Udam Saini

Computer Networks and Communications · 2008–2009

A researcher in the Science corpus: 4 papers; trusts 20 researchers and is trusted by 8 researchers here, as inferred from the citation graph.

Subfields

• Computer Networks and Communications — 35 citations into it; #8,377 of 9,886 by trust here, #3,523 by citations
• Signal Processing — 25 citations into it
• Artificial Intelligence — 24 citations into it; #30,357 of 35,345 by trust here, #17,110 by citations
• Safety, Robustness & Interpretability — 24 citations into it; #1,156 of 2,251 by trust here, #791 by citations
• Information Systems — 21 citations into it; #8,649 of 8,771 by trust here, #4,518 by citations
• Privacy & Security — 17 citations into it; #365 of 709 by trust here, #160 by citations
• Natural Language Processing — 11 citations into it

Whom Udam Saini trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Bryan Klimt
2. Tony Andrew Meyer
3. Gordon V. Cormack
4. Marco Barreno
5. Daniel Lowd
6. James Newsome
7. Yiming Yang
8. Brendon Whateley
9. Blaine Nelson
10. Michael Kearns

Who trusts Udam Saini overall

1. Octavian Suciu
2. Blaine Nelson
3. Radu Marginean
4. Battista Biggio
5. Yigitcan Kaya
6. Arturo Geigel
7. Hal Daumé Iii
8. Ling Huang

Papers from Udam Saini's perspective

Ordered by how strongly the researchers Udam Saini trusts endorse each paper. Same corpus, a different order for every researcher.

1. On Attacking Statistical Spam Filters
2. Adversarial classification
3. Adversarial learning
4. Spam Corpus Creation for TREC
5. Learning in the presence of malicious errors
6. Hamsa: fast signature generation for zero-day polymorphic worms with provable attack resilience
7. Polygraph: automatically generating signatures for polymorphic worms
8. Can machine learning be secure?
9. Paragraph: Thwarting Signature Learning by Training Maliciously
10. Prediction, learning, and games

Their papers

• Open problems in the security of learning (2008) — 44 citations
• Misleading Learners: Co-opting Your Spam Filter (2009) — 125 citations
• Machine Learning in the Presence of an Adversary: Attacking and Defending the SpamBayes Spam Filter (2008) — 12 citations
• Exploiting Machine Learning to Subvert Your Spam Filter (2008) — 397 citations