A Framework for Constructing Features and Models for Intrusion Detection Systems Authors: Wenke Lee & Salvatore J.Stolfo Published in ACM Transactions on Information ...
Method proposed by Lee, Stolfo, and Mok. Process raw audit data into ASCII network events ... Mok August 1999 Proceedings of the fifth ACM SIGKDD international ...
Proactively Removing the Botnet Threat ... Question: Is there a botnet threat (that s distinct from the general threat of network/computer insecurity)?
Intrusion Detection Using Data Mining By Anshu Veda(04329022) Prajakata Kalekar(04329008) Anirudha Bodhankar(04329003) Under the Guidance of Prof Sunita Sarawagi
... with areas of focus Leading research in Natural language processing Mobile and wireless ... Mesh Networks Systems: Evolution ... intrusion detection ...
training non-CS SEAS and College students in algorithmic thinking and ... Only SEAS department that enrolls SEAS, College, GSAS & Barnard students. Columbia CS ...
Knowledge discovery & data mining: Classification UCLA CS240A Winter 2002 Notes from a tutorial presented @ EDBT2000 By Fosca Giannotti and Dino Pedreschi
Any Card , plate , or coupon book that may be used repeatedly to borrow money or ... AdaCost Algo. Used internal heuristics based upon training acuracy ...
and anomaly: some connection that is neither normal nor some known types of intrusions. ... based Artificial Anomaly (Fan et al, ... Anomaly Detection: ...
Combining Technique-Averaging ... include variations of averaging, regression and meta-learning ... Averaging, although simple, has the highest accuracy. ...
True Positive = a/(a c) False Positive = b/(b d) Miss Rate = 1 ... False Positive. Percentage of False Alarm system calls ( or short sequences ) within a normal ...
Each block is N-dimensional binary feature vector. N is the number of unique ... Each 1 dimension is a Bernoulli, the whole vector is multivariate Bernoulli. ...
Bagging and Random Forest: the introduction of ... Out-of-bag Margin ... Out-of-bag margin is a more fair estimate of the performance on test data. 9/2/09 ...
Passively monitors the system for suspect behavior. Sources for monitored data ... Evolved from IDES over the early 1990's. Uses both rule based and anomaly detection ...
Title: One Class Training for Masquerade Detection Author: Ke Wang Last modified by: Ke Wang Created Date: 5/7/2003 8:20:28 PM Document presentation format
CS@25 - October 22, 2004. The Department of Computer Science at ... Recife. U Palermo. U Rome. U Macedonia. National University Seoul. Tel Aviv University ...
... traces cleaning training data can reduce false positive rate. ... false positive rate drops to: 0.000254% worm packets detection rate 100%. Future work ...
IDS Quality: ROC curve ... Linear Piecewise ROC. 17. Optimal ... Extend the study with other types of ROC functions. Include multiple types of alarm ...
1. Symposium on Machine Learning for Anomaly Detection. Activity ... Mixing one account's examples between train and test sets may leak test info into training ...
Bit 0, Bit 1, Bit 2 Length of packet - 1. Encode by Protocol. Encoding Headers. Navigation ... screenshots. with supporting .rum and .pcap files, if possible ...
Artificial Immunity-based Intrusion Detection System Associate Prof. Fang Xian-jin Computer School of AUST Background With the development of computer and network ...
No finals, midterms or exams. Graduate course: E6998. http://www.columbia.edu/~dd20/e6998.htm ... Sample Spring 2006 final projects: UIs for the Skype API, emphasizing ...
Modern document formats (Word, PowerPoint, PDF) are 'code injection platforms' ... Many forms of malicious code: Macros, JavaScript, arbitrary 'object code' ...
Two generations of LANs 100 Mb/s switched for every workstation. CLIC teaching lab (Sun Linux) ... About 40 Unix workstations. Combines. MS/PhD research ...
Data Mining &Intrusion Detection Shan Bai Instructor: Dr. Yingshu Li CSC 8712 ,Spring 08 Outline Intrusion Detection Data Mining Data Mining in Intrusion Detection ...
Data Mining &Intrusion Detection Shan Bai Instructor: Dr. Yingshu Li CSC 8712 ,Spring 08 Outline Intrusion Detection Data Mining Data Mining in Intrusion Detection ...
The Overall Classification of this Briefing is UNCLASSIFIED National Intelligence Community Information Assurance Research Program NICIAR: Pursuing Disruptive ...
Title: 10 Challenging Problems in Data Mining Research prepared for ICDM 2005 Author: qyang Last modified by: mukka Created Date: 11/19/2005 8:11:28 AM
NL/UI/Medical collaboration. 5. Research Projects. Vision. Shree ... How to construct a Bayesian net for a given problem. What are the independence assumptions? ...
Why PCs Are Fragile and What We Can Do About It: A Study of Windows Registry ... Technical report CRHC 98-08, University of Illinois at Urbana-Champaign, 1998. ...
Each class define a unique kind of object ( a new data type) ... same as one of the class names, including capitalization! At most one public class per file ...
1. Probabilistic/Uncertain Data Management. Slides based on the Suciu/Dalvi SIGMOD' ... Das Sarma et al. 'Working models for uncertain data', ICDE'2006. 2 ...
Intrusion Detection System collect information from a variety of system and ... translated into facts carrying their semantic signification in the expert system. ...
A Quantum Programming Language and Compiler. Katherine Heller, Krysta ... Stop when ROC score drops below 90% of original value on untouched test set. Results ...
Relies on consistency checks over normal data and labels a record anomalous if ... Ability of OCSVM to detect anomalies relies on the choice of the kernel ...
The model is represented as classification rules, decision trees or mathematical formulae ... Classical example: play tennis? Training set from Quinlan's ID3 ...
Predict fraud since we get $10 back. Combining Multiple Models. Individual benefits ... card fraud detection. Total benefits: Recovered fraud amount minus ...
Data Stream Classification and Novel Class Detection Mehedy Masud, Latifur Khan, Qing Chen and Bhavani Thuraisingham Department of Computer Science , University of ...
Text-mined PSS case logs. Extract registry-related problems from e-mails ... Text-mined Data Distribution. Only 100 most common problems graphed. Why Are PCs Fragile? ...