Adrian-Stefan Popescu

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As the number and impact of online threats increases exponentially, the automatic classification of malware becomes increasingly important in the antivirus business. The heavy use of machine learning in this field raises the following question: “How much will a trained machine-learning model resist in time against the ever-changing malware binary code?” In(More)
As most of the malware nowadays use Internet as their main doorway to infect a new system, it has become imperative for security vendors to provide cloud-based solutions that can filter and block malicious URLs. This paper presents different practical considerations related to this problem. The key points that we focus on are the usage of different machine(More)
Detection of malicious software is a current problem which can be solved via several approaches. Among these are signature based detection, heuristic detection and behavioral analysis. In the last year the number of malicious files has increased exponentially. At the same time, automated obfuscation methods (used to generate malicious files with similar(More)
As malware industry grows, so does the means of infecting a computer or device evolve. One of the most common infection vector is to use the Internet as an entry point. Not only that this method is easy to use, but due to the fact that URLs come in different forms and shapes, it is really difficult to distinguish a malicious URL from a benign one.(More)
Over the last couple of years there has been a substantial increase of malicious attacks that are using the Internet as an infection vector. One solution to counter this problem is to implement a filter at the network connection level. Due to the large amount of data that has to be filtered in real-time, any practical approach has to consider both memory(More)
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