Allure Security Unveils Industry's First Data Loss Detection and ...
www.businesswire.com
Allure Security was founded in a Columbia University research labs by Dr. Salvatore Stolfo and Dr. Angelos Keromytis, two renowned security ...
Salvatore J. Stolfo | Columbia Engineering
www.engineering.columbia.edu
Stolfo is regarded as creating the area of machine learning applied to intrusion detection and has created several anomaly-detection algorithms and systems addressing some of the hardest problems in securing computer systems.
AI Approaches to Fraud Detection and Risk Management
www.aaai.org
AAAI advances the understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines.
Foundations of Security: What Every Programmer Needs to Know
books.google.de
Lee, Wenke, Salvatore Stolfo, and Phil Chan Learning patterns from Unix process execution traces for intrusion detection. In Proceedings of the AAAI
Controls, Automation of Communication Systems (ICCACS2004) - Google...
books.google.de
[4] Back Officer Friendly. WWW.NFR.COM/RESOURCE/BACKOCER.PHP. [5] Wenke Lee and Salvatore Stolfo. Data mining approaches for intrusion detection.
Recent Advances in Intrusion Detection: 5th International Symposium,...
books.google.de
Andrew Honig, Andrew Howard, Eleazar Eskin, and Salvatore Stolfo. Adaptive model generation: An architecture for the deployment of data minig-based ...
[ ] Unsupervised Anomaly-based Malware Detection using...
arxiv.org
Authors: Adrian Tang, Simha Sethumadhavan, Salvatore Stolfo. (Submitted on 7 Mar (v1), last revised 28 Mar (this version, v2)). Abstract: Recent ...
Segmentation and Automated Social Hierarchy Detection ...
papers.ssrn.com
Creamer, Germán G. and Rowe, Ryan and hershkop, shlomo and Stolfo, Salvatore, Segmentation and Automated Social Hierarchy Detection Through Email Network Analysis (March 25, 2012).
Wikipedia: Salvatore J. Stolfo - Wikipedia
Salvatore J. Stolfo is a tenured professor of computer science at Columbia University in New York and a leading expert in computer security. He is known for his research in machine learning applied to computer security, intrusion detection systems, anomaly …
All web results to the name "Salvatore Stolfo"
Salvatore Stolfo - Google Scholar Citations
scholar.google.com
Salvatore Stolfo. Professor of Computer Science, Columbia University. Verified email at columbia.edu - Homepage. Security. Articles Cited by Co-authors. Title Cited by Year; Data mining approaches for intrusion detection. W Lee, S Stolfo : 1998: A data mining framework for building intrusion detection models.
Ensemble-based Adaptive Intrusion Detection Wei Fan IBM T.J.Watson...
slideplayer.com
Some interesting requirements ƒNew types of intrusions are constantly invented by hackers. Most recent coordinated attacks on many ebusiness websites in...
Black Hat Europe | Salvatore Stolfo
www.blackhat.com
Salvatore Stolfo Columbia University. Salvatore Stolfo is a Professor of Computer Science at Columbia University. He is regarded as creating the area of machine learning applied to computer security in the mid-1990's and has created several anomaly detection algorithms and systems addressing some of the hardest problems in securing computer systems.
Anomaly Detection At Multiple Scales (ADAMS) | SBIR.gov
www.sbir.gov
Principal Investigator. Name: Salvatore Stolfo Title: President Phone: (201) Business Contact. Name: Salvatore Stolfo
Anomalous Payload Based Worm Detectioncs.uccs.edu/~cs591/studentproj/projF2009/mkopps/doc/present.pptx
cs.uccs.edu
Anomalous Payload Based Worm Detection. Ke Wang, Gabriela Cretu, Salvatore Stolfo. Computer Science, Columbia University. Mike Kopps. CS591. Agenda.
Decoy Documents May Soon Defend Against Data Loss
www.esecurityplanet.com
Salvatore Stolfo, a computer science professor at Columbia University's Intrusion Detection Systems Lab has developed document decoy technology and is ...
Eleazar Eskin: Publications
cseweb.ucsd.edu
Eleazar Eskin, Andrew Arnold, Michael Prerau, Leonid Portnoy and Salvatore Stolfo. ``A Geometric Framework for Unsupervised Anomaly Detection: Detecting ...
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