Programming Experience Might Not Help in Comprehending Obfuscated Source Code Efficiently
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1 Programming Experience Might Not Help in Comprehending Obfuscated Source Code Efficiently Norman Hänsch 1, Andrea Schankin 2, Mykolai Protsenko 3 Felix Freiling 1, Zinaida Benenson 1 1 Friedrich-Alexander-Universität Erlangen-Nürnberg 2 Karlsruhe Institute of Technology 3 Fraunhofer Institute for Applied and Integrated Security August 14, 2018
2 Background - Software Obfuscation Software obfuscation: protect programs by making them harder to understand 2 of 17
3 Background - Software Obfuscation Software obfuscation: protect programs by making them harder to understand Who obfuscates? Why? 2 of 17
4 Background - Software Obfuscation Software obfuscation: protect programs by making them harder to understand Who obfuscates? Why? Software vendors secure their intellectual property Hackers make their malicious code harder to understand 2 of 17
5 Background - Software Obfuscation Software obfuscation: protect programs by making them harder to understand Who obfuscates? Why? Software vendors secure their intellectual property Hackers make their malicious code harder to understand Collberg et al. (Technical Report, 1997): Potency: To what degree is a human reader confused? Resilience: How well an obfuscation methods up under an attack from an automatic deobfuscator? 2 of 17
6 Background - Software Obfuscation Software obfuscation: protect programs by making them harder to understand Who obfuscates? Why? Software vendors secure their intellectual property Hackers make their malicious code harder to understand Collberg et al. (Technical Report, 1997): Potency: To what degree is a human reader confused? Resilience: How well an obfuscation methods up under an attack from an automatic deobfuscator? Evaluation based on software metrics 2 of 17
7 Background - Software Obfuscation Software obfuscation: protect programs by making them harder to understand Who obfuscates? Why? Software vendors secure their intellectual property Hackers make their malicious code harder to understand Collberg et al. (Technical Report, 1997): Potency: To what degree is a human reader confused? Resilience: How well an obfuscation methods up under an attack from an automatic deobfuscator? Evaluation based on software metrics Ceccato et al. (Empirical Software Engineering, 2014): user studies 2 of 17
8 The Study - Replication and Novelty Replication Study materials Questionnaire Code understanding (correctness, time, efficiency) Obfuscation methods: Name Overloading (NO), Opaque Predicates (OP) 3 of 17
9 The Study - Replication and Novelty Replication Novelty Study materials Questionnaire Code understanding (correctness, time, efficiency) Obfuscation methods: Name Overloading (NO), Opaque Predicates (OP) Code analysis behavior (actions & time spent on them) The influence of experience Evaluation of correctness of the answers Study design 3 of 17
10 The Study - The Programs Figure: Race Program Figure: Chat Program 4 of 17
11 The Study - Code Examples Listing 1: Code obfuscated with Name Overloading (NO) 1 p u b l i c void m1 ( i n t i ) 2 { 3 i f ( f 2 2 ) 4 i f ( f 1 9 == 0) 5 { 6 f 5 += i ; 7 i f ( f 5 > f 6 / 10) 8 f 5 = f 6 / 1 0 ; 9 e l s e 10 i f ( f 5 < f 7 / 10) 11 f 5 = f 7 / 1 0 ; 12 } e l s e [... ] 5 of 17
12 The Study - Code Examples Listing 2: Clear code from Race MovingCarModel.java 1 p u b l i c void changespeed ( i n t i ) 2 { 3 i f ( s t a r t e d ) 4 i f ( gas == 0) 5 { 6 speed += i ; 7 i f ( speed > maxspeed / 10) 8 speed = maxspeed / 1 0 ; 9 e l s e 10 i f ( speed < minspeed / 10) 11 speed = minspeed / 1 0 ; 12 } e l s e [... ] 6 of 17
13 The Study - Code Examples Listing 3: Code obfuscated with Opaque Predicates (OP) 1 p u b l i c void changespeed ( i n t i ) { 2 i f ( Node. g e t I ( )!= Node. geth ( ) ) { 3 l a s t F u e l = (0 L + time2 ) ( long ) l a p ; 4 s t a r t e d = l a s t F u e l == 0L ; 5 Node. getf ( ). s e t L e f t ( Node. geth ( ). g e t L e f t ( ) ) ; 6 } e l s e { 7 Node. getg ( ). g e t L e f t ( ). swap ( 8 Node. getg ( ). g e t R i g h t ( ) ) ; 9 i f ( s t a r t e d ) 10 i f ( Node. g e t I ( ) == Node. geth ( ) ) { 11 i f ( gas == 0) { 12 i f ( Node. getf ( ) == Node. getg ( ) ) { 13 Node. getf ( ). s e t L e f t ( 14 7 of 17 Node. g e t I ( ). g e t R i g h t ( ) ) ; [... ]
14 The Study - Study Design Group 1st Program (clear code) 2nd Program (obfuscated) 1 Race: Rnd(Box,Laps) NO(Chat): Rnd(Messages,Users) 2 Race: Rnd(Box,Laps) OP(Chat): Rnd(Messages,Users) 3 Chat: Rnd(Messages,Users) NO(Race): Rnd(Box,Laps) 4 Chat: Rnd(Messages,Users) OP(Race): Rnd(Box,Laps) 8 of 17
15 The Study - Demographics of the Participants 66 participants 44 bachelor students 20 master students 2 PhD students 24.2% already participated in a course related to software obfuscation 9 of 17
16 Results - Code Comprehension Clear vs NO Correctness Efficiency * Total time 0.338** Time correct 0.351* Table: Wilcoxon & Mann-Whitney-U tests; *p <.05, **p <.01 Effect sizes r (no effect, small, medium) 10 of 17
17 Results - Code Comprehension Clear vs NO Clear vs OP Correctness Efficiency * ** Total time 0.338** 0.276* Time correct 0.351* Table: Wilcoxon & Mann-Whitney-U tests; *p <.05, **p <.01 Effect sizes r (no effect, small, medium) 10 of 17
18 Results - Code Comprehension Clear Clear NO vs NO vs OP vs OP Correctness Efficiency * ** Total time 0.338** 0.276* Time correct 0.351* Table: Wilcoxon & Mann-Whitney-U tests; *p <.05, **p <.01 Effect sizes r (no effect, small, medium) 10 of 17
19 Results - Behavior 11 of 17 Clear vs NO Number of: File open commands 0.451** Advanced commands 0.352** Program executions Debugging mode 0.420** Time spent on: Program executions 0.290* Debugging mode 0.433** Code reading Table: Wilcoxon & Mann-Whitney-U tests; *p <.05, **p <.01 Effect sizes r (no effect, small, medium)
20 Results - Behavior 11 of 17 Clear vs NO Clear vs OP Number of: File open commands 0.451** Advanced commands 0.352** 0.282* Program executions ** Debugging mode 0.420** 0.349** Time spent on: Program executions 0.290* 0.278* Debugging mode 0.433** 0.308* Code reading Table: Wilcoxon & Mann-Whitney-U tests; *p <.05, **p <.01 Effect sizes r (no effect, small, medium)
21 Results - Behavior 11 of 17 Clear Clear NO vs NO vs OP vs OP Number of: File open commands 0.451** ** Advanced commands 0.352** 0.282* Program executions ** Debugging mode 0.420** 0.349** Time spent on: Program executions 0.290* 0.278* Debugging mode 0.433** 0.308* Code reading Table: Wilcoxon & Mann-Whitney-U tests; *p <.05, **p <.01 Effect sizes r (no effect, small, medium)
22 The Study - Experience Survey questions Programming Experience: quality and type of code written so far Obfuscation Experience: experience with obfuscation and debugging Java Experience: experience with Java and using Eclipse Experiment Comprehension Skills: efficiency in working on clear code 12 of 17
23 The Study - Experience Survey questions Programming Experience: quality and type of code written so far Obfuscation Experience: experience with obfuscation and debugging Java Experience: experience with Java and using Eclipse Experiment Comprehension Skills: efficiency in working on clear code k-means cluster analysis: 21 beginners 45 experienced participants 12 of 17
24 Results - Experience Experience leads to significant differences concerning: ω 2 p Measurement 0.16 ** Correctness 0.10 ** Efficiency 0.13 ** Advanced commands 0.13 ** Debugging mode 0.05 * Time spent debugging Table: ANOVA; *p <.05, **p <.01; Effect size ω 2 (small, medium, large effect) 13 of 17
25 Results - Exp. x Obf.: Behavior Figure: ω 2 = 0.06* significant difference (ANOVA; *p <.05, **p <.01.) 14 of 17
26 Results - Exp. x Obf.: Behavior Figure: ω 2 = 0.09** significant difference (ANOVA; *p <.05, **p <.01.) 15 of 17
27 Results - Exp. x Obf.: Code Comprehension Figure: ω 2 = 0.01* significant difference (ANOVA; *p <.05, **p <.01.) 16 of 17
28 Summary 1. Confirmation of all findings by Ceccato et al. 2. Empirical support of the taxonomy of Collberg et al. 3. Code comprehension behavior on obfuscated software may be different from comprehension on traditional programs. 4. Programming experience might not help in comprehending obfuscated source code efficiently. 17 of 17
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