Privacy protection in pervasive systems: State of the art and technical challenges

Pervasive and mobile computing applications are dramatically increasing the amount of personal data released to service providers as well as to third parties. Data includes geographical and indoor positions of individuals, their movement patterns as well as sensor-acquired data that may reveal individuals’ physical conditions, habits, and, in general, information that may lead to undesired consequences like unsolicited advertisement or more serious ones like discrimination and stalking.In this survey paper, at first we consider representative classes of pervasive applications, and identify the requirements they impose in terms of privacy and trade-off with service quality. Then, we review the most prominent privacy preservation approaches, we discuss and summarize them in terms of the requirements.Finally, we take a more holistic view of the privacy problem by discussing other aspects that turn out to be crucial for the widespread adoption of privacy enhancing technologies. We discuss technical challenges like the need for tools augmenting the awareness of individuals and to capture their privacy preferences, as well as legal and economic challenges. Indeed, on one side privacy solutions must comply to ethical and legal requirements, and not prevent profitable business models, while on the other side it is unlikely that privacy preserving solutions will become practical and effective without new regulations.     

基于控制流混淆转换的代码保护技术

混淆转换作为一种防止逆向工程的代码保护技术伴随着Java,语言的迅速发展应运而生。以保护软件代码、提高逆向工程代价为目标,从破解与反破解的角度对控制流混淆转换技术进行了研究,提出了重构程序整体控制结构及隐藏用于控制转换的短暂变量的方法,并通过试验对控制流混淆转换给程序带来的时间和空间上的过载进行了客观评析。     

一种分布式环境下的代码保护方案

总结软件迷乱技术的发展现状,提出了一种分布式环境下基于控制流迷乱变换的代码保护方案。该方案利用分布式环境下各并发进程的局部状态构造全局不透明分支,并利用并发进程间的同步通信模式改变局部状态以增强迷乱强度,经性能分析认为该方案具有较好的隐蔽性和鲁棒性,能有效抵抗分布式环境下的窃听攻击。     

Generalising the array split obfuscation

An obfuscation is a behaviour-preserving program transformation whose aim is to make a program “harder to understand”. Obfuscations are mainly applied to make reverse engineering of object-oriented programs more difficult. In this paper, we propose a fresh approach by obfuscating abstract data-types allowing us to develop structure-dependent obfuscations that would otherwise (traditionally) not be available. We regard obfuscation as data refinement enabling us to produce equations for proving correctness. We model the data-type operations as functional programs making our proofs easy to construct.We show how we can generalise an imperative obfuscation - an array split - so that we can apply it to abstract data-types and we give specific examples for lists and matrices. We develop a theorem which allows us, under certain conditions, to produce obfuscated operations directly. Our approach also allows us to produce random obfuscations and we give an example for our list data-type.     

New lightweight Anti-SAT block design and obfuscation technique to thwart removal attack

Logic locking has emerged as a prominent technique to protect an integrated circuit from piracy, overbuilding, and hardware Trojans. Most of the well-known logic locking techniques are vulnerable to satisfiability (SAT) based attack. Though several SAT-resistant logic locking techniques such as Anti-SAT block (ASB) are reported that increase the time to decipher the secret key, the existing techniques are either vulnerable to signal probability skew (SPS) based removal attack or require significant design overhead. Therefore, a new lightweight ASB design and obfuscation technique is proposed that effectively integrate and obfuscates the ASB in the design to thwart removal attack. We first propose a new ASB design/integration approach that effectively thwarts the structural/functional analysis based removal attack with minimum overhead. Further, we also propose an ASB obfuscation approach that shifts the inverter deep in the circuit using De Morgan's law and replaces an ASB gate with a key-gate to thwart SPS based removal attack. Moreover, a new algorithm is proposed that inserts the ASB in the locked design to achieve desired output corruptibility. Finally, a new INV/BUFF key-gate is proposed that constructs the ASB with reduced overhead over the XOR/XNOR. Experimental evaluation on ISCAS-85 benchmarks shows that our ASB design and obfuscation approaches, on an average, reduce area overhead by 25.5% and 22% respectively, and effectively prevent removal attack without reducing any security.     

使用混合开发技术快速构建跨平台移动应用系统

移动应用已成为人们日常生活不可或缺的一部分,但是由于移动终端的多样性,构建一个兼容多个平台的移动应用成本非常高昂且耗时。本文将Ionic、Cordova、Gulp、SpringMVC等多种技术有效结合,提出一种快速构建跨平台移动应用系统的方法。该系统不仅具有“一次开发,多处运行”的跨平台移动应用特点,同时能够解决普通跨平台应用代码混淆、版本升级等问题,并且提供一种快速整合企业原有多个app的解决方案。     

基于不透明谓词的软件抗动态逆向分析研究

传统的不透明谓词对谓词内部逻辑结构进行复杂化,难以有效应对软件的动态逆向分析。通过插入运行环境检测代码并将检测结果返回给不透明谓词,动态选择分支路径使软件仅在安全环境下运行被保护代码,防止代码被动态分析。引入一般和关键节点概念,提高谓词内部逻辑结构的复杂度并使用形式化方法进行描述。实验证明,成功检测出虚拟机和调试器并避开了受保护代码;在静态指令统计上与使用变形隐匿的方法对比,具有更好的隐匿效果。     

计算机软件的防篡改技术

随着软件产业的快速发展,软件产品的保护已成为一个十分重要的问题.本文详细介绍了防止计算机软件被篡改的各种技术,并分析了它们的优缺点.     

AdaptiveMutate: a technique for privacy preservation

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.