NeighborWatcher：Detecting Piggybacked Smartphone Applications with Their Family Members

ZHANG Huan; WU Jian-liang; TANG Jun-jie; BAN Tao; YU Yan; GUO Shan-qing; WANG Li-ming; HU An-lei

doi:10.3969/j.issn.0372-2112.2014.08.029

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NeighborWatcher：Detecting Piggybacked Smartphone Applications with Their Family Members

更新时间：2025-07-16

- NeighborWatcher：Detecting Piggybacked Smartphone Applications with Their Family Members
- Acta Electronica Sinica Vol. 42, Issue 8, Pages: 1642-1646(2014)
- 作者机构：
  
  1. 山东大学计算机科学与技术学院,山东,济南,250100
  2. 日本信息与通信技术研究所, 日本东京 1848795
  3. 南京理工大学计算机学院,江苏,南京,210094
  4. 山东省软件工程重点实验室,山东,济南,250100
  5. 中国互联网络信息中心,北京,100010
  6. 山东大学计算机科学与技术学院,山东,济南,250100
  7. 日本信息与通信技术研究所日本东京 1848795
  8. 南京理工大学计算机学院,江苏,南京,210094
  9. 山东省软件工程重点实验室,山东,济南,250100
  10. 中国互联网络信息中心,北京,100010
- 作者简介：
- 基金信息：
  
  National Natural Science Foundation of China (No.61173139, No.61303243);Science and Technology Research and Development Project of Shandong Province (No.2010GGX10117);Open Laboratory Foundation for Internet Basic Technologies (No.K201206007)
- DOI：10.3969/j.issn.0372-2112.2014.08.029
  CLC： TP309
- Published：2014
- 稿件说明：
移动端阅览
ZHANG Huan, WU Jian-liang, TANG Jun-jie, et al. NeighborWatcher：Detecting Piggybacked Smartphone Applications with Their Family Members[J]. Acta Electronica Sinica, 2014, 42(8): 1642-1646.
DOI：

ZHANG Huan, WU Jian-liang, TANG Jun-jie, et al. NeighborWatcher：Detecting Piggybacked Smartphone Applications with Their Family Members[J]. Acta Electronica Sinica, 2014, 42(8): 1642-1646. DOI： 10.3969/j.issn.0372-2112.2014.08.029.

摘要

经过对多个手机恶意应用程序的分析，发现其与被感染程序所属家族的不同版本在程序语义方面存在很大的相似性，并且这种相似性与原家族中不同版本之间的相似性有很大不同.基于该事实，本文借助于分层聚类技术，针对函数的调用图，提出了一种基于程序家族关系的恶意手机应用检测方法并构建了一个NeighborWatcher系统.实验结果表明当每个程序家族都含有四个以上的成员时，NeighborWatcher系统对附加恶意应用的检测率可以达到92.86%.

Abstract

Through the analysis of some mobile malwares

we found that malware is similar with its original application in semantics of the program

and the similarity is different with the similarity between other members of the family.Based on this fact

by means of hierarchical clustering technology for the function call graph

we propose a program based on family relationships to detect the malicious mobile applications and build a system named as NeighborWatcher.Experimental results show that when each family contains four or more members

the detection rate of Piggybacked application can reach 92.86%.

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