Partial Evaluation for Java']Java Malware Detection

被引:2
|
作者
Singh, Ranjeet [1 ]
King, Andy [1 ]
机构
[1] Univ Kent, Sch Comp, Canterbury CT2 7NF, Kent, England
关键词
D O I
10.1007/978-3-319-17822-6_8
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The fact that Java is platform independent gives hackers the opportunity to write exploits that can target users on any platform, which has a JVM implementation. To circumvent detection by anti-virus (AV) software, obfuscation techniques are routinely applied to make an exploit more difficult to recognise. Popular obfuscation techniques for Java include string obfuscation and applying reflection to hide method calls; two techniques that can either be used together or independently. This paper shows how to apply partial evaluation to remove these obfuscations and thereby improve AV matching. The paper presents a partial evaluator for Jimple, which is a typed three-address code suitable for optimisation and program analysis, and also demonstrates how the residual Jimple code, when transformed back into Java, improves the detection rates of a number of commercial AV products.
引用
收藏
页码:133 / 147
页数:15
相关论文
共 50 条
  • [1] Partial evaluation of string obfuscations for Java']Java malware detection
    Chawdhary, Aziem
    Singh, Ranjeet
    King, Andy
    [J]. FORMAL ASPECTS OF COMPUTING, 2017, 29 (01) : 33 - 55
  • [2] Detection of obfuscation in java']java malware
    Kumar, Renuka
    Vaishakh, Anand Raj Essar
    [J]. 1ST INTERNATIONAL CONFERENCE ON INFORMATION SECURITY & PRIVACY 2015, 2016, 78 : 521 - 529
  • [3] Reverse Engineering for potential Malware detection: Android APK Smali to Java']Java
    Sharma, Girish
    Mahrishi, Mehul
    Hiran, Kamal Kant
    Doshi, Ruchi
    [J]. JOURNAL OF INFORMATION ASSURANCE AND SECURITY, 2020, 15 (01): : 26 - +
  • [4] Decompilation of Java']Java bytecode to Prolog by partial evaluation
    Gomez-Zamalloa, Miguel
    Albert, Elvira
    Puebla, German
    [J]. INFORMATION AND SOFTWARE TECHNOLOGY, 2009, 51 (10) : 1409 - 1427
  • [5] Optimizing Java']Java based web services by partial evaluation
    Lin, L
    Huang, LP
    Sun, YQ
    [J]. GRID AND COOPERATIVE COMPUTING, PT 1, 2004, 3032 : 1071 - 1074
  • [6] Report: Java']Java Is Now the Favorite Malware Target
    不详
    [J]. COMPUTER, 2014, 47 (04) : 16 - 17
  • [7] BejaGNN: behavior-based Java']Java malware detection via graph neural network
    Feng, Pengbin
    Yang, Li
    Lu, Di
    Xi, Ning
    Ma, Jianfeng
    [J]. JOURNAL OF SUPERCOMPUTING, 2023, 79 (14): : 15390 - 15414
  • [8] Specializing the Java']Java object serialization using partial evaluation for a faster RMI
    Park, JG
    Lee, AH
    [J]. PROCEEDINGS OF THE EIGHTH INTERNATIONAL CONFERENCE ON PARALLEL AND DISTRIBUTED SYSTEMS, 2001, : 451 - 458
  • [9] Detecting Java']Java Compiled Malware using Machine Learning Techniques
    Balan, Gheorghe
    Popescu, Adrian Stefan
    [J]. 2018 20TH INTERNATIONAL SYMPOSIUM ON SYMBOLIC AND NUMERIC ALGORITHMS FOR SCIENTIFIC COMPUTING (SYNASC 2018), 2019, : 435 - 439
  • [10] Jadeite: A novel image-behavior-base approach for Java']Java malware detection using deep learning
    Obaidat, Islam
    Sridhar, Meera
    Pham, Khue M.
    Phung, Phu H.
    [J]. COMPUTERS & SECURITY, 2022, 113