-Currently, different forms of ransomware are increasingly threatening Internet users. Modern ransomware encrypts important user data and it is only possible to recover it once a ransom has been paid. In this paper we show how Software-Defined Networking (SDN) can be utilized to improve ransomware mitigation. In more detail, we analyze the behavior of popular ransomware -CryptoWall -and, based on this knowledge, we propose two real-time mitigation methods. Then we designed the SDN-based system, implemented using OpenFlow, which facilitates a timely reaction to this threat, and is a crucial factor in the case of crypto ransomware. What is important is that such a design does not significantly affect overall network performance. Experimental results confirm that the proposed approach is feasible and efficient.

Ransomware is currently the key threat for individual as well as corporate Internet users. Especially dangerous is crypto ransomware that encrypts important user data and it is only possible to recover it once a ransom has been paid. Therefore devising efficient and effective countermeasures is a rising necessity. In this paper we present a novel Software-Defined Networking (SDN) based detection approach that utilizes characteristics of ransomware communication. Based on the observation of network communication of two crypto ransomware families, namely CryptoWall and Locky we conclude that analysis of the HTTP messages' sequences and their respective content sizes is enough to detect such threats. We show feasibility of our approach by designing and evaluating the proof-of-concept SDNbased detection system. Experimental results confirm that the proposed approach is feasible and efficient.

The paper presents the analysis of the CryptoWall ransomware network behaviour. In this approach a HoneyPot technology as well as the automatic run-time malware analytical system called Maltester were used. We present the practical results of the analyses, technologies and tools used, and the gained experience with dynamic analysis of ransomware software in a dedicated environment. Most of the data was collected with the use of the HoneyPot infrastructure created and deployed in the network of the Institute of Computer Science WUT.Streszczenie. Praca przedstawia analizę zachowania sieciowego złośliwego oprogramowania CryptoWall typu ransomware. W badaniach wykorzystano technologię HoneyPot oraz system automatycznej analizy działania złośliwego oprogramowania w czasie jego wykonywania o nazwie Maltester. Zaprezentowano zarówno uzyskane wyniki analiz, wykorzystane technologie i narzędzia jak i doświadczenia zebrane podczas analizy oprogramowania typu ransomware w autorskim środowisku analitycznym. Większość danych zebrana została z wykorzystaniem infrastruktury HoneyPot stworzonej i wdrożonej w sieci Instytutu Informatyki Politechniki Warszawskiej. (Dynamiczna analiza aktywności sieciowej oprogramowania CryptoWall typu ransomware).

Compared to cryptography, steganography is a less discussed domain. However, there is a recent trend of exploiting various information hiding techniques to empower malware, for instance to bypass security frameworks of mobile devices or to exfiltrate sensitive data. This is mostly due to the need to counteract increasingly sophisticated security mechanisms, such as code analysis, runtime countermeasures, or real-time traffic inspection tools. In this perspective, this paper presents malware exploiting information hiding in a broad sense, i.e., it does not focus on classical covert channels, but also discusses other camouflage techniques. Differently from other works, this paper solely focuses on real-world threats observed in the 2011 -2017 timeframe. The observation indicates a growing number of malware equipped with some form of data hiding capabilities and a lack of effective and universal countermeasures.

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