- Computer Science2018 International Joint Conference on Neural Networks (IJCNN)
The proposed Doc2Vec features provide better accuracy and fast classification in malicious JS code detection compared to conventional approaches, and are compared to other feature learning methods.
A Practical Guide for Detecting the Java Script-Based Malware Using Hidden Markov Models and Linear Classifiers
- Computer Science2014 16th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing
This paper proposes various methods for detecting Java Script-based attack vectors, and analyzes these detection methods from a practical point of view, emphasizing the need for a very low false positive rate and the ability to be trained on large datasets.
- Computer Science, MathematicsSecur. Commun. Networks
Probe the Proto: Measuring Client-Side Prototype Pollution Vulnerabilities of One Million Real-world Websites
- Computer ScienceProceedings 2022 Network and Distributed System Security Symposium
This paper proposes the first large- scale measurement study of client-side prototype pollution among one million real-world websites and answers the questions of whether a prototypical object is controllable, whether and what properties can be manipulated, and whether the injected value leads to further consequences.
- Computer ScienceSEC
According to the empirical results based on a ten day polling period of over 35 thousand scripts collected from popular websites, temporal integrity changes are relatively common and it is possible to statistically predict whether a temporal integrity change is likely to occur.
DETECTION : A STATE OF ART SURVEY
- Computer Science
The detailed analysis carried out in this paper provides a new road map for the research in this area and classifies the detection methods in three categoriesstatic, dynamic and hybrid approaches.
Probabilistic Methods for Network Security. From Analysis to Response
- Computer Science
This thesis shows, how methods from statistics and machine learning can improve the security cycle of analysis, detection and response to threats by carefully layering probabilistic methods andMachine learning techniques, and creates solid solutions for pressing security problems.
Data Mining Based Strategy for Detecting Malicious PDF Files
- Computer Science2018 17th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/ 12th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE)
A new algorithm is presented for detecting malicious PDF files based on data mining techniques to achieve high detection rate and low false positive rate with small computational overhead.
Malware Slums: Measurement and Analysis of Malware on Traffic Exchanges
- Computer Science2016 46th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN)
Drive-by Disclosure: A Large-Scale Detector of Drive-by Downloads Based on Latent Behavior Prediction
- Computer Science2015 IEEE Trustcom/BigDataSE/ISPA
The proposed Drive-by Disclosure leverages availability of AST representation to predict script's latent behaviors statically and facilitates distinction between scripting practices of drive-by downloads and disguised transformations.
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