BarkDroid: Android Malware Detection Using Bark Frequency Cepstral Coefficients
نویسندگان
چکیده
Since their inaugural releases in 2007, Google’s Android and Apple’s iOS have grown to dominate the mobile OS market share. Currently, they jointly possess over 99% of global share with being leading Operating System choice worldwide, controlling close 70% Mobile devices enabled exponential growth a plethora applications that play key roles enabling many use cases are pivotal our daily lives. On other hand, access large pool potential end users is available both legitimate nefarious applications, thus making burgeoning target malicious applications. Current malware detection solutions rely on tedious, time-consuming, knowledge-based, manual processes identify malware. This paper presents BarkDroid, novel technique uses low-level Bark Frequency Cepstral Coefficients audio features detect The results obtained outperform using same datasets. BarkDroid achieved 97.9% accuracy, 98.5% precision, an F1 score 98.6%, shorter execution times.
منابع مشابه
Detection of Replay Attacks Using Single Frequency Filtering Cepstral Coefficients
Automatic speaker verification systems are vulnerable to spoofing attacks. Recently, various countermeasures have been developed for detecting high technology attacks such as speech synthesis and voice conversion. However, there is a wide gap in dealing with replay attacks. In this paper, we propose a new feature for replay attack detection based on single frequency filtering (SFF), which provi...
متن کاملAndroid Malware Detection Using Backpropagation Neural Network
The rapid growing adoption of android operating system around the world affects the growth of malware that attacks this platform. One possible solution to overcome the threat of malware is building a comprehensive system to detect existing malware. This paper proposes multilayer perceptron artificial neural network trained with backpropagation algorithm to determine an application is malware or...
متن کاملAndroid Malware Detection Using SVM and GA
Security is one of the main concerns for Smartphone users today. As the power and features of Smartphone’s increase, so has their vulnerability for attacks by viruses etc. An Android OS could be attacked by hackers: Because it’s Open platform, Users will access the Internet intensively and everyone can develop applications for Android. In previous technique described that how security can be im...
متن کاملDroidMat: Android Malware Detection
Recently, the threat of Android malware is spreading rapidly, especially those repackaged Android malware. Although understanding Android malware using dynamic analysis can provide a comprehensive view, it is still subjected to high cost in environment deployment and manual efforts in investigation. In this study, we propose a static feature-based mechanism to provide a static analyst paradigm ...
متن کاملPermission-Based Android Malware Detection
Mobile devices have become popular in our lives since they offer almost the same functionality as personal computers. Among them, Android-based mobile devices had appeared lately and, they were now an ideal target for attackers. Android-based smartphone users can get free applications from Android Application Market. But, these applications were not certified by legitimate organizations and the...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Indonesian Journal of Information Systems
سال: 2022
ISSN: ['2623-0119', '2623-2308']
DOI: https://doi.org/10.24002/ijis.v5i1.6266