Cyber attacks are currently blooming, as the attackers reap signiﬁcant proﬁts from them andface a limited risk when compared to committing the ‘‘classical’’ crimes. One of the major componentsthat leads to the successful compromising of the targeted system is malicious software. It allows using thevictim’smachineforvariousnefariouspurposes,e.g.,makingitapartofthebotnet,miningcryptocurrencies,or holding hostage the data stored there. At present, the complexity, proliferation, and variety of malwarepose a real challenge for the existing countermeasures and require their constant improvements. That iswhy, in this paper we ﬁrst perform a detailed meta-review of the existing surveys related to malware and itsdetection techniques, showing an arms race between these two sides of a barricade. On this basis, we reviewthe evolution of modern threats in the communication networks, with a particular focus on the techniquesemploying information hiding. Next, we present the bird’s eye view portraying the main development trendsin detection methods with a special emphasis on the machine learning techniques. The survey is concludedwith the description of potential future research directions in the ﬁeld of malware detection.
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