Intelligent hashes for centralized malware detection

JD Park, P Szor - US Patent 8,732,825, 2014 - Google Patents
A suspicious entity is identified. An intelligent hash for the suspicious entity is generated,
wherein the intelligent hash includes a set of metadata that is specific to the suspicious entity …

Malware classification algorithm using advanced Word2vec-based Bi-LSTM for ground control stations

Y Sung, S Jang, YS Jeong, J Hyuk - Computer Communications, 2020 - Elsevier
Abstract Recently, Internet of Drones (IoD) are issued to utilize the diverse kinds of drones
for leisure, education and so on. Researchers study to prevent the situations that drones are …

Method of generating in-kernel hook point candidates to detect rootkits and the system thereof

W Chi-Wei, C Chen, CW Wang, S Shieh - US Patent 9,747,452, 2017 - Google Patents
US9747452B2 - Method of generating in-kernel hook point candidates to detect rootkits and the
system thereof - Google Patents US9747452B2 - Method of generating in-kernel hook point …

Callgraph properties of executables

D Bilar - AI Communications, 2007 - content.iospress.com
This paper examines the callgraphs of 120 malicious and 280 non-malicious executables.
Pareto models are fitted to indegree, outdegree and basic block count distributions, and a …

An advanced profile hidden Markov model for malware detection

AA Alipour, E Ansari - Intelligent Data Analysis, 2020 - content.iospress.com
The rapid growth of malicious software (malware) production in recent decades and the
increasing number of threats posed by malware to network environments, such as the …

Morphed virus family classification based on opcodes statistical feature using decision tree

B Bashari Rad, M Masrom, S Ibrahim… - … and Information Science …, 2011 - Springer
Use of morphing engine in metamorphic and polymorphic malware, and virus creation kits
aid malware authors to produce a plenty number of variants for a virus. These variants …

On callgraphs and generative mechanisms

D Bilar - Journal in Computer Virology, 2007 - Springer
This paper examines the structural features of callgraphs. The sample consisted of 120
malicious and 280 non-malicious executables. Pareto models were fitted to indegree …

Fractals, malware, and data models

HM Jaenisch, AN Potter, D Williams… - Cyber Sensing …, 2012 - spiedigitallibrary.org
We examine the hypothesis that the decision boundary between malware and non-malware
is fractal. We introduce a novel encoding method derived from text mining for converting …

A deep learning approach to the Malware classification problem using autoencoders

DR Pinto, JC Duarte, R Sant'Ana - … of the XV Brazilian Symposium on …, 2019 - dl.acm.org
Detecting malicious code or categorizing it among families has become an increasingly
difficult task. Malware1 exploits vulnerabilities and employ sophisticated techniques to avoid …

[PDF][PDF] MrKIP: Rootkit Recognition with Kernel Function Invocation Pattern.

CW Wang, CK Chen, CW Wang, SW Shieh - J. Inf. Sci. Eng., 2015 - Citeseer
Existing mechanisms tracing user-level activities such as system calls and APIs can be
circumvented by the kernel-level rootkits. In this paper, a novel system, MrKIP, is proposed to …