Midas: safeguarding iot devices against malware via real-time behavior auditing

Y Xu, Z Yin, Y Hou, J Liu, Y Jiang - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
The number of IoT devices on the Internet has surged recently, accompanied by a barrage of
large-scale IoT malware infections breakouts. Designing security mechanisms for IoT …

CMD: co-analyzed iot malware detection and forensics via network and hardware domains

Z Zhao, Z Li, J Yu, F Zhang, X Xie… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
With the widespread use of Internet of Things (IoT) devices, malware detection has become
a hot spot for both academic and industrial communities. Existing approaches can be …

IoT malware dynamic analysis profiling system and family behavior analysis

CY Chen, SW Hsiao - … Conference on Big Data (Big Data), 2019 - ieeexplore.ieee.org
Not only the number of deployed IoT devices increases but also that of IoT malware
increases. We eager to understand the threat made by IoT malware but we lack tools to …

ELF analyzer demo: Online identification for IoT malwares with multiple hardware architectures

SM Cheng, T Ban, JW Huang… - 2020 IEEE Security …, 2020 - ieeexplore.ieee.org
This demonstration presents an automatic IoT runtime platform with a web interface, ELF
Analyzer, where suspicious ELF files uploaded by users could be executed and dynamically …

Iron-dome: Securing iot networked systems at runtime by network and device characteristics to confine malware epidemics

S Shukla, A Dhavlle, SM PD… - 2022 IEEE 40th …, 2022 - ieeexplore.ieee.org
The rapid growth of IoT networks presents an enlarged" attack space" for the adversary and
poses significant security risks on a large scale. A single device in a network that is …

[PDF][PDF] Tamer: A Sandbox for Facilitating and Automating IoT Malware Analysis with Techniques to Elicit Malicious Behavior.

S Yonamine, Y Taenaka, Y Kadobayashi - ICISSP, 2022 - pdfs.semanticscholar.org
As malware poses a significant threat to IoT devices, the technology to combat IoT malware,
like sandbox, has not received enough attention. The majority of efforts in existing …

E-spion: A system-level intrusion detection system for iot devices

A Mudgerikar, P Sharma, E Bertino - Proceedings of the 2019 ACM Asia …, 2019 - dl.acm.org
As the Internet of Things (IoT) grows at a rapid pace, there is a need for an effective and
efficient form of security tailored for IoT devices. In this paper, we introduce E-Spion, an …

IoT‐DeepSense: Behavioral Security Detection of IoT Devices Based on Firmware Virtualization and Deep Learning

J Wang, C Liu, J Xu, J Wang, S Hao… - Security and …, 2022 - Wiley Online Library
Recently, IoT devices have become the targets of large‐scale cyberattacks, and their
security issues have been increasingly serious. However, due to the limited memory and …

Persistence in linux-based iot malware

C Brierley, J Pont, B Arief, DJ Barnes… - Secure IT Systems: 25th …, 2021 - Springer
Abstract The Internet of Things (IoT) is a rapidly growing collection of “smart” devices
capable of communicating over the Internet. Being connected to the Internet brings new …

[PDF][PDF] SIMBIoTA-ML: Light-weight, Machine Learning-based Malware Detection for Embedded IoT Devices.

D Papp, G Ács, R Nagy, L Buttyán - IoTBDS, 2022 - scitepress.org
Embedded devices are increasingly connected to the Internet to provide new and innovative
applications in many domains. However, these devices can also contain security …