An Anomaly Detection System for the Protection of Relational Database Systems against Data Leakage by Application Programs
暂无分享,去创建一个
[1] Elisa Bertino,et al. DetAnom: Detecting Anomalous Database Transactions by Insiders , 2015, CODASPY.
[2] Ali Ahmadian Ramaki,et al. A systematic review on intrusion detection based on the Hidden Markov Model , 2018, Stat. Anal. Data Min..
[3] Barbara G. Ryder,et al. A Sharper Sense of Self: Probabilistic Reasoning of Program Behaviors for Anomaly Detection with Context Sensitivity , 2016, 2016 46th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN).
[4] Salvatore J. Stolfo,et al. Anomaly Detection as a Service: Challenges, Advances, and Opportunities , 2017, Anomaly Detection as a Service.
[5] Sin Yeung Lee,et al. Learning Fingerprints for a Database Intrusion Detection System , 2002, ESORICS.
[6] Christopher J. Novak,et al. 2009 Data Breach Investigations Report , 2009 .
[7] Dan Boneh,et al. Hacking Blind , 2014, 2014 IEEE Symposium on Security and Privacy.
[8] Elisa Bertino,et al. Detecting anomalous access patterns in relational databases , 2008, The VLDB Journal.
[9] Yevgeniy Vorobeychik,et al. Optimal Thresholds for Anomaly-Based Intrusion Detection in Dynamical Environments , 2016, GameSec.
[10] Alex Bateman,et al. An introduction to hidden Markov models. , 2007, Current protocols in bioinformatics.
[11] Michael Gertz,et al. DEMIDS: A Misuse Detection System for Database Systems , 2000, IICIS.
[12] Hung Q. Ngo,et al. A Data-Centric Approach to Insider Attack Detection in Database Systems , 2010, RAID.
[13] Beizhan Wang,et al. Survey on HMM based anomaly intrusion detection using system calls , 2010, 2010 5th International Conference on Computer Science & Education.
[14] Yuxin Ding,et al. Host-based intrusion detection using dynamic and static behavioral models , 2003, Pattern Recognit..
[15] Barbara G. Ryder,et al. Probabilistic Program Modeling for High-Precision Anomaly Classification , 2015, 2015 IEEE 28th Computer Security Foundations Symposium.
[16] Zoubin Ghahramani,et al. An Introduction to Hidden Markov Models and Bayesian Networks , 2001, Int. J. Pattern Recognit. Artif. Intell..
[17] Debin Gao,et al. Beyond Output Voting: Detecting Compromised Replicas Using HMM-Based Behavioral Distance , 2009, IEEE Transactions on Dependable and Secure Computing.
[18] R. Sekar,et al. A fast automaton-based method for detecting anomalous program behaviors , 2001, Proceedings 2001 IEEE Symposium on Security and Privacy. S&P 2001.
[19] Hovav Shacham,et al. Return-Oriented Programming: Systems, Languages, and Applications , 2012, TSEC.
[20] Alessandro Orso,et al. A Classification of SQL Injection Attacks and Countermeasures , 2006, ISSSE.
[21] Navjot Singh,et al. Transparent Run-Time Defense Against Stack-Smashing Attacks , 2000, USENIX Annual Technical Conference, General Track.
[22] Matilde Santos Peñas,et al. Data leakage detection algorithm based on task sequences and probabilities , 2017, Knowl. Based Syst..
[23] Elisa Bertino,et al. Data and syntax centric anomaly detection for relational databases , 2016, WIREs Data Mining Knowl. Discov..
[24] Chih-Jen Lin,et al. A Study on Threshold Selection for Multi-label Classification , 2007 .
[25] Debin Gao,et al. Gray-box extraction of execution graphs for anomaly detection , 2004, CCS '04.
[26] Elisa Bertino,et al. PANDDE: Provenance-based ANomaly Detection of Data Exfiltration , 2016, CODASPY.
[27] Harish Patil,et al. Pin: building customized program analysis tools with dynamic instrumentation , 2005, PLDI '05.
[28] Elisa Bertino,et al. A-PANDDE: Advanced Provenance-based ANomaly Detection of Data Exfiltration , 2019, Comput. Secur..
[29] Marius Kloft,et al. Hidden Markov Anomaly Detection , 2015, ICML.
[30] Vallipuram Muthukkumarasamy,et al. A survey on data leakage prevention systems , 2016, J. Netw. Comput. Appl..