[SPARTA - bodies.dissemination-committee] Submission

Hello, We have submitted a paper on “Optimized Parameter Search Approach For Weight Modification Attack Targeting Deep Learning Models” to Applied Sciences journal. If it is accepted we will acknowledge the SPARTA project. Please see its abstract below. Best wishes, Xabi Title: Optimized Parameter Search Approach For Weight Modification Attack Targeting Deep Learning Models Authors: Xabier Echeberria-Barrio, Amaia Gil-Lerchundi, Raul Orduna-Urrutia, Iñigo Mendialdua Abstract. Deep Neural Network models have been developed in different fields bringing many advances in several tasks. However, they have also started to be incorporated into tasks with critical risk. That worries researchers who have been interested in studying possible attacks on these models, discovering a long list of threats from which every model should be defended. The weights modification attack is presented and discussed among researchers who have presented several versions and analyses about such a threat. It focuses on detecting the vulnerable weight to modify them, misclassifying the desired input data. Therefore, analyzing the different approaches of this attack can help to understand more precisely how to defend such vulnerabilities. In this work, a new version of the weight modification attack is presented. That approach is based on three processes: input data clusterization, weight selection, and the modification of the weights. The data clusterization allows attacking the model more precisely. The weight selection uses the gradient given by the input data to know the desired parameters. The modification is incorporated little by little via reduced noise. -- <https://www.vicomtech.org/> Xabier Etxeberria Barrio Researcher | Investigador xetxeberria(a)vicomtech.org +[34] 943 30 92 30 Digital Security | Seguridad digital <https://www.linkedin.com/company/vicomtech> <https://www.youtube.com/user/VICOMTech> <https://twitter.com/@Vicomtech> member of: <https://graphicsvision.ai/> La información que contiene este mensaje y sus adjuntos son confidenciales y están dirigidos exclusivamente a sus destinatarios. Si recibe este mensaje por error, se ruega nos lo comunique y proceda a su borrado. The information contained in this electronic message is intended only for the personal and confidential use of the recipients designated in the original message. If you have received this communication in error, please notify us immediately by replying to the message and deleting it from your computer.