Results 41 to 50 of about 46,394 (182)
Unsupervised Anomaly-based Malware Detection using Hardware Features [PDF]
Recent works have shown promise in using microarchitectural execution patterns to detect malware programs. These detectors belong to a class of detectors known as signature-based detectors as they catch malware by comparing a program's execution pattern (
Sethumadhavan, Simha +2 more
core +4 more sources
Metamorphic malware detection using base malware identification approach [PDF]
ABSTRACTMalware is a malicious program that is intentionally developed to harm computer systems. Because the metamorphic malwares are advanced in nature, they mutate their code in each generation by employing code obfuscation techniques to thwart detection. Conventional scanners even fail to detect all variants of such malware.
Devendra Kumar Mahawer, A. Nagaraju
openaire +1 more source
The ever-increasing growth of online services and smart connectivity of devices have posed the threat of malware to computer system, android-based smart phones, Internet of Things (IoT)-based systems.
Santosh K. Smmarwar +2 more
doaj +1 more source
Research on Application of Attention-CNN in Malware Detection
The attack of malware has become one of the most major threats to the Internet. What??s more, the existing malware data are huge and have multiple features. In order to extract the characteristics better and master the behaviors of malware, Attention-CNN
MA Dan, WAN Liang, CHENG Qiqin, SUN Zhiqiang
doaj +1 more source
Intensive Malware Detection Approach based on Data Mining
Malicious software, sometimes known as malware, is software designed to harm a computer, network, or any of the connected resources. Without the user's knowledge, malware can spread throughout their computer system. Malware is typically disseminated via
Israa Ezzat Salem, Karim Hashim Al-Saedi
doaj +1 more source
Malware detection based on semi-supervised learning with malware visualization
The traditional signature-based detection method requires detailed manual analysis to extract the signatures of malicious samples, and requires a large number of manual markers to maintain the signature library, which brings a great time and resource costs, and makes it difficult to adapt to the rapid generation and mutation of malware.
Tan Gao, Lan Zhao, Xudong Li, Wen Chen
openaire +3 more sources
On the Effectiveness of Perturbations in Generating Evasive Malware Variants
Malware variants are generated using various evasion techniques to bypass malware detectors, so it is important to understand what properties make them evade malware detection techniques.
Beomjin Jin +3 more
doaj +1 more source
Automatically combining static malware detection techniques [PDF]
Malware detection techniques come in many different flavors, and cover different effectiveness and efficiency trade-offs. This paper evaluates a number of machine learning techniques to combine multiple static Android malware detection techniques using ...
Coppens, Bart +3 more
core +1 more source
Learning the PE Header, Malware Detection with Minimal Domain Knowledge
Many efforts have been made to use various forms of domain knowledge in malware detection. Currently there exist two common approaches to malware detection without domain knowledge, namely byte n-grams and strings. In this work we explore the feasibility
Nicholas, Charles +2 more
core +1 more source
As a result of the rapid advancement of mobile and internet technology, a plethora of new mobile security risks has recently emerged. Many techniques have been developed to address the risks associated with Android malware.
Abimbola G. Akintola +9 more
doaj +1 more source

