Search results for "Obfuscation"
showing 3 items of 3 documents
Hypervisor-based Protection of Code
2019
The code of a compiled program is susceptible to reverse-engineering attacks on the algorithms and the business logic that are contained within the code. The main existing countermeasure to reverse-engineering is obfuscation. Generally, obfuscation methods suffer from two main deficiencies: 1) the obfuscated code is less efficient than the original and 2) with sufficient effort, the original code may be reconstructed. We propose a method that is based on cryptography and virtualization. The most valuable functions are encrypted and remain inaccessible even during their execution, thus preventing their reconstruction. A specially crafted hypervisor is responsible for decryption, execution, a…
Acquiescence to opacity
2017
Opacity may affect both the means used to implement policies and the real objectives that they pursue. Our concern with opacity is limited to the cases when it is the result of obfuscation. that is, of some effort on the part of governments or other public bodies (central banks or international organisations) to hide or misrepresent their choices. In the literature concerned with accounting for inefficient policies, there are now models in which opacity plays no significant role. This chapter provides a number of mechanisms that account for or lead to the phenomenon the authors are interested in, that is, voters preferring a policy to be opaque rather than transparent. It then discusses two…
Support vector machine integrated with game-theoretic approach and genetic algorithm for the detection and classification of malware
2013
Abstract. —In the modern world, a rapid growth of mali- cious software production has become one of the most signifi- cant threats to the network security. Unfortunately, wides pread signature-based anti-malware strategies can not help to de tect malware unseen previously nor deal with code obfuscation te ch- niques employed by malware designers. In our study, the prob lem of malware detection and classification is solved by applyin g a data-mining-based approach that relies on supervised mach ine- learning. Executable files are presented in the form of byte a nd opcode sequences and n-gram models are employed to extract essential features from these sequences. Feature vectors o btained are…