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2021-05-13
Susukailo, Vitalii, Opirskyy, Ivan, Vasylyshyn, Sviatoslav.  2020.  Analysis of the attack vectors used by threat actors during the pandemic. 2020 IEEE 15th International Conference on Computer Sciences and Information Technologies (CSIT). 2:261—264.

This article describes attacks methods, vectors and technics used by threat actors during pandemic situations in the world. Identifies common targets of threat actors and cyber-attack tactics. The article analyzes cybersecurity challenges and specifies possible solutions and improvements in cybersecurity. Defines cybersecurity controls, which should be taken against analyzed attack vectors.

S, Naveen, Puzis, Rami, Angappan, Kumaresan.  2020.  Deep Learning for Threat Actor Attribution from Threat Reports. 2020 4th International Conference on Computer, Communication and Signal Processing (ICCCSP). :1–6.
Threat Actor Attribution is the task of identifying an attacker responsible for an attack. This often requires expert analysis and involves a lot of time. There had been attempts to detect a threat actor using machine learning techniques that use information obtained from the analysis of malware samples. These techniques will only be able to identify the attack, and it is trivial to guess the attacker because various attackers may adopt an attack method. A state-of-the-art method performs attribution of threat actors from text reports using Machine Learning and NLP techniques using Threat Intelligence reports. We use the same set of Threat Reports of Advanced Persistent Threats (APT). In this paper, we propose a Deep Learning architecture to attribute Threat actors based on threat reports obtained from various Threat Intelligence sources. Our work uses Neural Networks to perform the task of attribution and show that our method makes the attribution more accurate than other techniques and state-of-the-art methods.
2020-10-05
Fowler, Stuart, Sitnikova, Elena.  2019.  Toward a framework for assessing the cyber-worthiness of complex mission critical systems. 2019 Military Communications and Information Systems Conference (MilCIS). :1–6.
Complex military systems are typically cyber-physical systems which are the targets of high level threat actors, and must be able to operate within a highly contested cyber environment. There is an emerging need to provide a strong level of assurance against these threat actors, but the process by which this assurance can be tested and evaluated is not so clear. This paper outlines an initial framework developed through research for evaluating the cyber-worthiness of complex mission critical systems using threat models developed in SysML. The framework provides a visual model of the process by which a threat actor could attack the system. It builds on existing concepts from system safety engineering and expands on how to present the risks and mitigations in an understandable manner.