In recent years,with the increase in the price of cryptocurrencies,the number of mali-cious cryptomining software has increased signifi-cantly.With their powerful spreading ability,cryp-tomining malware can unknowingly occupy our re-sources,harm our interests,and damage more legit-imate assets.However,although current traditional rule-based malware detection methods have a low false alarm rate,they have a relatively low detection rate when faced with a large volume of emerging mal-ware.Even though common machine learning-based or deep learning-based methods have certain ability to learn and detect unknown malware,the characteris-tics they learn are single and independent,and cannot be learned adaptively.Aiming at the above problems,we propose a deep learning model with multi-input of multi-modal features,which can simultaneously ac-cept digital features and image features on different dimensions.The model in turn includes parallel learn-ing of three sub-models and ensemble learning of an-other specific sub-model.The four sub-models can be processed in parallel on different devices and can be further applied to edge computing environments.The model can adaptively learn multi-modal features and output prediction results.The detection rate of our model is as high as 97.01％ and the false alarm rate is only 0.63％.The experimental results prove the ad-vantage and effectiveness of the proposed method.

Wenjuan Lian;Guoqing Nie;Yanyan Kang;Bin Jia;Yang Zhang

College of Computer Science & Engineering,Shandong University of Science and Technology,Qingdao,Shandong 266590,China;College of Foreign Languages,Shandong University of Science and Technology,Qingdao,Shandong 266590,China

中国通信（英文版）

[1]Wenjuan Lian;Guoqing Nie;Yanyan Kang;Bin Jia;Yang Zhang-.Cryptomining Malware Detection Based on Edge Computing-Oriented Multi-Modal Features Deep Learning)[J].中国通信（英文版）,2022(02):174-185

Cryptomining,cious,cryptomining,cryp,tomining,unknowingly,legit

Malware,Detection,Based,Edge,Computing,Oriented,Multi,Modal,Features,Deep,Learning,In,recent,years,price,cryptocurrencies,number,mali,software,has,increased,signifi,cantly,With,their,powerful,spreading,ability,malware,occupy,sources,harm,interests,damage,more,imate,assets,However,although,current,traditional,rule,detection,methods,have,low,false,alarm,rate,they,relatively,when,faced,large,volume,emerging,Even,common,machine,learning,deep,certain,unknown,characteris,tics,single,independent,cannot,learned,adaptively,Aiming,above,problems,multi,input,modal,features,which,simultaneously,cept,digital,image,different,dimensions,turn,includes,parallel,three,sub,models,ensemble,other,specific,four,processed,devices,further,applied,edge,computing,environments,output,prediction,results,high,only,experimental,prove,vantage,effectiveness,proposed

0.532006