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Anti-malware companies receive thousands of malware samples every day. To process this large quantity, a number of automated analysis tools were developed. These tools execute a malicious program in a controlled environment and produce reports that summarize the program's actions. Of course, the problem of analyzing the reports still remains. Recently,(More)
2 Motivation • Binary signature based detection inherently ineffective – We all know the problems... – Arms-race, pretty much a lost battle • Network based approaches evadable – Systems scan for communication artifacts – Encryption / blending thwart detection Why do we propose yet another malware detection scheme (yamds)? 3 Motivation • Don't rely on(More)
Malicious web pages that use drive-by download attacks or social engineering techniques to install unwanted software on a user's computer have become the main avenue for the propagation of malicious code. To search for malicious web pages, the first step is typically to use a crawler to collect URLs that are live on the Internet. Then, fast prefiltering(More)
Protocol reverse engineering is the process of extracting application-level specifications for network protocols. Such specifications are very helpful in a number of security-related contexts. For example, they are needed by intrusion detection systems to perform deep packet inspection , and they allow the implementation of black-box fuzzing tools.(More)
Protocol reverse engineering is the process of extracting application-level specifications for network protocols. Such specifications are very useful in a number of security-related contexts, for example, to perform deep packet inspection and black-box fuzzing, or to quickly understand custom botnet command and control (C\&C) channels.Since manual(More)
The execution of malware in an instrumented sandbox is a widespread approach for the analysis of malicious code, largely because it sidesteps the difficulties involved in the static analysis of obfuscated code. As malware analysis sandboxes increase in popularity, they are faced with the problem of malicious code detecting the instrumented environment to(More)
The steadily increasing number of malware variants is a significant problem, clogging the input queues of automated analysis tools. The generation of malware variants is made easy by automatic packers and polymorphic engines, which produce by encryption and compression a multitude of distinct versions. A great deal of time and resources could be saved by(More)
Malicious software installed on infected computers is a fundamental component of online crime. Malware development thus plays an essential role in the underground economy of cyber-crime. Malware authors regularly update their software to defeat defenses or to support new or improved criminal business models. A large body of research has focused on detecting(More)
To handle the growing flood of malware, security vendors and analysts rely on tools that automatically identify and analyze malicious code. Current systems for automated malware analysis typically follow a dynamic approach, executing an unknown program in a controlled environment (sandbox) and recording its runtime behavior. Since dynamic analysis platforms(More)
To handle the large number of malware samples appearing in the wild each day, security analysts and vendors employ automated tools to detect, classify and analyze malicious code. Because malware is typically resistant to static analysis, automated dynamic analysis is widely used for this purpose. Executing malicious software in a controlled environment(More)