Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Mobile devices are especially vulnerable nowadays to malware attacks, thanks to the current trend of increased app downloads. Despite the significant security and privacy concerns it received, effective malware detection (MD) remains a significant challenge.  tackles this challenge by introducing a streaminglized machine learning-based MD framework, StormDroid: (i) The core of StormDroid is based on machine learning, enhanced with a novel combination of contributed features that  observed over a fairly large collection of data set; and (ii)  streaminglize the whole MD process to support large-scale analysis, yielding an efficient and scalable MD technique that observes app behaviors statically and dynamically. Evaluated on roughly 8,000 applications, our combination of contributed features improves MD accuracy by almost 10% compared with state-of-the-art antivirus systems; in parallel our streaminglized process, StormDroid, further improves efficiency rate by approximately three times than a single thread.
['Sen Chen', 'Minhui Xue', 'Zhushou Tang', 'Lihua Xu', 'Haojin Zhu']
I am writing a research paper on a idea StormDroid: A Streaminglized Machine Learning-Based System for Detecting Android Malware
[{"from": "human", "value": "I am writing a research paper on a idea StormDroid: A Streaminglized Machine Learning-Based System for Detecting Android Malware"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Mobile devices are especially vulnerable nowadays to malware attacks, thanks to the current trend of increased app downloads. Despite the significant security and privacy concerns it received, effective malware detection (MD) remains a significant challenge.  tackles this challenge by introducing a streaminglized machine learning-based MD framework, StormDroid: (i) The core of StormDroid is based on machine learning, enhanced with a novel combination of contributed features that  observed over a fairly large collection of data set; and (ii)  streaminglize the whole MD process to support large-scale analysis, yielding an efficient and scalable MD technique that observes app behaviors statically and dynamically. Evaluated on roughly 8,000 applications, our combination of contributed features improves MD accuracy by almost 10% compared with state-of-the-art antivirus systems; in parallel our streaminglized process, StormDroid, further improves efficiency rate by approximately three times than a single thread."}]