6 citations · 6 across the 1 of their papers we have counts for
5 papers
Similarity-based Android Malware Detection Using Hamming Distance of Static Binary Features
Rahim Taheri, Meysam Ghahramani, Reza Javidan +3
In this paper, we develop four malware detection methods using Hamming distance to find similarity between samples which are first nearest neighbors (FNN), all nearest neighbors (A…
On Defending Against Label Flipping Attacks on Malware Detection Systems
Rahim Taheri, Reza Javidan, Mohammad Shojafar +3
Label manipulation attacks are a subclass of data poisoning attacks in adversarial machine learning used against different applications, such as malware detection. These types of a…
Can Machine Learning Model with Static Features be Fooled: an Adversarial Machine Learning Approach
Rahim Taheri, Reza Javidan, Mohammad Shojafar +2
The widespread adoption of smartphones dramatically increases the risk of attacks and the spread of mobile malware, especially on the Android platform. Machine learning-based solut…
FeatureAnalytics: An approach to derive relevant attributes for analyzing Android Malware
Deepa K, Radhamani G, Vinod P +3
Ever increasing number of Android malware, has always been a concern for cybersecurity professionals. Even though plenty of anti-malware solutions exist, a rational and pragmatic a…
FOCAN: A Fog-supported Smart City Network Architecture for Management of Applications in the Internet of Everything Environments
Paola G. Vinueza Naranjo, Zahra Pooranian, Mohammad Shojafar +2
Smart city vision brings emerging heterogeneous communication technologies such as Fog Computing (FC) together to substantially reduce the latency and energy consumption of Interne…