An Evasion Resilient Approach to the Detection of Malicious PDF Files

[1]  Giorgio Giacinto,et al.  A structural and content-based approach for a precise and robust detection of malicious PDF files , 2015, 2015 International Conference on Information Systems Security and Privacy (ICISSP).

[2]  Yuval Elovici,et al.  Detection of malicious PDF files and directions for enhancements: A state-of-the art survey , 2015, Comput. Secur..

[3]  Fabio Roli,et al.  Poisoning behavioral malware clustering , 2014, AISec '14.

[4]  Giorgio Giacinto,et al.  Lux0R: Detection of Malicious PDF-embedded JavaScript code through Discriminant Analysis of API References , 2014, AISec '14.

[5]  Angelos Stavrou,et al.  Detecting Malicious Javascript in PDF through Document Instrumentation , 2014, 2014 44th Annual IEEE/IFIP International Conference on Dependable Systems and Networks.

[6]  Pavel Laskov,et al.  Practical Evasion of a Learning-Based Classifier: A Case Study , 2014, 2014 IEEE Symposium on Security and Privacy.

[7]  Jonathan Aldrich,et al.  In-nimbo sandboxing , 2014, HotSoS '14.

[8]  Fabio Roli,et al.  Security Evaluation of Pattern Classifiers under Attack , 2014, IEEE Transactions on Knowledge and Data Engineering.

[9]  Fabio Roli,et al.  Security Evaluation of Support Vector Machines in Adversarial Environments , 2014, ArXiv.

[10]  Fabio Roli,et al.  Is data clustering in adversarial settings secure? , 2013, AISec.

[11]  Fabio Roli,et al.  Evasion Attacks against Machine Learning at Test Time , 2013, ECML/PKDD.

[12]  Giorgio Giacinto,et al.  Looking at the bag is not enough to find the bomb: an evasion of structural methods for malicious PDF files detection , 2013, ASIA CCS '13.

[13]  Angelos Stavrou,et al.  Malicious PDF detection using metadata and structural features , 2012, ACSAC '12.

[14]  Giorgio Giacinto,et al.  A Pattern Recognition System for Malicious PDF Files Detection , 2012, MLDM.

[15]  Blaine Nelson,et al.  Poisoning Attacks against Support Vector Machines , 2012, ICML.

[16]  Pavel Laskov,et al.  Static detection of malicious JavaScript-bearing PDF documents , 2011, ACSAC '11.

[17]  Benjamin Livshits,et al.  ZOZZLE: Fast and Precise In-Browser JavaScript Malware Detection , 2011, USENIX Security Symposium.

[18]  Niels Provos,et al.  SHELLOS: Enabling Fast Detection and Forensic Analysis of Code Injection Attacks , 2011, USENIX Security Symposium.

[19]  Evangelos P. Markatos,et al.  Combining static and dynamic analysis for the detection of malicious documents , 2011, EUROSEC '11.

[20]  Giovanni Vigna,et al.  Prophiler: a fast filter for the large-scale detection of malicious web pages , 2011, WWW.

[21]  Fabio Roli,et al.  Multiple classifier systems for robust classifier design in adversarial environments , 2010, Int. J. Mach. Learn. Cybern..

[22]  Piotr Bania,et al.  JIT Spraying and Mitigations , 2010, ArXiv.

[23]  Christopher Krügel,et al.  Detection and analysis of drive-by-download attacks and malicious JavaScript code , 2010, WWW '10.

[24]  Benjamin Livshits,et al.  NOZZLE: A Defense Against Heap-spraying Code Injection Attacks , 2009, USENIX Security Symposium.

[25]  Muhammad Zubair Shafiq,et al.  Malware detection using statistical analysis of byte-level file content , 2009, CSI-KDD '09.

[26]  Carsten Willems,et al.  Learning and Classification of Malware Behavior , 2008, DIMVA.

[27]  Muhammad Zubair Shafiq,et al.  Embedded Malware Detection Using Markov n-Grams , 2008, DIMVA.

[28]  Salvatore J. Stolfo,et al.  A Study of Malcode-Bearing Documents , 2007, DIMVA.

[29]  Felix C. Freiling,et al.  Toward Automated Dynamic Malware Analysis Using CWSandbox , 2007, IEEE Secur. Priv..

[30]  Pierre Baldi,et al.  Assessing the accuracy of prediction algorithms for classification: an overview , 2000, Bioinform..

[31]  Yoav Freund,et al.  A decision-theoretic generalization of on-line learning and an application to boosting , 1997, EuroCOLT.

[32]  J. Ross Quinlan,et al.  Learning decision tree classifiers , 1996, CSUR.

[33]  Pavel Laskov,et al.  Detection of Malicious PDF Files Based on Hierarchical Document Structure , 2013, NDSS.

[34]  Andreas Dewald,et al.  Forschungsberichte der Fakultät IV – Elektrotechnik und Informatik C UJO : Efficient Detection and Prevention of Drive-by-Download Attacks , 2010 .

[35]  J. MacQueen.  Some methods for classification and analysis of multivariate observations , 1967 .