Anatoli Kalysch, M. Sc.

  • Organization: Department of Computer Science
  • Working group: Chair of Computer Science 1 (IT Security Infrastructures)
  • Phone number: +49 9131 85 67651
  • Fax number: +49 9131 85 69919
  • Email:
  • Website:
  • Address:
    Martensstr. 3
    91058 Erlangen
    Room 12.139

PhD candidate at Friedrich-Alexander-University, passionate about IT security with a focus on vulnerability research and malware analysis, with strong technical, business, and interpersonal skills. I have been teaching and tutoring courses in IT Forensics, as well as offensive and defensive IT Security at the IT Security Infrastructures Lab since 2016.

Current Research Interests

Mobile Security (Android):

  • Application UI Security and Data Leakage;
  • Application Packers and Protectors;
  • Emulation and Analysis Detection;

Program Analysis Techniques:

  • Taint-tracking;
  • Code similarity measures;
  • Symbolic execution;
  • Fuzzing;

Obfuscation Techniques:

  • Virtualization-based Obfuscation;

Machine Learning Approaches:

  • Supervised (SVM, RF, KNN) and Unsupervised (K-Means) Machine Learning;
  • Deep Learning (CNN);
  • Natural Language Processing;


Professional Activities

Supervised Student Thesises

Due to capacity constrains I currently no longer offer any project or thesis supervision.


  • (Master’s Thesis) An Empirical Study of Malicious Native Libraries on Android (WiSe2017)
  • (Master’s Thesis) Evaluating the Effectiveness of Machine Learning for Android Packer Detection and Classification (WiSe2017)
  • (Master’s Thesis) Clickjacking Revised: An Automated Framework for Clickjacking Attacks (SoSe2018)
  • (Master’s Thesis) Dismanteling On-Device Android Malware Protection (SoSe2018)
  • (Bachelor’s Thesis) Android UI-Instrumentation for Malware Analysis and Forensic Trace Generation (WiSe2018)
  • (Bachelor’s Thesis) Automated Static Vulnerability Detection for Android Third Party Applications (WiSe2018)
  • (Master’s Thesis) Enhancing Malware Analysis Through Automated IR-based Functionality Extraction (WiSe2018)
  • (Bachelor’s Thesis) Android Inter Process Communication Fuzzing (WiSe2018)
  • (Master’s Thesis) Opaque Predicate and Junk Code resistant Decompilation (WiSe2018)
  • (Master’s Thesis) Automated Entropy-Based Detection of Cryptographic Functions in Binaries (WiSe2018)


  • (Master’s Thesis) A Study on Code and Functionality Reuse among Android Mass Malware Families (est. 2019)
  • (Bachelor’s Thesis) Automated Vulnerability Scanning in Machine Learned Code Reuse Detection Systems (est. 2019)
  • (Master’s Thesis) Deep Learning in Automated Vulnerability Assessments for Android Applications (est. 2019)
  • (Master’s Thesis) Virtualization-Based Android App Obfuscation (est. 2019)
  • (Master’s Thesis) A Study on Code Similarity Measures (est. 2019)




ID: F95069D5
SHA1 Fingerprint: 0470 4645 32E3 4C29 7732 7CFA 9B04 DCF8 F950 69D5
Public Key: ASCII Armored