The evolution of technology in 1990s resulted in the enormous growth of smartphones and the propagation of mobile applications (App) that marked new opportunities for healthcare centers and medical education. Apps hav...The evolution of technology in 1990s resulted in the enormous growth of smartphones and the propagation of mobile applications (App) that marked new opportunities for healthcare centers and medical education. Apps have altered health services from patient’s health monitoring to specialist’s appointments and consultations from specialized health facilities. It can be argued that a healthy society can bring forth sustainable economic development to its full potential while an unhealthy society cannot. However, a free movement of people, labour and right to residence which was built across East Africa (EA) borders enabled Tanzania and Kenya borders to have enormous interactions. Subsequently, increase the risk of highly communicable diseases such as Tuberculosis and Sexually transmitted infections in such a way that medical attention is unavoidable along the borders. Statistically, Android Operating System (OS) owns 83% of Africa’s mobile OS market. In addition, 25,794,560 internet users reported by Tanzania Communications Regulatory Authority (TCRA) together with the 22.86 million internet users provided by Kenya Digital which is equivalent to 46% and 43% of internet penetration in year 2020, disclose the need for Android mobile application for mapping health facilities both online and offline using Google map API, which will solve residents’ need to healthcare services on the presence or shortage of internet connections;using either Swahili or English language via Smartphone devices. The App incorporates Monitoring and Evaluation (M & E) tool for tracking application usage which will ease Admin’s task to generate daily and monthly reports in Excel and Comma-Separated Values (CSV) formats. The developed system received positive feedback from EA citizens and residents in the Arusha region and Namanga border crossing where 90.2% of the system evaluation conducted between Dec 2020 and Apr 2021 agreed upon App usage.展开更多
在万物互联的云时代,云应用程序编程接口(API)是数字经济建设和服务化软件开发的关键数字基础设施。然而,云API数量的持续增长给用户决策和推广带来挑战,设计有效的推荐方法成为亟待解决的重要问题。现有研究多利用调用偏好、搜索关键...在万物互联的云时代,云应用程序编程接口(API)是数字经济建设和服务化软件开发的关键数字基础设施。然而,云API数量的持续增长给用户决策和推广带来挑战,设计有效的推荐方法成为亟待解决的重要问题。现有研究多利用调用偏好、搜索关键词或二者结合进行建模,主要解决为给定Mashup推荐合适云API的问题,未考虑开发者对个性化高阶互补云API的实际需求。该文提出一种基于个性化张量分解的高阶互补云API推荐方法(Personalized Tensor Decomposition based High-order Complementary cloud API Recommendation,PTDHCR)。首先,将Mashup与云API之间的调用关系,以及云API与云API之间的互补关系建模为三维张量,并利用RECAL张量分解技术对这两种关系进行共同学习,以挖掘云API之间的个性化非对称互补关系。然后,考虑到不同互补关系对推荐结果的影响程度不同,构建个性化高阶互补感知网络,充分利用Mashup、查询云API以及候选云API的多模态特征,动态计算Mashup对不同查询和候选云API之间互补关系的关注程度。在此基础上,将个性化互补关系拓展到高阶,得到候选云API与查询云API集合的整体个性化互补性。最后,利用两个真实云API数据集进行实验,结果表明,相较于传统方法,PTDHCR在挖掘个性化互补关系和推荐方面具有较大的优势。展开更多
The paper proposes a conference control model between a web server and a telecom application server,referred to as the Conference Directed Graph(CDG) ,and describes an asynchronous communication mechanism between them...The paper proposes a conference control model between a web server and a telecom application server,referred to as the Conference Directed Graph(CDG) ,and describes an asynchronous communication mechanism between them. The Corba Interface Definition Language(IDL) interfaces are defined,and a message sequence chart is illustrated. This web conference control model provides conference users with a new approach to manage and control a conference and the participants. The performance of the system prototype is analyzed and verified in the 863 project named "The Multi-media and Mobile Services Enabled Soft-switch System".展开更多
Ransomware,particularly crypto-ransomware,remains a significant cybersecurity challenge,encrypting victim data and demanding a ransom,often leaving the data irretrievable even if payment is made.This study proposes an...Ransomware,particularly crypto-ransomware,remains a significant cybersecurity challenge,encrypting victim data and demanding a ransom,often leaving the data irretrievable even if payment is made.This study proposes an early detection approach to mitigate such threats by identifying ransomware activity before the encryption process begins.The approach employs a two-tiered approach:a signature-based method using hashing techniques to match known threats and a dynamic behavior-based analysis leveraging Cuckoo Sandbox and machine learning algorithms.A critical feature is the integration of the most effective Application Programming Interface call monitoring,which analyzes system-level interactions such as file encryption,key generation,and registry modifications.This enables the detection of both known and zero-day ransomware variants,overcoming limitations of traditional methods.The proposed technique was evaluated using classifiers such as Random Forest,Support Vector Machine,and K-Nearest Neighbors,achieving a detection accuracy of 98%based on 26 key ransomware attributes with an 80:20 training-to-testing ratio and 10-fold cross-validation.By combining minimal feature sets with robust behavioral analysis,the proposed method outperforms existing solutions and addresses current challenges in ransomware detection,thereby enhancing cybersecurity resilience.展开更多
传统的勒索软件动态检测方法需要收集较长时间的软件行为,难以满足勒索软件及时检测的需求.本文从勒索软件及时检测的角度出发,提出了“勒索软件检测关键时间段(Critical Time Periods for Ransomware Detection,CTP)”的概念,并基于CT...传统的勒索软件动态检测方法需要收集较长时间的软件行为,难以满足勒索软件及时检测的需求.本文从勒索软件及时检测的角度出发,提出了“勒索软件检测关键时间段(Critical Time Periods for Ransomware Detection,CTP)”的概念,并基于CTP的要求提出了一种基于应用程序编程接口(Application Programming Interface,API)短序列的勒索软件早期检测方法(Ransomware Early Detection Method based on short API Sequence,REDMS).REDMS以软件在CTP内执行时所调用的API短序列为分析对象,通过n-gram模型和词频-逆文档频率算法对采集到的API短序列进行计算以生成特征向量,然后运用机器学习算法建立检测模型对勒索软件进行早期检测.实验结果显示,REDMS在API采集时段为前7s且使用随机森林算法时,分别能以98.2%、96.7%的准确率检测出已知和未知的勒索软件样本.展开更多
针对基于Android应用程序申请权限的检测过于粗粒度的问题,提出了基于敏感应用程序编程接口(application program interface,API)配对的恶意应用检测方法。通过反编译应用程序提取危险权限对应的敏感API,将敏感API两两配对分别构建恶意...针对基于Android应用程序申请权限的检测过于粗粒度的问题,提出了基于敏感应用程序编程接口(application program interface,API)配对的恶意应用检测方法。通过反编译应用程序提取危险权限对应的敏感API,将敏感API两两配对分别构建恶意应用无向图与良性应用无向图,再根据恶意应用和良性应用在敏感API调用上的差异分配相同边不同的权重,以此检测Android恶意应用。实验结果表明,提出的方法可以有效地检测出Android恶意应用程序,具有现实意义。展开更多
文摘The evolution of technology in 1990s resulted in the enormous growth of smartphones and the propagation of mobile applications (App) that marked new opportunities for healthcare centers and medical education. Apps have altered health services from patient’s health monitoring to specialist’s appointments and consultations from specialized health facilities. It can be argued that a healthy society can bring forth sustainable economic development to its full potential while an unhealthy society cannot. However, a free movement of people, labour and right to residence which was built across East Africa (EA) borders enabled Tanzania and Kenya borders to have enormous interactions. Subsequently, increase the risk of highly communicable diseases such as Tuberculosis and Sexually transmitted infections in such a way that medical attention is unavoidable along the borders. Statistically, Android Operating System (OS) owns 83% of Africa’s mobile OS market. In addition, 25,794,560 internet users reported by Tanzania Communications Regulatory Authority (TCRA) together with the 22.86 million internet users provided by Kenya Digital which is equivalent to 46% and 43% of internet penetration in year 2020, disclose the need for Android mobile application for mapping health facilities both online and offline using Google map API, which will solve residents’ need to healthcare services on the presence or shortage of internet connections;using either Swahili or English language via Smartphone devices. The App incorporates Monitoring and Evaluation (M & E) tool for tracking application usage which will ease Admin’s task to generate daily and monthly reports in Excel and Comma-Separated Values (CSV) formats. The developed system received positive feedback from EA citizens and residents in the Arusha region and Namanga border crossing where 90.2% of the system evaluation conducted between Dec 2020 and Apr 2021 agreed upon App usage.
文摘在万物互联的云时代,云应用程序编程接口(API)是数字经济建设和服务化软件开发的关键数字基础设施。然而,云API数量的持续增长给用户决策和推广带来挑战,设计有效的推荐方法成为亟待解决的重要问题。现有研究多利用调用偏好、搜索关键词或二者结合进行建模,主要解决为给定Mashup推荐合适云API的问题,未考虑开发者对个性化高阶互补云API的实际需求。该文提出一种基于个性化张量分解的高阶互补云API推荐方法(Personalized Tensor Decomposition based High-order Complementary cloud API Recommendation,PTDHCR)。首先,将Mashup与云API之间的调用关系,以及云API与云API之间的互补关系建模为三维张量,并利用RECAL张量分解技术对这两种关系进行共同学习,以挖掘云API之间的个性化非对称互补关系。然后,考虑到不同互补关系对推荐结果的影响程度不同,构建个性化高阶互补感知网络,充分利用Mashup、查询云API以及候选云API的多模态特征,动态计算Mashup对不同查询和候选云API之间互补关系的关注程度。在此基础上,将个性化互补关系拓展到高阶,得到候选云API与查询云API集合的整体个性化互补性。最后,利用两个真实云API数据集进行实验,结果表明,相较于传统方法,PTDHCR在挖掘个性化互补关系和推荐方面具有较大的优势。
基金the National High-Tech Research and De-velopment Plan of China (No.2001AA121021)the Na-tional Research Foundation for the Doctoral Program of Higher Education of China (No.20020013004)+2 种基金the Na-tional Grand Fundamental Research 973 Program of China (No.2003CB314806)the National Natural Science Foundation for Distinguished Young Scholars of China (No.60125101)the Cheung Kong Scholar’s Program and the Promotion Project for Creative Teams of the Ministry of Education (Networking Theory and Tech-nology in Telecommunication) (No.IRT0410).
文摘The paper proposes a conference control model between a web server and a telecom application server,referred to as the Conference Directed Graph(CDG) ,and describes an asynchronous communication mechanism between them. The Corba Interface Definition Language(IDL) interfaces are defined,and a message sequence chart is illustrated. This web conference control model provides conference users with a new approach to manage and control a conference and the participants. The performance of the system prototype is analyzed and verified in the 863 project named "The Multi-media and Mobile Services Enabled Soft-switch System".
基金funded by the National University of Sciences and Technology(NUST)supported by the Basic Science Research Program through the National Research Foundation of Korea(NRF),funded by the Ministry of Education(2021R1IIA3049788).
文摘Ransomware,particularly crypto-ransomware,remains a significant cybersecurity challenge,encrypting victim data and demanding a ransom,often leaving the data irretrievable even if payment is made.This study proposes an early detection approach to mitigate such threats by identifying ransomware activity before the encryption process begins.The approach employs a two-tiered approach:a signature-based method using hashing techniques to match known threats and a dynamic behavior-based analysis leveraging Cuckoo Sandbox and machine learning algorithms.A critical feature is the integration of the most effective Application Programming Interface call monitoring,which analyzes system-level interactions such as file encryption,key generation,and registry modifications.This enables the detection of both known and zero-day ransomware variants,overcoming limitations of traditional methods.The proposed technique was evaluated using classifiers such as Random Forest,Support Vector Machine,and K-Nearest Neighbors,achieving a detection accuracy of 98%based on 26 key ransomware attributes with an 80:20 training-to-testing ratio and 10-fold cross-validation.By combining minimal feature sets with robust behavioral analysis,the proposed method outperforms existing solutions and addresses current challenges in ransomware detection,thereby enhancing cybersecurity resilience.
文摘传统的勒索软件动态检测方法需要收集较长时间的软件行为,难以满足勒索软件及时检测的需求.本文从勒索软件及时检测的角度出发,提出了“勒索软件检测关键时间段(Critical Time Periods for Ransomware Detection,CTP)”的概念,并基于CTP的要求提出了一种基于应用程序编程接口(Application Programming Interface,API)短序列的勒索软件早期检测方法(Ransomware Early Detection Method based on short API Sequence,REDMS).REDMS以软件在CTP内执行时所调用的API短序列为分析对象,通过n-gram模型和词频-逆文档频率算法对采集到的API短序列进行计算以生成特征向量,然后运用机器学习算法建立检测模型对勒索软件进行早期检测.实验结果显示,REDMS在API采集时段为前7s且使用随机森林算法时,分别能以98.2%、96.7%的准确率检测出已知和未知的勒索软件样本.
文摘针对基于Android应用程序申请权限的检测过于粗粒度的问题,提出了基于敏感应用程序编程接口(application program interface,API)配对的恶意应用检测方法。通过反编译应用程序提取危险权限对应的敏感API,将敏感API两两配对分别构建恶意应用无向图与良性应用无向图,再根据恶意应用和良性应用在敏感API调用上的差异分配相同边不同的权重,以此检测Android恶意应用。实验结果表明,提出的方法可以有效地检测出Android恶意应用程序,具有现实意义。
