1. Malwares
1.1. Response to Malware Detection
1.1.1. Malware which can learn thus evolve against malware detection systems
1.2. Repackaging
1.2.1. Detecting Piggybacked Code
1.3. Rapid Malware Production
1.4. Trojan & Backdoors
1.4.1. Rooting Exploits
1.4.2. SMS Fraud
1.5. Spywares
1.5.1. Eavesdropping although the phone is closed
1.6. Adwares
1.6.1. Adjacking
1.6.2. False Notification Attacks
1.7. Android Malware Diagnosis
1.7.1. Market Scale Malware Triage
1.7.2. Android Malware Phylogeny
1.7.3. Malware Provalance
1.7.4. Android Malware Survey
2. Mobile Botnets
2.1. Epidemic Spread
2.2. Attacking Network Services
2.3. Evasive and Robust P.O.C.
2.4. Tracking Uninfected Devices
3. Browser Attacks
3.1. Phishing
3.2. Click Through
4. Baseband Attacks
5. Reverse Engineering
5.1. Limited availibility of tools
5.1.1. Apktool
5.1.2. Dex2Jar
5.1.3. Dexdump
6. Static Analysis
6.1. Class Dependence
6.1.1. Graph Centrality
6.2. Component Count
6.3. Permissions
6.4. Data Flow
6.4.1. User-Centric Analysis
6.5. Control Flow
6.6. Opcodes
6.7. Imported Packages
6.8. Market Data
6.9. Analyzing Native Code
6.10. Separation of malicious code from benign
6.11. Obfuscation
6.12. Dynamic code loading
6.13. Poor Application Verification
6.13.1. Weak Default App Scanner
6.13.2. Anti-malware against Transformation Attacks
6.13.3. Private App Channels
6.14. Limitted availability of tools
6.14.1. DroidMat
6.14.2. Andrubis
6.14.3. DroidRanger
6.14.4. Androguard
7. Dynamic Analysis
7.1. Sandboxing
7.1.1. Droidbox
7.2. Input Generation
7.2.1. Dynodroid
7.2.2. Monkey
7.3. Anamoly Detection
7.4. Behavioral Analysis
7.4.1. Bouncer
7.4.2. Aurasium
7.4.3. Taintdroid
7.4.4. Crowdroid
7.4.5. Machine Leaning based behavioral analysis
8. Android Forensics
8.1. Hiding Data
8.2. Data Mining Personal Information
8.3. Physical Access Attacks
8.3.1. password cracking
8.3.1.1. smudge detection
8.3.1.2. brute force
8.3.1.3. bypass
8.3.2. access data on RAM
8.3.2.1. FROST
8.3.3. survey of attacks