A survey of android malware detection with deep neural models
Deep Learning (DL) is a disruptive technology that has changed the landscape of cyber
security research. Deep learning models have many advantages over traditional Machine …
security research. Deep learning models have many advantages over traditional Machine …
Cyber security meets artificial intelligence: a survey
J Li - Frontiers of Information Technology & Electronic …, 2018 - Springer
There is a wide range of interdisciplinary intersections between cyber security and artificial
intelligence (AI). On one hand, AI technologies, such as deep learning, can be introduced …
intelligence (AI). On one hand, AI technologies, such as deep learning, can be introduced …
Cyber security in smart cities: a review of deep learning-based applications and case studies
D Chen, P Wawrzynski, Z Lv - Sustainable Cities and Society, 2021 - Elsevier
On the one hand, smart cities have brought about various changes, aiming to revolutionize
people's lives. On the other hand, while smart cities bring better life experiences and great …
people's lives. On the other hand, while smart cities bring better life experiences and great …
GDroid: Android malware detection and classification with graph convolutional network
The dramatic increase in the number of malware poses a serious challenge to the Android
platform and makes it difficult for malware analysis. In this paper, we propose a novel …
platform and makes it difficult for malware analysis. In this paper, we propose a novel …
Detection of cross-site scripting (XSS) attacks using machine learning techniques: a review
With the rising demand for E-commerce, Social Networking websites, it has become
essential to develop security protocols over the World Wide Web that can provide security …
essential to develop security protocols over the World Wide Web that can provide security …
A survey on machine learning in Internet of Things: Algorithms, strategies, and applications
In the IoT and WSN era, large number of connected objects and sensing devices are
dedicated to collect, transfer, and generate a huge amount of data for a wide variety of fields …
dedicated to collect, transfer, and generate a huge amount of data for a wide variety of fields …
Evaluating shallow and deep neural networks for network intrusion detection systems in cyber security
RK Vigneswaran, R Vinayakumar… - 2018 9th …, 2018 - ieeexplore.ieee.org
Intrusion detection system (IDS) has become an essential layer in all the latest ICT system
due to an urge towards cyber safety in the day-to-day world. Reasons including uncertainty …
due to an urge towards cyber safety in the day-to-day world. Reasons including uncertainty …
Deep learning for android malware defenses: a systematic literature review
Malicious applications (particularly those targeting the Android platform) pose a serious
threat to developers and end-users. Numerous research efforts have been devoted to …
threat to developers and end-users. Numerous research efforts have been devoted to …
DroidMalwareDetector: A novel Android malware detection framework based on convolutional neural network
AT Kabakus - Expert Systems with Applications, 2022 - Elsevier
Smartphones have become an integral part of our daily lives thanks to numerous reasons.
While benefitting from what they offer, it is critical to be aware of the existence of malware in …
While benefitting from what they offer, it is critical to be aware of the existence of malware in …
Deep feature extraction and classification of android malware images
The Android operating system has gained popularity and evolved rapidly since the previous
decade. Traditional approaches such as static and dynamic malware identification …
decade. Traditional approaches such as static and dynamic malware identification …