VPNFilter Malware Analysis on Cyber Threat in Smart Home Network
Source abstract
Abstract
Recently, the development of smart home technologies has played a crucial role in enhancing several real-life smart applications. They help improve the quality of life through systems designed to enhance convenience, comfort, entertainment, health of the householders, and security. Note, however, that malware attacks on smart home devices are increasing in frequency and volume. As people seek to improve and optimize comfort in their home and minimize their daily home responsibilities at the same time, this makes them attractive targets for a malware attack. Thus, attacks on smart home-based devices have emerged. The goals of this paper are to analyze the different aspects of cyber-physical threats on the smart home from a security perspective, discuss the types of attacks including advanced cyber-attacks and cyber-physical system attacks, and evaluate the impact on a smart home system in daily life. We have come up with a taxonomy focusing on cyber threat attacks that can also have potential impact on a smart home system and identify some key issues about VPNFilter malware that constitutes large-scale Internet of Things (IoT)-based botnet malware infection. We also discuss the defense mechanism against this threat and mention the most infected routers. The specific objective of this paper is to provide efficient task management and knowledge related to VPNFilter malware attack.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Advanced Malware Detection Techniques · Cloud Data Security Solutions · Network Security and Intrusion Detection
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Computer Science and Engineering, Seoul National University of Science and Technology, Seoul 01811, Korea
Dipartimento di Scienze Aziendali, Management & Innovation Systems, DISA-MIS, Universitá degli Studi di Salerno, 132-84084 Fisciano, Italy
Funding
This research was supported by the MSIT (Ministry of Science and ICT), Korea, under the ITRC (Information Technology Research Center) support program(IITP-2019-2014-1-00720) supervised by the IITP(Institute for Information & communications Technology Plan
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