Enlace del recurso
Enlace del recurso

“…Traditional approaches such as static and dynamic malware identification techniques require a lot of human intervention and resources to design the malware classification model. …”
Enlace del recurso
Enlace del recurso
Enlace del recurso

“…Malware has seriously threatened the safety of computer systems for a long time. …”
Enlace del recurso
Enlace del recurso
Enlace del recurso

“…The various application markets are facing an exponential growth of Android malware. Every day, thousands of new Android malware applications emerge. …”
Enlace del recurso
Enlace del recurso
Enlace del recurso

“…The widespread usage of mobile devices and their seamless adaptation to each user’s needs through useful applications (apps) makes them a prime target for malware developers. Malware is software built to harm the user, e.g., to access sensitive user data, such as banking details, or to hold data hostage and block user access. …”
Enlace del recurso
Enlace del recurso
Enlace del recurso

“…In recent years, massive development in the malware industry changed the entire landscape for malware development. …”
Enlace del recurso
Enlace del recurso
Enlace del recurso

“…For efficient malware removal, determination of malware threat levels, and damage estimation, malware family classification plays a critical role. …”
Enlace del recurso
Enlace del recurso

Enlace del recurso

Enlace del recurso

Enlace del recurso

Enlace del recurso

“…However, most present studies lack a deep understanding of IoT malware and its various aspects. As understanding IoT malware is the preliminary base of research, in this work, we present an IoT malware taxonomy with 100 attributes based on the IoT malware categories, attack types, attack surfaces, malware distribution architecture, victim devices, victim device architecture, IoT malware characteristics, access mechanisms, programming languages, and protocols. …”
Enlace del recurso
Enlace del recurso
Enlace del recurso

“…In earlier years, most malware attacks were against Android smartphones. …”
Enlace del recurso
Enlace del recurso

“…In this work, we present a static malware detection system to detect Portable Executable (PE) malware in Windows environment and classify them as benign or malware with high accuracy. …”
Enlace del recurso
Enlace del recurso
Enlace del recurso

“…We outline here the mathematical expression of a diffusion model for cellphones malware transmitted through Bluetooth channels. In particular, we provide the deterministic formula underlying the proposed infection model, in its equivalent recursive (simple but computationally heavy) and closed form (more complex but efficiently computable) expression.…”
Enlace del recurso
Enlace del recurso
Enlace del recurso

“…Malware has become one of the most serious threats to computer information system and the current malware detection technology still has very significant limitations. …”
Enlace del recurso
Enlace del recurso
Enlace del recurso

“…With the continuous development of machine learning algorithms, the learning-based Android malware detection system for IoT devices has gradually increased. …”
Enlace del recurso
Enlace del recurso
Enlace del recurso

Enlace del recurso
Enlace del recurso
Enlace del recurso

“…Given the fast evolution of Android malware releases, it is practically not feasible to manually detect malware apps in the Android ecosystem. …”
Enlace del recurso
Enlace del recurso
Enlace del recurso

“…The family homology determination of malware has become a research hotspot as the number of malware variants are on the rise. …”
Enlace del recurso
Enlace del recurso
Enlace del recurso