数据泄露的概率及其对保密性的影响

Paul M. Simon, Scott Graham
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引用次数: 0

摘要

提出了一种以分布式数据片段为特征的多通道通信体系结构,作为提高通信体系结构安全性的一种方法。然而,衡量安全性仍然具有挑战性。安全服务质量(qos)模型定义了一种方法,通过该方法可以使用数据泄漏的概率和数据损坏的概率来估计给定通信网络的安全属性。这两个概率反映了IT安全三位一体的三个方面中的两个,特别是机密性和完整性。数据泄露的概率与保密的概率直接相关,可以根据数据被截获、解密和解码的概率来估计。访问通信通道的侦听器的数量会影响这些概率,并且是qos模型所独有的,能够在发送方和接收方之间跨多个通道分割和分发数据消息。为了模拟各种通信架构的行为和恶意干扰的可能性,需要对数据泄漏的概率及其构成指标进行彻底的分析。即使侦听器知道存在多个通道,每个中间节点(如果有的话)看起来也只是有一个输入和一个输出。可能有一个或多个听众,他们可能合作,也可能不合作。即使侦听器获得了对多个通道的访问权,解密、解码或重新组装碎片数据仍然是一个挑战。本文的分析将从授权用户和对手的角度探讨机密性的可能性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Probability of Data Leakage and Its Impacts on Confidentiality
A multi-channel communication architecture featuring distributed fragments of data is presented as a method for improving security available in a communication architecture. However, measuring security remains challenging. The Quality of Secure Service (QoSS) model defines a manner by which the probability of data leakage and the probability of data corruption may be used to estimate security properties for a given communication network. These two probabilities reflect two of the three aspects of the IT security triad, specifically confidentiality and integrity. The probability of data leakage is directly related to the probability of confidentiality and may be estimated based on the probabilities of data interception, decryption, and decoding. The number of listeners who have access to the communication channels influences these probabilities, and unique to the QoSS model, the ability to fragment and distribute data messages across multiple channels between sender and receiver. To simulate the behaviors of various communication architectures and the possibility of malicious interference, the probability of data leakage and its constituent metrics require a thorough analysis. Even if a listener is aware that multiple channels exist, each intermediate node (if any) simply appears to have one input and one output. There may be one or more listeners, and they may or may not be working cooperatively. Even if the listener(s) gains access to more than one channel, there is still the challenge of decrypting, decoding, or reassembling the fragmented data. The analysis presented herein will explore the probability of confidentiality from both the authorized user’s and the adversary’s perspective.
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