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Record Nr. |
UNINA9910376542703321 |
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Titolo |
AISec'15 : proceedings of the 8th ACM Workshop on Artificial Intelligence and Security : October 16, 2015, Denver, Colorado, USA / / Indrajit Ray [and five others], editors |
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Pubbl/distr/stampa |
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New York, NY : , : Association for Computing Machinery, , 2015 |
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ISBN |
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Descrizione fisica |
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1 online resource (104 pages) : illustrations |
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Collana |
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ACM international conference proceedings series |
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Disciplina |
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Soggetti |
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Artificial intelligence |
Computer security |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Sommario/riassunto |
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It is our great pleasure to welcome you to the 2015 ACM Workshop Artificial Intelligence and Security (AISec 2015) -- the eighth annual workshop addressing technologies that fuse intelligent systems into computer security applications and the implications of these approaches. The papers to be presented in this year's program span topics ranging from adversarial learning, detecting fake OSN accounts, malware classification to privacy preserving data processing and game theoretic techniques in adversarial learning. The workshop's aim is to advance research at the intersection of artificial intelligence, machine learning, privacy and security. In particular, AISec gives researchers and practitioners working within one or more of those fields a platform for interdisciplinary discussion, which would otherwise be lacking. Hopefully, the workshop will lead to a high degree of cross-pollination between groups working across these areas. We are delighted to again be co-located with the premier ACM Computer and Communication Security (CCS 2015) conference. This year we had 25 submissions from Asia, Europe and North America. After a rigorous reviewing process, involving at 2-3 referees per paper, 11 papers were accepted for presentation at the workshop, including presentation-only papers. Apart from the main program, there will also be a keynote speech by |
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Pratyusa Manadhata titled "Machine Learning for Enterprise Security". |
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