[HTML][HTML] N-gram MalGAN: Evading machine learning detection via feature n-gram

E Zhu, J Zhang, J Yan, K Chen, C Gao - Digital communications and …, 2022 - Elsevier
In recent years, many adversarial malware examples with different feature strategies,
especially GAN and its variants, have been introduced to handle the security threats, eg …

[PDF][PDF] Insider threat detection based on NLP word embedding and machine learning

MA Haq, MAR Khan, M Alshehri - Intell. Autom. Soft Comput, 2022 - researchgate.net
The growth of edge computing, the Internet of Things (IoT), and cloud computing have been
accompanied by new security issues evolving in the information security infrastructure …

BCTrustFrame: enhancing trust management via blockchain and IPFS in 6G era

W Li, W Meng - IEEE Network, 2022 - ieeexplore.ieee.org
Beginning in 2030, sixth generation (6G) mobile communication is expected to play a key
role by collecting billions of things, humans, and robots, resulting in zettabytes of digital …

[PDF][PDF] A model for blockchain-based privacy-preserving for big data users on the internet of thing

ILH Alsammak, MF Alomari, IS Nasir… - Indones. J. Electr. Eng …, 2022 - researchgate.net
Recently, with the emergence and growth of the internet of things (IoT) as a promising
vehicle for sustainable development, the concept of 'smart cities' has advanced significantly …

[HTML][HTML] A multiplayer game model to detect insiders in wireless sensor networks

I Kantzavelou, L Maglaras, PF Tzikopoulos… - PeerJ Computer …, 2022 - peerj.com
Insiders might have incentives and objectives opposed to those of the belonging
organization. It is hard to detect them because of their privileges that partially protect them. In …

工业互联网边缘终端初始接入可信度量方法研究

于亚, 伏玉笋 - 物联网学报, 2022 - infocomm-journal.com
离散制造业的发展呈现智能, 开放和协同的趋势, 大量异构设备接入工业互联网,
给安全带来了严重挑战, 因此, 引入信任管理和对设备进行可信度量的初始接入显得尤为重要 …

[PDF][PDF] Fuzzy Based Latent Dirichlet Allocation for Intrusion Detection in Cloud Using ML.

S Ranjithkumar… - Computers, Materials & …, 2022 - pdfs.semanticscholar.org
The growth of cloud in modern technology is drastic by provisioning services to various
industries where data security is considered to be common issue that influences the …

Evaluating intrusion sensitivity allocation with supervised learning in collaborative intrusion detection

W Li, F Tian, J Li, Y Xiang - Concurrency and Computation …, 2022 - Wiley Online Library
Network intrusions are a big security threat to current computer networks. For protection,
collaborative intrusion detection networks (CIDNs) are developed attempting to reach better …

Implementation of Blockchain with Machine Learning Intrusion Detection System for Defending IoT Botnet and Cloud Networks.

S Siddamsetti, M Srivenkatesh - Ingénierie des Systèmes d' …, 2022 - search.ebscohost.com
Significant research has been done on combining intrusion detection and blockchain to
increase data privacy and find both current and future threats. This research suggests a …

A MALWARE VARIANT RESISTANT TO TRADITIONAL ANALYSIS TECHNIQUES A FORENSIC ANALYSIS OF ANDROID MALWARE

K Shoraimov, I Akhmadjonov - Евразийский журнал …, 2022 - in-academy.uz
In today's world, the word malware is synonymous with mysterious programs that spread
havoc and sow destruction upon the computing system it infects. These malware are …