Visible to the public Biblio

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A
Tanana, D., Tanana, G..  2020.  Advanced Behavior-Based Technique for Cryptojacking Malware Detection. 2020 14th International Conference on Signal Processing and Communication Systems (ICSPCS). :1—4.
With rising value and popularity of cryptocurrencies, they inevitably attract cybercriminals seeking illicit profits within blockchain ecosystem. Two of the most popular methods are ransomware and cryptojacking. Ransomware, being the first and more obvious threat has been extensively studied in the past. Unlike that, scientists have often neglected cryptojacking, because it’s less obvious and less harmful than ransomware. In this paper, we’d like to propose enhanced detection program to combat cryptojacking, additionally briefly touching history of cryptojacking, also known as malicious mining and reviewing most notable previous attempts to detect and combat cryptojacking. The review would include out previous work on malicious mining detection and our current detection program is based on its previous iteration, which mostly used CPU usage heuristics to detect cryptojacking. However, we will include additional metrics for malicious mining detection, such as network usage and calls to cryptographic libraries, which result in a 93% detection rate against the selected number of cryptojacking samples, compared to 81% rate achieved in previous work. Finally, we’ll discuss generalization of proposed detection technique to include GPU cryptojackers.
B
Tanana, D..  2020.  Behavior-Based Detection of Cryptojacking Malware. 2020 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology (USBEREIT). :0543—0545.
With rise of cryptocurrency popularity and value, more and more cybercriminals seek to profit using that new technology. Most common ways to obtain illegitimate profit using cryptocurrencies are ransomware and cryptojacking also known as malicious mining. And while ransomware is well-known and well-studied threat which is obvious by design, cryptojacking is often neglected because it's less harmful and much harder to detect. This article considers question of cryptojacking detection. Brief history and definition of cryptojacking are described as well as reasons for designing custom detection technique. We also propose complex detection technique based on CPU load by an application, which can be applied to both browser-based and executable-type cryptojacking samples. Prototype detection program based on our technique was designed using decision tree algorithm. The program was tested in a controlled virtual machine environment and achieved 82% success rate against selected number of cryptojacking samples. Finally, we'll discuss generalization of proposed technique for future work.
D
Tanana, D..  2019.  Decentralized Labor Record System Based on Wavelet Consensus Protocol. 2019 International Multi-Conference on Engineering, Computer and Information Sciences (SIBIRCON). :0496—0499.

The labor market involves several untrusted actors with contradicting objectives. We propose a blockchain based system for labor market, which provides benefits to all participants in terms of confidence, transparency, trust and tracking. Our system would handle employment data through new Wavelet blockchain platform. It would change the job market enabling direct agreements between parties without other participants, and providing new mechanisms for negotiating the employment conditions. Furthermore, our system would reduce the need in existing paper workflow as well as in major internet recruiting companies. The key differences of our work from other blockchain based labor record systems are usage of Wavelet blockchain platform, which features metastability, directed acyclic graph system and Turing complete smart contracts platform and introduction of human interaction inside the smart contracts logic, instead of automatic execution of contracts. The results are promising while inconclusive and we would further explore potential of blockchain solutions for labor market problems.