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10 results for Impersonators

Study shows impersonators generate fake engagement on Instagram.

problem Impersonators exploit Instagram for fake engagement.
method Examined three communities (Politician, News agency, Sports star) on Instagram, collected data on 4.8K comments and 2.6K likes from 3.8K impersonators over 7 months.
result Impersonators generate significant fake engagement on verified accounts.

Personalized activity recognition improves performance for diverse users.

problem Poor performance of impersonal algorithms for individual users.
method Personalized activity recognition using deep embeddings from a fully convolutional neural network with triplet loss.
result Novel subject triplet loss provides the best performance overall.

Optimizes master faces for 2D and 3D face verification using evolutionary algorithms and neural networks.

problem Impersonation attacks using master faces for face-based identity authentication.
method Evolutionary algorithm in latent space of StyleGAN, neural network to direct search, 2D and 3D face reconstruction.
result Obtains high impersonation rates with fewer master faces for 2D and 3D face verification.

The paper introduces a US crime index to assess financial losses from property and cyber crimes.

problem Lack of indices evaluating crime's financial impact on investments.
method Developed an index-based insurance portfolio using FBI financial losses data.
result Real estate, ransomware, and government impersonation are major risk contributors.

Phishing as one of the most well-known cybercrime activities is a deception of online users to steal their personal or confidential information by impersonating a legitimate website. Several machine learning-based strategies have been proposed to detect phishing websites. These techniques are dependent on the features …

2019-03-13abs ↗pdf ↗