MACE: Model-inference-Assisted Concolic Exploration for Protocol and Vulnerability Discovery
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Summary
This paper uses a combination of symbolic and concrete execution to build an abstract model of the analyzed application, in the form of a finite-state automaton, and uses the model to guide further state-space exploration, which increases the code coverage and exploration depth.
- Type
- article
- Published
- 2011-08-08
- Cited by
- 134
- References
- 39
- OpenAlex
- https://openalex.org/W77946476
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:811610
Keywords
Computer science, Finite-state machine, Software, Code (set theory), Linear subspace
References
- Introduction to algorithms [2nd ed.]
- Automated Whitebox Fuzz Testing
- Insights from the Inside: A View of Botnet Management from Infiltration
- Discoverer: Automatic Protocol Reverse Engineering from Network Traces
- Black Box Checking
- Colin de la Higuera: Grammatical inference: learning automata and grammars
- KLEE: unassisted and automatic generation of high-coverage tests for complex systems programs
- Learning Regular Sets from Queries and Counterexamples
- CUTE: a concolic unit testing engine for C
- Polyglot: automatic extraction of protocol message format using dynamic binary analysis
- A method for synthesizing sequential circuits
- DART: directed automated random testing
- Symbolic execution and program testing
- SYNERGY: a new algorithm for property checking
- Prospex: Protocol Specification Extraction
- EXE: automatically generating inputs of death
- Tupni: automatic reverse engineering of input formats
- Design, Deployment, and Use of the DETER Testbed
- Inference and analysis of formal models of botnet command and control protocols
- Dispatcher: enabling active botnet infiltration using automatic protocol reverse-engineering
Cited by
- INFERENCE-BASED FORENSICS FOR EXTRACTING INFORMATION FROM DIVERSE SOURCES
- MetaSymploit: Day-One Defense against Script-based Attacks with Security-Enhanced Symbolic Analysis
- Gatling: Automatic Attack Discovery in Large-Scale Distributed Systems
- Automated performance attack discovery in distributed system implementations
- Transparently improving regression testing using symbolic execution
- Framework Of Security Mechanism In Cloud Computing By Denial Of Service Bandwidth Allowance Parameters
- Leveraging State Information for Automated Attack Discovery in Transport Protocol Implementations
- Scaling Concolic Execution of Binary Programs for Security Applications
- Discovering specification violations in networked software systems
- PeerPress: utilizing enemies' P2P strength against them
- DASE: Document-Assisted Symbolic Execution for Improving Automated Software Testing
- A software-hardware architecture for self-protecting data
- TLV: abstraction through testing, learning, and validation
- Graph based Binary Code Execution Path Exploration Platform for Dynamic Symbolic Execution
- iPanda: A comprehensive malware analysis tool
- Hybrid learning: interface generation through static, dynamic, and symbolic analysis
- The BORG: Nanoprobing Binaries for Buffer Overreads
- Branch Obfuscation Using Code Mobility and Signal
- Gatling
- Sigma*: symbolic learning of input-output specifications
Related papers
- KLEE: unassisted and automatic generation of high-coverage tests for complex systems programs
- Learning Regular Sets from Queries and Counterexamples
- DART: directed automated random testing
- CUTE: a concolic unit testing engine for C
- Automated Whitebox Fuzz Testing
- Inference and analysis of formal models of botnet command and control protocols
- Polyglot: automatic extraction of protocol message format using dynamic binary analysis
- Symbolic execution and program testing