Efficient, compiler-agnostic and platform-independent labeling of functions in executable programs:
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| 1. Verfasser: | |
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| Format: | Abschlussarbeit Buch |
| Sprache: | English |
| Veröffentlicht: |
Waabs
GCA-Verlag
[2017]
|
| Schriftenreihe: | Forschen und Wissen - Informatik
|
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis Inhaltsverzeichnis |
| Beschreibung: | XV, 150 Seiten Illustrationen, Diagramme 21 cm |
| ISBN: | 9783898632669 3898632660 |
Internformat
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| 245 | 1 | 0 | |a Efficient, compiler-agnostic and platform-independent labeling of functions in executable programs |c Sebastian Eschweiler |
| 264 | 1 | |a Waabs |b GCA-Verlag |c [2017] | |
| 300 | |a XV, 150 Seiten |b Illustrationen, Diagramme |c 21 cm | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
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| 490 | 0 | |a Forschen und Wissen - Informatik | |
| 502 | |b Dissertation |c Rheinische Friedrich-Wilhelms-Universität Bonn |d 2017 | ||
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Datensatz im Suchindex
| _version_ | 1804182102818684928 |
|---|---|
| adam_text | C O N T E N T S
1 INTRODUCTION 1
1.1 PROBLEM D E FIN ITIO N
....................................................................................................
I
1.2 RESEARCH Q U E STIO N
S....................................................................................................
2
1.2.1 IDENTIFICATION OF VULNERABLE F U N C TIO N
S.................................................................. 2
1.2.2 RECOVERING THE VERSION HISTORY OF EXECUTABLE PROGRAM S
.....................................
4
1.3 CONTRIBUTIONS
............................................................................................................
4
1.4 THESIS O U TLIN E
............................................................................................................
5
2 BACKGROUND 7
2.1 CODE A N A LY
SIS............................................................................................................
7
2.2 REVERSE
ENGINEERING....................................................................................................
8
2.2.1 STATIC A NALY
SIS.........................................................................................................
8
2.2.2
DISASSEMBLER............................................................................................................
9
2.2.3 REPRESENTATIONS OF MACHINE C O D
E..........................................................................
10
2.3 THEORY
........................................................................................................................
11
3 RELATED WORK 15
3.1 DESIGN G O A
LS...............................................................................................................
15
3.2 SOURCE CODE PLAGIARISM
...........................................................................................
17
3.2.1 STRINGS
.....................................................................................................................
18
3.2.2 TOKENS
.....................................................................................................................
18
3.2.3 ABSTRACT SYNTAX T R E E
..............................................................................................
18
3.2.4 PROGRAM DEPENDENCE G RAP H
...................................................................................
20
3.3 DETECTION OF SIMILARITIES IN MACHINE C O D E
.............................................................. 20
3.3.1 MACHINE CODE INSTRUCTIONS
.....................................................................................
21
3.3.2 CLASS F E A TU RE
S.........................................................................................................
23
3.3.3 API F U N CTIO N
S.........................................................................................................
23
3.3.4 STRINGS AND NUMERIC C O N STAN
TS.............................................................................
24
3.3.5 GRAPH S TRU C TU RE
......................................................................................................
24
3.3.6 VALUE
SETS.................................................................................................................
25
3.3.7 F O RM U
LAS..................................................................................................................
25
3.3.8 TRACELETS
..................................................................................................................
26
3.3.9 COMBINED A
PPROACHES...........................................................................................
27
3.4 C
ONCLUSION.......................................................................................................
27
4 DISCOVRE 31
4.1 SYSTEM O V E RV IE W
......................................................................................................
31
4.2 MATCHING WITH THE DESIGN GOALS
.............................................................................
32
4.3 G
RANULARITY..................................................................................................................
33
XU C O NTEN TS
4 4 FUNCTION F E A TU RE
S.......................................................................................................
34
44.1 NUMERIC F E A TU RE
S....................................................................................................
35
4.4.2 C
ONSTANTS..................................................................................................................
39
4.4.3 COMPLEX F EATU
RES....................................................................................................
41
4.4.4 D ISCU SSIO N
...............................................................................................................
43
4.5 NUMERIC F ILTE
R............................................................................................................
44
4.5.1 REQUIREMENTS
..........................................................................................................
45
4.5.2 MACHINE LEARNING A LGORITHM
S................................................................................
46
4.5.3 DATA N ORM
ALIZATION.................................................................................................
48
4.5.4 DIMENSIONALITY R ED U CTIO N
......................................................................................
48
4.5.5 D ISCU SSIO N
...............................
49
4.6 COMPLEX F ILTE
R............................................................................................................
49
4.6.1 BASIC BLOCK DISTANCE
..............................................................................................
50
4.6.2 GRAPH-BASED SIM
ILARITY...........................................................................................
51
4.7 C
ONCLUSION..................................................................................................................
54
5 GENERATION OF A REPRESENTATIVE GROUND TRUTH 57
5.1 GENERATION OF THE GROUND T RU TH
................................................................................
57
5.1.1 CPU ARCHITECTURES
.................................................................................................
58
5.1.2 OPERATING SYSTEMS
.................................................................................................
59
5.1.3 COMPILERS
...............................................................................................................
59
5.1.4 COMPILATION O P TIO N S
..............................................................................................
60
5.1.5 SOURCE C O D E
.............................................................................................................
61
5.1.6 VALIDATION OF THE COMPILATION P RO C E S
S.................................................................. 62
5.1.7 CONCLUSION .
.
............................................................................................................
63
5.2 ASSESSMENT OF THE GROUND T R U T H
...........................................................................
63
5.2.1 CHOICE OF THE DISASSEMBLER F RA M E W O RK
............................................................... 64
5.2.2 VALIDATION OF THE DISASSEM
BLY................................................................................
66
5.2.3 MATCHING OF MACHINE CODE F U N C TIO N
S.................................................................. 71
5.2.4 C
ONCLUSION...............................................................................................................
73
5.3 REMOVAL OF D U P LIC A TE
S............................................................................................
73
5.3.1 ON THE RANDOMNESS OF COMPILER O PTIM IZATIONS
................................................
74
5.3.2 REMOVAL OF NEAR DUPLICATE EXECUTABLE PROGRAM S
................................................
75
5.3.3 REMOVAL OF DUPLICATE AND TRIVIAL
FUNCTIONS......................................................... 76
5.3.4 C
ONCLUSION...............................................................................................................
77
5.4 SUMMARY AND DISCUSSION
........................................................................................
78
6 DERIVATION AND EVALUATION OF DISCOVRE S KEY PROPERTIES 79
6.1 ANALYSIS OF THE NUMERIC F
ILTER...................................................................................
79
6.1.1 IDENTIFICATION OF ROBUST NUMERIC
FEATURES............................................................ 79
6.1.2 COMPARISON OF MACHINE LEARNING ALGORITHMS
...................................................
83
6.1.3 K-NEAREST NEIGHBOR M E TH O D S
................................................................................
85
6.1.4 K-NEAREST NEIGHBOR IMPLEMENTATIONS
.................................................................. 86
CONTENTS
XIII
6.1.5 EVALUATION OF THE EFFICIENT P REFILTER
.....................
87
6.1.6 C ON CLU SION
........................................................................................................................
90
6.2 ANALYSIS OF THE COMPLEX
FILTER.........................................................................................
92
6.2.1 EVALUATION OF THE BASIC BLOCK D ISTA N
CE.......................................................................
93
6.2.2 ROBUSTNESS OF THE GRAPH DISTANCE F
UNCTION.............................................................. 98
6.2.3 CONVERGENCE SPEED OF THE M C S
.......................................................................................
102
6.2.4 COMPARISON OF DMCS WITH BIPARTITE M ATCHING
..............................................................
103
6.2.5 COMPARISON TO VANTAGE POINT T R E E
.................................................... 105
6.3 C O N CLU SIO N
..............................................................................................................................105
7
E V A L U A T IO N
107
7.1 PREDICTION QUALITY OF D ISC O V R E
..........................................................................................
107
7.1.1 RESULTS OF THE NUMERIC FILTER
..........................................................................................
108
7.1.2 RESULTS OF THE COMBINED FILTER S T A G E S
...........................................................................108
7.1.3 DIMENSIONALITY R ED U CTIO N
................................................................................................
109
7.1.4 C ON CLU SION
............................................................................................................................109
7.2 EFFICIENT CROSS-ARCHITECTURE IDENTIFICATION OF BUGS IN MACHINE C O D
E
.........................
N O
7.2.1 R E S U LT S
..................................................................................................................................
113
7.2.2 CROSS-ARCHITECTURE BUG SEARCH IN COMPLETE FIRMWARE IM A G E
S................................113
7.2.3 COMPARISON TO INDUSTRIAL S TA N D A R D
S..............................................................................114
7.3 RECOVERING THE VERSION HISTORY OF EXECUTABLE PROGRAM S
................................................
116
7.3.1 CASE S TU D Y
............................................................................................................................118
7.3.2 R E S U LT S
..................................................................................................................................119
7.4 C O N CLU SIO N
...............................................................................................................................120
8
C O N C L U S I O N A N D O U T L O O K
123
8.1 L IM
ITATIONS...............................................................................................................................126
8.2 FURTHER RESEARCH Q U E STIO N
S................................................................................................
127
8.2.1 NORMALIZATION OF THE INPUT C O D E
....................................................................................127
8.2.2 SCRUTINY OF OTHER F
EATURES................................................................................................
127
8.2.3
PARALLELIZATION......................................................................................................................128
8.3 FURTHER A P P LICA TIO N
S............................................................................................................
128
8.3.1 MALWARE A N A LY
SIS................................................................ 128
8.3.2 DETECTION OF SOFTWARE P LAGIARISM
....................................................................................129
APPENDIX 131
N O M E N C L A T U R E 1 3 3
133
BIBLIOGRAPHY
|
| adam_txt |
C O N T E N T S
1 INTRODUCTION 1
1.1 PROBLEM D E FIN ITIO N
.
I
1.2 RESEARCH Q U E STIO N
S.
2
1.2.1 IDENTIFICATION OF VULNERABLE F U N C TIO N
S. 2
1.2.2 RECOVERING THE VERSION HISTORY OF EXECUTABLE PROGRAM S
.
4
1.3 CONTRIBUTIONS
.
4
1.4 THESIS O U TLIN E
.
5
2 BACKGROUND 7
2.1 CODE A N A LY
SIS.
7
2.2 REVERSE
ENGINEERING.
8
2.2.1 STATIC A NALY
SIS.
8
2.2.2
DISASSEMBLER.
9
2.2.3 REPRESENTATIONS OF MACHINE C O D
E.
10
2.3 THEORY
.
11
3 RELATED WORK 15
3.1 DESIGN G O A
LS.
15
3.2 SOURCE CODE PLAGIARISM
.
17
3.2.1 STRINGS
.
18
3.2.2 TOKENS
.
18
3.2.3 ABSTRACT SYNTAX T R E E
.
18
3.2.4 PROGRAM DEPENDENCE G RAP H
.
20
3.3 DETECTION OF SIMILARITIES IN MACHINE C O D E
. 20
3.3.1 MACHINE CODE INSTRUCTIONS
.
21
3.3.2 CLASS F E A TU RE
S.
23
3.3.3 API F U N CTIO N
S.
23
3.3.4 STRINGS AND NUMERIC C O N STAN
TS.
24
3.3.5 GRAPH S TRU C TU RE
.
24
3.3.6 VALUE
SETS.
25
3.3.7 F O RM U
LAS.
25
3.3.8 TRACELETS
.
26
3.3.9 COMBINED A
PPROACHES.
27
3.4 C
ONCLUSION.
27
4 DISCOVRE 31
4.1 SYSTEM O V E RV IE W
.
31
4.2 MATCHING WITH THE DESIGN GOALS
.
32
4.3 G
RANULARITY.
33
XU C O NTEN TS
4 4 FUNCTION F E A TU RE
S.
34
44.1 NUMERIC F E A TU RE
S.
35
4.4.2 C
ONSTANTS.
39
4.4.3 COMPLEX F EATU
RES.
41
4.4.4 D ISCU SSIO N
.
43
4.5 NUMERIC F ILTE
R.
44
4.5.1 REQUIREMENTS
.
45
4.5.2 MACHINE LEARNING A LGORITHM
S.
46
4.5.3 DATA N ORM
ALIZATION.
48
4.5.4 DIMENSIONALITY R ED U CTIO N
.
48
4.5.5 D ISCU SSIO N
.
49
4.6 COMPLEX F ILTE
R.
49
4.6.1 BASIC BLOCK DISTANCE
.
50
4.6.2 GRAPH-BASED SIM
ILARITY.
51
4.7 C
ONCLUSION.
54
5 GENERATION OF A REPRESENTATIVE GROUND TRUTH 57
5.1 GENERATION OF THE GROUND T RU TH
.
57
5.1.1 CPU ARCHITECTURES
.
58
5.1.2 OPERATING SYSTEMS
.
59
5.1.3 COMPILERS
.
59
5.1.4 COMPILATION O P TIO N S
.
60
5.1.5 SOURCE C O D E
.
61
5.1.6 VALIDATION OF THE COMPILATION P RO C E S
S. 62
5.1.7 CONCLUSION .
.
.
63
5.2 ASSESSMENT OF THE GROUND T R U T H
.
63
5.2.1 CHOICE OF THE DISASSEMBLER F RA M E W O RK
. 64
5.2.2 VALIDATION OF THE DISASSEM
BLY.
66
5.2.3 MATCHING OF MACHINE CODE F U N C TIO N
S. 71
5.2.4 C
ONCLUSION.
73
5.3 REMOVAL OF D U P LIC A TE
S.
73
5.3.1 ON THE RANDOMNESS OF COMPILER O PTIM IZATIONS
.
74
5.3.2 REMOVAL OF NEAR DUPLICATE EXECUTABLE PROGRAM S
.
75
5.3.3 REMOVAL OF DUPLICATE AND TRIVIAL
FUNCTIONS. 76
5.3.4 C
ONCLUSION.
77
5.4 SUMMARY AND DISCUSSION
.
78
6 DERIVATION AND EVALUATION OF DISCOVRE'S KEY PROPERTIES 79
6.1 ANALYSIS OF THE NUMERIC F
ILTER.
79
6.1.1 IDENTIFICATION OF ROBUST NUMERIC
FEATURES. 79
6.1.2 COMPARISON OF MACHINE LEARNING ALGORITHMS
.
83
6.1.3 K-NEAREST NEIGHBOR M E TH O D S
.
85
6.1.4 K-NEAREST NEIGHBOR IMPLEMENTATIONS
. 86
CONTENTS
XIII
6.1.5 EVALUATION OF THE EFFICIENT P REFILTER
.
87
6.1.6 C ON CLU SION
.
90
6.2 ANALYSIS OF THE COMPLEX
FILTER.
92
6.2.1 EVALUATION OF THE BASIC BLOCK D ISTA N
CE.
93
6.2.2 ROBUSTNESS OF THE GRAPH DISTANCE F
UNCTION. 98
6.2.3 CONVERGENCE SPEED OF THE M C S
.
102
6.2.4 COMPARISON OF DMCS WITH BIPARTITE M ATCHING
.
103
6.2.5 COMPARISON TO VANTAGE POINT T R E E
. 105
6.3 C O N CLU SIO N
.105
7
E V A L U A T IO N
107
7.1 PREDICTION QUALITY OF D ISC O V R E
.
107
7.1.1 RESULTS OF THE NUMERIC FILTER
.
108
7.1.2 RESULTS OF THE COMBINED FILTER S T A G E S
.108
7.1.3 DIMENSIONALITY R ED U CTIO N
.
109
7.1.4 C ON CLU SION
.109
7.2 EFFICIENT CROSS-ARCHITECTURE IDENTIFICATION OF BUGS IN MACHINE C O D
E
.
N O
7.2.1 R E S U LT S
.
113
7.2.2 CROSS-ARCHITECTURE BUG SEARCH IN COMPLETE FIRMWARE IM A G E
S.113
7.2.3 COMPARISON TO INDUSTRIAL S TA N D A R D
S.114
7.3 RECOVERING THE VERSION HISTORY OF EXECUTABLE PROGRAM S
.
116
7.3.1 CASE S TU D Y
.118
7.3.2 R E S U LT S
.119
7.4 C O N CLU SIO N
.120
8
C O N C L U S I O N A N D O U T L O O K
123
8.1 L IM
ITATIONS.126
8.2 FURTHER RESEARCH Q U E STIO N
S.
127
8.2.1 NORMALIZATION OF THE INPUT C O D E
.127
8.2.2 SCRUTINY OF OTHER F
EATURES.
127
8.2.3
PARALLELIZATION.128
8.3 FURTHER A P P LICA TIO N
S.
128
8.3.1 MALWARE A N A LY
SIS. 128
8.3.2 DETECTION OF SOFTWARE P LAGIARISM
.129
APPENDIX 131
N O M E N C L A T U R E 1 3 3
133
BIBLIOGRAPHY |
| any_adam_object | 1 |
| any_adam_object_boolean | 1 |
| author | Eschweiler, Sebastian |
| author_GND | (DE-588)1150866586 |
| author_facet | Eschweiler, Sebastian |
| author_role | aut |
| author_sort | Eschweiler, Sebastian |
| author_variant | s e se |
| building | Verbundindex |
| bvnumber | BV047087529 |
| classification_rvk | ST 255 |
| ctrlnum | (OCoLC)1016445128 (DE-599)DNB1149068833 |
| dewey-full | 005.12028 005.453 005.8 |
| dewey-hundreds | 000 - Computer science, information, general works |
| dewey-ones | 005 - Computer programming, programs, data, security |
| dewey-raw | 005.12028 005.453 005.8 |
| dewey-search | 005.12028 005.453 005.8 |
| dewey-sort | 15.12028 |
| dewey-tens | 000 - Computer science, information, general works |
| discipline | Informatik |
| discipline_str_mv | Informatik |
| format | Thesis Book |
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| genre | (DE-588)4113937-9 Hochschulschrift gnd-content |
| genre_facet | Hochschulschrift |
| id | DE-604.BV047087529 |
| illustrated | Illustrated |
| index_date | 2024-07-03T16:18:17Z |
| indexdate | 2024-07-10T09:02:13Z |
| institution | BVB |
| institution_GND | (DE-588)1065363656 |
| isbn | 9783898632669 3898632660 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-032494180 |
| oclc_num | 1016445128 |
| open_access_boolean | |
| owner | DE-83 |
| owner_facet | DE-83 |
| physical | XV, 150 Seiten Illustrationen, Diagramme 21 cm |
| publishDate | 2017 |
| publishDateSearch | 2017 |
| publishDateSort | 2017 |
| publisher | GCA-Verlag |
| record_format | marc |
| series2 | Forschen und Wissen - Informatik |
| spelling | Eschweiler, Sebastian Verfasser (DE-588)1150866586 aut Efficient, compiler-agnostic and platform-independent labeling of functions in executable programs Sebastian Eschweiler Waabs GCA-Verlag [2017] XV, 150 Seiten Illustrationen, Diagramme 21 cm txt rdacontent n rdamedia nc rdacarrier Forschen und Wissen - Informatik Dissertation Rheinische Friedrich-Wilhelms-Universität Bonn 2017 Optimierender Compiler (DE-588)4342511-2 gnd rswk-swf Binäre Funktion (DE-588)4242035-0 gnd rswk-swf Programmcode (DE-588)4734701-6 gnd rswk-swf Softwareklon (DE-588)1147495300 gnd rswk-swf Kontrollflussdiagramm (DE-588)4740359-7 gnd rswk-swf Decompiler (DE-588)115303560X gnd rswk-swf Maschinencode (DE-588)4169002-3 gnd rswk-swf Wiederherstellung Informatik (DE-588)4177289-1 gnd rswk-swf Quellcode (DE-588)4488209-9 gnd rswk-swf Bug Informatik (DE-588)4238603-2 gnd rswk-swf Paperback / softback Fachpublikum/ Wissenschaft 004 Detection of code clones binary functions efficient algorithms error-tolerant graph matching 1630: Hardcover, Softcover / Informatik, EDV (DE-588)4113937-9 Hochschulschrift gnd-content Programmcode (DE-588)4734701-6 s Quellcode (DE-588)4488209-9 s Maschinencode (DE-588)4169002-3 s Softwareklon (DE-588)1147495300 s Decompiler (DE-588)115303560X s Optimierender Compiler (DE-588)4342511-2 s Kontrollflussdiagramm (DE-588)4740359-7 s Binäre Funktion (DE-588)4242035-0 s Bug Informatik (DE-588)4238603-2 s Wiederherstellung Informatik (DE-588)4177289-1 s DE-604 GCA Gesellschaft für Computeranwendung mbH (DE-588)1065363656 pbl B:DE-101 application/pdf http://d-nb.info/1149068833/04 Inhaltsverzeichnis DNB Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=032494180&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Eschweiler, Sebastian Efficient, compiler-agnostic and platform-independent labeling of functions in executable programs Optimierender Compiler (DE-588)4342511-2 gnd Binäre Funktion (DE-588)4242035-0 gnd Programmcode (DE-588)4734701-6 gnd Softwareklon (DE-588)1147495300 gnd Kontrollflussdiagramm (DE-588)4740359-7 gnd Decompiler (DE-588)115303560X gnd Maschinencode (DE-588)4169002-3 gnd Wiederherstellung Informatik (DE-588)4177289-1 gnd Quellcode (DE-588)4488209-9 gnd Bug Informatik (DE-588)4238603-2 gnd |
| subject_GND | (DE-588)4342511-2 (DE-588)4242035-0 (DE-588)4734701-6 (DE-588)1147495300 (DE-588)4740359-7 (DE-588)115303560X (DE-588)4169002-3 (DE-588)4177289-1 (DE-588)4488209-9 (DE-588)4238603-2 (DE-588)4113937-9 |
| title | Efficient, compiler-agnostic and platform-independent labeling of functions in executable programs |
| title_auth | Efficient, compiler-agnostic and platform-independent labeling of functions in executable programs |
| title_exact_search | Efficient, compiler-agnostic and platform-independent labeling of functions in executable programs |
| title_exact_search_txtP | Efficient, compiler-agnostic and platform-independent labeling of functions in executable programs |
| title_full | Efficient, compiler-agnostic and platform-independent labeling of functions in executable programs Sebastian Eschweiler |
| title_fullStr | Efficient, compiler-agnostic and platform-independent labeling of functions in executable programs Sebastian Eschweiler |
| title_full_unstemmed | Efficient, compiler-agnostic and platform-independent labeling of functions in executable programs Sebastian Eschweiler |
| title_short | Efficient, compiler-agnostic and platform-independent labeling of functions in executable programs |
| title_sort | efficient compiler agnostic and platform independent labeling of functions in executable programs |
| topic | Optimierender Compiler (DE-588)4342511-2 gnd Binäre Funktion (DE-588)4242035-0 gnd Programmcode (DE-588)4734701-6 gnd Softwareklon (DE-588)1147495300 gnd Kontrollflussdiagramm (DE-588)4740359-7 gnd Decompiler (DE-588)115303560X gnd Maschinencode (DE-588)4169002-3 gnd Wiederherstellung Informatik (DE-588)4177289-1 gnd Quellcode (DE-588)4488209-9 gnd Bug Informatik (DE-588)4238603-2 gnd |
| topic_facet | Optimierender Compiler Binäre Funktion Programmcode Softwareklon Kontrollflussdiagramm Decompiler Maschinencode Wiederherstellung Informatik Quellcode Bug Informatik Hochschulschrift |
| url | http://d-nb.info/1149068833/04 http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=032494180&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT eschweilersebastian efficientcompileragnosticandplatformindependentlabelingoffunctionsinexecutableprograms AT gcagesellschaftfurcomputeranwendungmbh efficientcompileragnosticandplatformindependentlabelingoffunctionsinexecutableprograms |
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