called Social Engineering 2.0, and thus prone to targeted cyber-attacks. Unfortunately, there is currently no solution available on the market that allows neither the comprehensive assessment of Social Vulnerabilities nor the management and reduction of the associated risk.
DOGANA aims to fill this gap by developing a framework that delivers ""aDvanced sOcial enGineering And vulNerability Assessment"". The underlying concept of DOGANA is that Social Vulnerabilities Assessments (SVAs), when regularly performed with the help of an efficient framework, help deploy effective mitigation strategies and lead to reducing the risk created by modern Social Engineering 2.0 attack techniques. Two relevant features of the proposed framework are: i) the presence of the ""awareness"" component within the framework as the cornerstone of the mitigation activities; ii) the legal compliance by design of the whole framework, that will be ensured by a partner and a work package explicitly devoted to this task. Moreover, the outcomes of the project are also expected to provide a solid basis to revise the insurance models for cyber-attacks related risks, thanks to the involvement of 2 strong DOGANA partners in this area of activity.
The project will be implemented by a consortium of 18 partners, from 11 different countries, including users, technology providers of whom 3 are major world-wide cyber-security solutions market leaders as well as legal and psychological expertise. An extensive field trial plan enables the testing of the DOGANA platform with six users (4 partners and 2 supporting users) operating in the critical areas of energy, finance, transport, utilities, and public authorities. DOGANA has also created a unique consortium with a world-wide scope.
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Web resources: https://cordis.europa.eu/project/id/653618
Start date: 01-09-2015
End date: 31-08-2018
Total budget - Public funding: 5 808 217,13 Euro - 4 599 806,00 Euro
Cordis data

Original description

"The advent of Social Networks has made both companies and public bodies tremendously exposed to the so-called Social Engineering 2.0, and thus prone to targeted cyber-attacks. Unfortunately, there is currently no solution available on the market that allows neither the comprehensive assessment of Social Vulnerabilities nor the management and reduction of the associated risk.
DOGANA aims to fill this gap by developing a framework that delivers ""aDvanced sOcial enGineering And vulNerability Assessment"". The underlying concept of DOGANA is that Social Vulnerabilities Assessments (SVAs), when regularly performed with the help of an efficient framework, help deploy effective mitigation strategies and lead to reducing the risk created by modern Social Engineering 2.0 attack techniques. Two relevant features of the proposed framework are: i) the presence of the ""awareness"" component within the framework as the cornerstone of the mitigation activities; ii) the legal compliance by design of the whole framework, that will be ensured by a partner and a work package explicitly devoted to this task. Moreover, the outcomes of the project are also expected to provide a solid basis to revise the insurance models for cyber-attacks related risks, thanks to the involvement of 2 strong DOGANA partners in this area of activity.
The project will be implemented by a consortium of 18 partners, from 11 different countries, including users, technology providers of whom 3 are major world-wide cyber-security solutions market leaders as well as legal and psychological expertise. An extensive field trial plan enables the testing of the DOGANA platform with six users (4 partners and 2 supporting users) operating in the critical areas of energy, finance, transport, utilities, and public authorities. DOGANA has also created a unique consortium with a world-wide scope.
"

Status

CLOSED

Call topic

DS-06-2014

Update Date

27-10-2022
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