Listar por autor "8002cbdf4d2bfb84463ca27cdf6192ac"

Mostrando ítems 1-7 de 7

    • Deobfuscating leetspeak with deep learning to improve spam filtering 

      Velez de Mendizabal, Iñaki; Vidriales Mazorriaga, Xabier; Ezpeleta, Iñigo; Zurutuza, Urko (UNIR - Universidad Internacional de La Rioja, 2023)
      The evolution of anti-spam filters has forced spammers to make greater efforts to bypass filters in order to distribute content over networks. The distribution of content encoded in images or the use of Leetspeak are ...

    • Dimensionality reduction for the improvement of anti-spam filters 

      Velez de Mendizabal, Iñaki (Mondragon Unibertsitatea. Goi Eskola Politeknikoa, 2022)
      Nowadays, spam represents more than 45% of the world’s email traffic. Filtering techniques to combat the problem of spam distribution have been the subject of many research studies in recent years. Several combinations of ...

    • Guardianes de la Galaxia: concienciación en Ciberseguridad 

      Fernández Arrieta, Miguel; Lizarraga Durandegui, Jesús María; Velez de Mendizabal, Iñaki; Rodriguez Ceberio, Antton; Zurutuza, Urko (Universidad de Sevilla, 2024)
      En este artículo se presenta una iniciativa de formación denominada “Guardianes de la Galaxia”, orientada a concienciar y formar a los participantes en la identificación, detección y prevención de ciberataques de tipo ...

    • A Mood Analysis on Youtube Comments and a Method for Improved Social Spam Detection 

      Ezpeleta, Enaitz; Iturbe, Mikel; Garitano, Iñaki; Velez de Mendizabal, Iñaki; Zurutuza, Urko (Springer, 2018)
      In the same manner that Online Social Networks (OSN) usage increases, non-legitimate campaigns over these types of web services are growing. This is the reason why signi cant number of users are affected by social spam ...

    • Multi-objective evolutionary optimization for dimensionality reduction of texts represented by synsets 

      Velez de Mendizabal, Iñaki; Ezpeleta, Enaitz; Zurutuza, Urko (PeerJ, 2023)
      Despite new developments in machine learning classification techniques, improving the accuracy of spam filtering is a difficult task due to linguistic phenomena that limit its effectiveness. In particular, we highlight ...

    • Novel email spam detection method using sentiment analysis and personality recognition 

      Velez de Mendizabal, Iñaki; Zurutuza, Urko; Ezpeleta, Enaitz (Oxford Academic, 2020)
      Unsolicited email campaigns remain as one of the biggest threats affecting millions of users per day. During the past years several techniques to detect unsolicited emails have been developed. This work provides means to ...

    • SDRS: A new lossless dimensionality reduction for text corpora 

      Velez de Mendizabal, Iñaki; Ezpeleta, Enaitz; Zurutuza, Urko (Elsevier Ltd., 2020)
      In recent years, most content-based spam filters have been implemented using Machine Learning (ML) approaches by means of token-based representations of textual contents. After introducing multiple performance enhancements, ...