The main goal of this thesis is the development of malware analysis methods to help human analysts better comprehend the threat it represents. The first achievement in this thesis is the large-scale and in-depth analysis of malware protection techniques. In particular, we have studied hundreds of malware samples, carefully selected according to their threat level. By automatically measuring a set of original characteristics, we have been able to demonstrate the existence of a particularly prevalent model of protection in these programmes that is based on self-modifying code and on a strict delimitation between protection code and payload code. Then, we have developed an identification method for cryptographic implementations adapted to protected machine language programmes. We have validated our approach by identifying several implementations of cryptographic algorithms ---the majority unidentified by existing tools--- and this even in particularly obscure malware protection schemes. Finally, we have developed what is, to our knowledge, the first emulation environment for botnets involving several thousands of machines. Thanks to this, we were able to validate the viability of the use of a vulnerability in the peer-to-peer protocol in the Waledac botnet to take over this network.
