The prevalence of smartphones is deeply embedded in modern society,impacting various aspects of our lives.Their versatility and functionalities have fundamentally changed how we communicate,work,seek entertainment,and...The prevalence of smartphones is deeply embedded in modern society,impacting various aspects of our lives.Their versatility and functionalities have fundamentally changed how we communicate,work,seek entertainment,and access information.Among the many smartphones available,those operating on the Android platform dominate,being the most widely used type.This widespread adoption of the Android OS has significantly contributed to increased malware attacks targeting the Android ecosystem in recent years.Therefore,there is an urgent need to develop new methods for detecting Android malware.The literature contains numerous works related to Android malware detection.As far as our understanding extends,we are the first ones to identify dangerous combinations of permissions and system calls to uncover malicious behavior in Android applications.We introduce a novel methodology that pairs permissions and system calls to distinguish between benign and malicious samples.This approach combines the advantages of static and dynamic analysis,offering a more comprehensive understanding of an application’s behavior.We establish covalent bonds between permissions and system calls to assess their combined impact.We introduce a novel technique to determine these pairs’Covalent Bond Strength Score.Each pair is assigned two scores,one for malicious behavior and another for benign behavior.These scores serve as the basis for classifying applications as benign or malicious.By correlating permissions with system calls,the study enables a detailed examination of how an app utilizes its requested permissions,aiding in differentiating legitimate and potentially harmful actions.This comprehensive analysis provides a robust framework for Android malware detection,marking a significant contribution to the field.The results of our experiments demonstrate a remarkable overall accuracy of 97.5%,surpassing various state-of-the-art detection techniques proposed in the current literature.展开更多
为确保数字经济高质量发展,加强移动应用的个人隐私保护至关重要。隐私设置和权限请求设置作为当前移动服务商向用户提供的主要隐私保护技术措施,其有效性受到争议,并未得到用户广泛的使用或采纳,这可能是因为用户无法通过隐私设置选择...为确保数字经济高质量发展,加强移动应用的个人隐私保护至关重要。隐私设置和权限请求设置作为当前移动服务商向用户提供的主要隐私保护技术措施,其有效性受到争议,并未得到用户广泛的使用或采纳,这可能是因为用户无法通过隐私设置选择和控制移动应用收集的个人信息种类、使用目的与共享对象,且权限请求设置操作流程较为复杂。要想切实发挥隐私保护技术的积极效果,其应具备的技术特征不容小觑。本研究从给予用户对个人信息披露的细粒度控制的视角,针对现有隐私设置和权限请求设置提出两种技术特征,即隐私设置可操作性与权限请求设置有效性,并基于信号传递理论,探究这两种技术特征对用户拒绝提供个人信息和提供虚假个人信息意愿(简称“隐私保护行为意愿”)的影响机理。本研究采用基于情景的实验方法,共收集334份有效数据,应用PLS-SEM(partial least squares-structural equation modeling)方法进行实证分析。研究结果发现,本研究提出的两种技术特征对用户的隐私保护行为意愿具有显著的直接负向影响,并通过隐私担忧间接负向影响用户的隐私保护行为意愿;这两种技术特征对用户隐私保护行为意愿具有显著的正向交互作用。本研究丰富和拓展了隐私保护技术设计与用户信息行为研究,并为移动服务商设计有效的隐私保护技术以提升竞争优势提供了启示,从而促进数字经济高质量发展。展开更多
文摘The prevalence of smartphones is deeply embedded in modern society,impacting various aspects of our lives.Their versatility and functionalities have fundamentally changed how we communicate,work,seek entertainment,and access information.Among the many smartphones available,those operating on the Android platform dominate,being the most widely used type.This widespread adoption of the Android OS has significantly contributed to increased malware attacks targeting the Android ecosystem in recent years.Therefore,there is an urgent need to develop new methods for detecting Android malware.The literature contains numerous works related to Android malware detection.As far as our understanding extends,we are the first ones to identify dangerous combinations of permissions and system calls to uncover malicious behavior in Android applications.We introduce a novel methodology that pairs permissions and system calls to distinguish between benign and malicious samples.This approach combines the advantages of static and dynamic analysis,offering a more comprehensive understanding of an application’s behavior.We establish covalent bonds between permissions and system calls to assess their combined impact.We introduce a novel technique to determine these pairs’Covalent Bond Strength Score.Each pair is assigned two scores,one for malicious behavior and another for benign behavior.These scores serve as the basis for classifying applications as benign or malicious.By correlating permissions with system calls,the study enables a detailed examination of how an app utilizes its requested permissions,aiding in differentiating legitimate and potentially harmful actions.This comprehensive analysis provides a robust framework for Android malware detection,marking a significant contribution to the field.The results of our experiments demonstrate a remarkable overall accuracy of 97.5%,surpassing various state-of-the-art detection techniques proposed in the current literature.
文摘为确保数字经济高质量发展,加强移动应用的个人隐私保护至关重要。隐私设置和权限请求设置作为当前移动服务商向用户提供的主要隐私保护技术措施,其有效性受到争议,并未得到用户广泛的使用或采纳,这可能是因为用户无法通过隐私设置选择和控制移动应用收集的个人信息种类、使用目的与共享对象,且权限请求设置操作流程较为复杂。要想切实发挥隐私保护技术的积极效果,其应具备的技术特征不容小觑。本研究从给予用户对个人信息披露的细粒度控制的视角,针对现有隐私设置和权限请求设置提出两种技术特征,即隐私设置可操作性与权限请求设置有效性,并基于信号传递理论,探究这两种技术特征对用户拒绝提供个人信息和提供虚假个人信息意愿(简称“隐私保护行为意愿”)的影响机理。本研究采用基于情景的实验方法,共收集334份有效数据,应用PLS-SEM(partial least squares-structural equation modeling)方法进行实证分析。研究结果发现,本研究提出的两种技术特征对用户的隐私保护行为意愿具有显著的直接负向影响,并通过隐私担忧间接负向影响用户的隐私保护行为意愿;这两种技术特征对用户隐私保护行为意愿具有显著的正向交互作用。本研究丰富和拓展了隐私保护技术设计与用户信息行为研究,并为移动服务商设计有效的隐私保护技术以提升竞争优势提供了启示,从而促进数字经济高质量发展。
