为了解决TCP(transmission control protocol)和UDP(user datagram protocol)在诸如卫星信道和无线信道等高误码率信道中遇到的问题,提出了一种基于跨层设计的简单可靠UDP协议。通过增加2个字节的包头建立了确认机制和重传机制,保证了...为了解决TCP(transmission control protocol)和UDP(user datagram protocol)在诸如卫星信道和无线信道等高误码率信道中遇到的问题,提出了一种基于跨层设计的简单可靠UDP协议。通过增加2个字节的包头建立了确认机制和重传机制,保证了数据包的可靠交付;通过增加1个字节的跨层信息,建立了自适应变包长机制,提高了协议效率。分析和仿真结果表明,该协议兼有UDP协议高效和TCP协议保证可靠交付的优点,可以很好地适用于卫星、无线等高误码率信道。展开更多
随着网络技术的发展,广泛互联互通的异构网络间的信息交互越来越频繁。为有效保障信息跨网安全实时交换,提出了一种抗隐蔽通道的网络隔离通信方案(NICS,network isolation communication scheme)。建立了NICS理论模型,基于信息论理论证...随着网络技术的发展,广泛互联互通的异构网络间的信息交互越来越频繁。为有效保障信息跨网安全实时交换,提出了一种抗隐蔽通道的网络隔离通信方案(NICS,network isolation communication scheme)。建立了NICS理论模型,基于信息论理论证明了该方案的正确性,并给出了具体的实施方案。安全特性分析表明,NICS可有效解决不同网络的通信协议均存在潜在的数据分组大小隐蔽通道与状态信息隐蔽通道的问题;在交互相同信息量的前提下,可实现与物理隔离等价的抗隐蔽通道的安全效果。展开更多
Mobile apps are known to be rich sources for gathering privacy-sensitive information about smartphone users.Despite the presence of encryption,passive network adversaries who have access to the network infrastructure ...Mobile apps are known to be rich sources for gathering privacy-sensitive information about smartphone users.Despite the presence of encryption,passive network adversaries who have access to the network infrastructure can eavesdrop on the traffic and therefore fingerprint a user’s app by means of packet-level traffic analysis.Since it is difficult to prevent the adversaries from accessing the network,providing secrecy in hostile environments becomes a serious concern.In this study,we propose AdaptiveMutate,a privacy-leak thwarting technique to defend against the statistical traffic analysis of apps.First,we present a method for the identification of mobile apps using traffic analysis.Further,we propose a confusion system in which we obfuscate packet lengths,and/or inter-arrival time information leaked by the mobile traffic to make it hard for intruders to differentiate between the altered app traffic and the actual one using statistical analysis.Our aim is to shape one class of app traffic to obscure its features with the minimum overhead.Our system strives to dynamically maximize its efficiency by matching each app with the corresponding most dissimilar app.Also,AdaptiveMutate has an adaptive capability that allows it to choose the most suitable feature to mutate,depending on the type of apps analyzed and the classifier used,if known.We evaluate the efficiency of our model by conducting a comprehensive simulation analysis that mutates different apps to each other using AdaptiveMutate.We conclude that our algorithm is most efficient when we mutate a feature of one app to its most dissimilar one in another app.When applying the identification technique,we achieve a classification accuracy of 91.1%.Then,using our obfuscation technique,we are able to reduce this accuracy to 7%.Also,we test our algorithm against a recently published approach for mobile apps classification and we are able to reduce its accuracy from 94.8%to 17.9%.Additionally,we analyze the tradeoff between the shaping cost and traffic privacy protection,specifically,the associated overhead and the feasibility for real-time implementation.展开更多
文摘为了解决TCP(transmission control protocol)和UDP(user datagram protocol)在诸如卫星信道和无线信道等高误码率信道中遇到的问题,提出了一种基于跨层设计的简单可靠UDP协议。通过增加2个字节的包头建立了确认机制和重传机制,保证了数据包的可靠交付;通过增加1个字节的跨层信息,建立了自适应变包长机制,提高了协议效率。分析和仿真结果表明,该协议兼有UDP协议高效和TCP协议保证可靠交付的优点,可以很好地适用于卫星、无线等高误码率信道。
文摘随着网络技术的发展,广泛互联互通的异构网络间的信息交互越来越频繁。为有效保障信息跨网安全实时交换,提出了一种抗隐蔽通道的网络隔离通信方案(NICS,network isolation communication scheme)。建立了NICS理论模型,基于信息论理论证明了该方案的正确性,并给出了具体的实施方案。安全特性分析表明,NICS可有效解决不同网络的通信协议均存在潜在的数据分组大小隐蔽通道与状态信息隐蔽通道的问题;在交互相同信息量的前提下,可实现与物理隔离等价的抗隐蔽通道的安全效果。
文摘Mobile apps are known to be rich sources for gathering privacy-sensitive information about smartphone users.Despite the presence of encryption,passive network adversaries who have access to the network infrastructure can eavesdrop on the traffic and therefore fingerprint a user’s app by means of packet-level traffic analysis.Since it is difficult to prevent the adversaries from accessing the network,providing secrecy in hostile environments becomes a serious concern.In this study,we propose AdaptiveMutate,a privacy-leak thwarting technique to defend against the statistical traffic analysis of apps.First,we present a method for the identification of mobile apps using traffic analysis.Further,we propose a confusion system in which we obfuscate packet lengths,and/or inter-arrival time information leaked by the mobile traffic to make it hard for intruders to differentiate between the altered app traffic and the actual one using statistical analysis.Our aim is to shape one class of app traffic to obscure its features with the minimum overhead.Our system strives to dynamically maximize its efficiency by matching each app with the corresponding most dissimilar app.Also,AdaptiveMutate has an adaptive capability that allows it to choose the most suitable feature to mutate,depending on the type of apps analyzed and the classifier used,if known.We evaluate the efficiency of our model by conducting a comprehensive simulation analysis that mutates different apps to each other using AdaptiveMutate.We conclude that our algorithm is most efficient when we mutate a feature of one app to its most dissimilar one in another app.When applying the identification technique,we achieve a classification accuracy of 91.1%.Then,using our obfuscation technique,we are able to reduce this accuracy to 7%.Also,we test our algorithm against a recently published approach for mobile apps classification and we are able to reduce its accuracy from 94.8%to 17.9%.Additionally,we analyze the tradeoff between the shaping cost and traffic privacy protection,specifically,the associated overhead and the feasibility for real-time implementation.
