Android ransomware detection based on a hybrid evolutionary approach in the context of highly imbalanced data

I Almomani, R Qaddoura, M Habib, S Alsoghyer… - IEEE …, 2021 - ieeexplore.ieee.org
In recent years, Ransomware has been a critical threat that attacks smartphones.
Ransomware is a kind of malware that blocks the mobile's system and prevents the user of …

Detecting ransomware attacks using intelligent algorithms: Recent development and next direction from deep learning and big data perspectives

I Bello, H Chiroma, UA Abdullahi, AY Gital… - Journal of Ambient …, 2021 - Springer
Recently, cybercriminals have infiltrated different sectors of the human venture to launch
ransomware attacks against information technology infrastructure. They demand ransom …

A hybrid deep learning approach for bottleneck detection in IoT

F Sattari, AH Farooqi, Z Qadir, B Raza, H Nazari… - IEEE …, 2022 - ieeexplore.ieee.org
Cloud computing is perhaps the most enticing innovation in the present figuring situation. It
gives an expense-effective arrangement by diminishing the enormous forthright expense of …

Android ransomware detection from traffic analysis using metaheuristic feature selection

MS Hossain, N Hasan, MA Samad… - IEEE …, 2022 - ieeexplore.ieee.org
Among the prevalent cyberattacks on Android devices, a ransomware attack is the most
common and damaging. Although there are many solutions for detecting Android …

[PDF][PDF] Enhanced android malware detection and family classification, using conversation-level network traffic features.

M Abuthawabeh, KW Mahmoud - Int. Arab J. Inf. Technol., 2020 - iajit.org
Signature-based malware detection algorithms are facing challenges to cope with the
massive number of threats in the Android environment. In this paper, conversation-level …

Behavioral based detection of android ransomware using machine learning techniques

G Kirubavathi, WR Anne - … Journal of System Assurance Engineering and …, 2024 - Springer
After the pandemic, the whole world is transforming digital, due to the increased usage of
handheld devices like smartphones and due to the evolution of the internet. All the …

Android ransomware detection using supervised machine learning techniques based on traffic analysis

A Albin Ahmed, A Shaahid, F Alnasser, S Alfaddagh… - Sensors, 2023 - mdpi.com
In today's digitalized era, the usage of Android devices is being extensively witnessed in
various sectors. Cybercriminals inevitably adapt to new security technologies and utilize …

A static feature selection-based android malware detection using machine learning techniques

A Sangal, HK Verma - 2020 International conference on smart …, 2020 - ieeexplore.ieee.org
With an increase in popularity and usage of smartphones, attackers are constantly trying to
get sensitive information from smartphones. To protect the information, researchers are …

A hybrid DL-based detection mechanism for cyber threats in secure networks

S Qureshi, J He, S Tunio, N Zhu, F Akhtar, F Ullah… - Ieee …, 2021 - ieeexplore.ieee.org
The astonishing growth of sophisticated ever-evolving cyber threats and attacks throws the
entire Internet-of-Things (IoT) infrastructure into chaos. As the IoT belongs to the …

Deep learning based malware detection for android systems: A Comparative Analysis

E Calik Bayazit, O Koray Sahingoz, B Dogan - Tehnički vjesnik, 2023 - hrcak.srce.hr
Sažetak Nowadays, cyber attackers focus on Android, which is the most popular open-
source operating system, as main target by applying some malicious software (malware) to …