Results 121 to 130 of about 2,905 (223)

Android malware detection with unbiased confidence guarantees

Neurocomputing, 2018
The impressive growth of smartphone devices in combination with the rising ubiquity of using mobile platforms for sensitive applications such as Internet banking, have triggered a rapid increase in mobile malware. In recent literature, many studies examine Machine Learning techniques, as the most promising approach for mobile malware detection, without
Harris Papadopoulos, Nestoras Georgiou, Charalambos Eliades, Andreas Konstantinidis 0002   +3 more
openaire   +2 more sources

Android Malware Detection Based on Factorization Machine

IEEE Access, 2019
As the popularity of Android smart phones has increased in recent years, so too has the number of malicious applications. Due to the potential for data theft mobile phone users face, the detection of malware on Android devices has become an increasingly important issue in cyber security.
Chenglin Li, Keith G. Mills, Di Niu, Rui Zhu 0007, Hongwen Zhang 0002, Husam Kinawi   +5 more
openaire   +3 more sources

Chat-GPT for Android malware detection [PDF]

The use of large-language models (LLMs) in the field of cybersecurity has been increasing greatly in recent years. With the advent of ChatGPT by OpenAI, there have been many different use cases for LLMs in cybersecurity, including in intrusion detection,
Ong, Eliezer De Zhi
core  

Malware Detection in Android Platforms [PDF]

, 2015
As one of the major operating systems adopted by mobile devices, security issues related to Android platform is gaining increasing attention in the research literature in recent years.
Liu, Peixiang, Li, Wei, Zhang, Yi
core  

Android malware detection with MH-100K: An innovative dataset for advanced research. [PDF]

Data Brief, 2023
Bragança H, Rocha V, Barcellos L, Souto E, Kreutz D, Feitosa E.   +5 more
europepmc   +1 more source

Is Malware Detection Needed for Android TV? [PDF]

The smart TV ecosystem is rapidly expanding, allowing developers to publish their applications on TV markets to provide a wide array of services to TV users.
Mehmet Ali Erturk, Erturk, Mehmet Ali, Gokhan Ozogur, Gurkas-Aydin, Zeynep, Zeynep Gurkas-Aydin, Ozogur, Gokhan   +5 more
core   +2 more sources

Android Malware Detection using Deep Learning Classification Approach [PDF]

Android devices are becoming increasingly popular, and there are more threats to Android users. This paper discusses Android malware detection using a deep learning classification approach.
Nik Zulkipli, Nurul Huda, Razak, Tajul Rosli, Mohd Fuzi, Mohd Faris, Amri, Nur Amirah, Ismail, Mohammad Hafiz, Darus, Mohamad Yusof   +5 more
core   +2 more sources

Automated Android Malware Detection Using User Feedback. [PDF]

Sensors (Basel), 2022
Duque J, Mendes G, Nunes L, de Almeida A, Serrão C.   +4 more
europepmc   +1 more source

Android malware detection method based on highly distinguishable static features and DenseNet. [PDF]

PLoS One, 2022
Yang J, Zhang Z, Zhang H, Fan J.
europepmc   +1 more source

Image-Based Android Malware Detection Using Deep Learning [PDF]

The Android operating system (OS) dominates the mobile phone OS industry, with over 70% of the market share. With the growth of Android OS-based smartphones, it has become a prime target for mobile malware attacks.
USMAN, MUHAMMAD; id_orcid, Jeremiah, Daniel, Udeze, Somadina, TA, VINH-THONG; id_orcid, RAFIQ, HUSNAIN; id_orcid   +4 more
core   +1 more source