CRMay 13, 2017

Aiming to Detect a malware of GSM frequency

arXiv:1705.04785v11 citations
Originality Synthesis-oriented
AI Analysis

This addresses malware detection for GSM systems, but appears incremental as it builds on existing methods without clear broad impact.

The paper tackles the problem of detecting GSM frequency-related malware by proposing an algorithm based on its essential characteristics, involving memory thread detection and binary string matching, and studies its effectiveness through simulations.

In order to find a specific type of malware which is related to GSM frequency, we propose an algorithm according to the most essential characteristics of this malware. At first, detect whether or not there exists a specific thread in the memory. And then, the generated binary strings will be tried to be matched with the one in the target computer. At last, determine whether this threat occurs or not. Furthermore, we study the effective of the new method via some simulations.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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