My slide presentation about malware detection technology on tssa conference 2020 http://tssa-conference.org

1. A Survey on Malware
Detection Technology and
Future Trends
Setia Juli Irzal Ismail, Hendrawan, Budi Rahardjo
57 JUL SurveyMalware

2. 2
Malware?
Wannacry
150 countries
200,000 devices

3. 3
Malware
analysis
Static Dynamic

4. 4
Static Analysis
Analyze code
Not executed
- obfuscation

5. 5
executed observed report
Dynamic analysis

6. 6
Classification
MalwareDetection
Traditional
Signature
Heuristic
Machine Learning
Supervised
Unsupervised
Deep Learning

7. 7
Signature-based
Analyze
Signature
Database

8. 8
Heuristic based
rules New malware False Positive

9. 9
Machine Learning
Malware
Samples
Machine
Learning
Malware vs Benign

10. 10
Supervised Learning
Malware
Benign
Feature
extraction
Training Classifier
Unknown
file
Malware Benign

11. 11
Unsupervised Learning
Unlabeled
Data
Training
Clustering
Feature
Cluster X
Cluster Y
Feature A
Feature B

12. 12
Deep Learning
Feature Classifier
Malware X
Malware Y
Malware Z
Benign
Multilayer
Learning
Dataset

13. 13
Challenges
Limited acces
Class Imbalance
Not Update
Labelling
Incorrect
prediction
Anti Machine
Learning
ClassifierAdversarialDataset
obsolete
Update
periodically

14. 14
Future Trends
Image Based
Representation
Multimodal
Learning
Artificial Immune
System

15. 15
Thank You
Setia Juli Irzal Ismail, Hendrawan, Budi Rahardjo
Institut Technology Bandung
julismail@telkomuniversity.ac.id
57, JUL, SurveyMalware