Preserving Privacy Against Side-Channel Leaks

The privacy preserving issues have received significant attentions in various domains. Various models and techniques have been proposed to achieve optimal privacy with minimal costs. However, side-channel leakages (such as, publicly-known algorithms of data publishing, observable traffic information in web application, fine-grained readings in smart metering) further complicate the process of privacy preservation. In this thesis, we make the first effort on investigating a general framework to model side-channel attacks across different domains and applying the framework to various categories of applications. In privacy-preserving data publishing with publicly-known algorithms, we first theoretically study a generic strategy independent of data utility measures and syntactic privacy properties. We then propose an efficient approach to preserving diversity. In privacy-preserving traffic padding in Web applications, we first propose a formal PPTP model to quantify the privacies and costs based on the key observation about the similarity between data publishing and traffic padding. We then introduce randomness into the previous solutions to provide background knowledge-resistant privacy guarantee. In privacy-preserving smart metering, we propose a light-weight approach to simultaneously preserving privacy on both billing and consumption aggregation based on the key observation about the privacy issue beyond the fine-grained readings

The microdata analysis system at the U.S. Census Bureau

The U.S. Census Bureau has the responsibility to release high quality data products while maintaining the confidentiality promised to all respondents under Title 13 of the U.S. Code. This paper describes a Microdata Analysis System (MAS) that is currently under development, which will allow users to receive certain statistical analyses of Census Bureau data, such as crosstabulations and regressions, without ever having access to the data themselves. Such analyses must satisfy several statistical confidentiality rules; those that fail these rules will not be output to the user. In addition, the Drop q Rule, which requires removing a relatively small number of units before performing an analysis, is applied to all datasets. We describe the confidentiality rules and briefly outline an evaluation of the effectiveness of the Drop q Rule. We conclude with a description of other approaches to creating a system of this sort, and some directions for future research

Exclusive Strategy for Generalization Algorithms in Micro-data Disclosure

Abstract. When generalization algorithms are known to the public, an adver-sary can obtain a more precise estimation of the secret table than what can be deduced from the disclosed generalization result. Therefore, whether a general-ization algorithm can satisfy a privacy property should be judged based on such an estimation. In this paper, we show that the computation of the estimation is inherently a recursive process that exhibits a high complexity when generaliza-tion algorithms take a straightforward inclusive strategy. To facilitate the design of more efficient generalization algorithms, we suggest an alternative exclusive strategy, which adopts a seemingly drastic approach to eliminate the need for recursion. Surprisingly, the data utility of the two strategies are actually not com-parable and the exclusive strategy can provide better data utility in certain cases.

Simulatable Auditing in Micro-Databases

How to protect individuals’ privacy while releasing microdata tables for analysis pur- poses has attracted significant attention. We study the case where different microdata tables generalized over the same underlying secret table may be released upon users’ queries. To satisfy privacy constraints, an auditing system must determine whether the next query can be safely answered based on the history of answered queries. However, when answering a new query is not safe, denying it may not be, either, since a denial itself may still convey some sensitive information to the user. We first model this issue in the context of releasing microdata tables. Inspired by the Simulatable Auditing technique in statistical databases, we propose a safe strategy for auditing queries that ask for microdata tables generalized over secret tables. The strategy can provide provably safe answers and good data utility. We also study how to efficiently maintain the history of answered queries for the auditing purpose. To the best of our knowledge, this is the first study on the simulatable auditing issue of microdata queries

Ethics_ Security is Only as Good as the Weakest Link - Legal Tech Security Measures Every Lawyer Must Take

Meeting proceedings of a seminar by the same name, held August 2, 2022

메모리 보호를 위한 보안 정책을 시행하기 위한 코드 변환 기술

학위논문(박사)--서울대학교 대학원 :공과대학 전기·컴퓨터공학부,2020. 2. 백윤흥.Computer memory is a critical component in computer systems that needs to be protected to ensure the security of computer systems. It contains security sensitive data that should not be disclosed to adversaries. Also, it contains the important data for operating the system that should not be manipulated by the attackers. Thus, many security solutions focus on protecting memory so that sensitive data cannot be leaked out of the computer system or on preventing illegal access to computer data. In this thesis, I will present various code transformation techniques for enforcing security policies for memory protection. First, I will present a code transformation technique to track implicit data flows so that security sensitive data cannot leak through implicit data flow channels (i.e., conditional branches). Then I will present a compiler technique to instrument C/C++ program to mitigate use-after-free errors, which is a type of vulnerability that allow illegal access to stale memory location. Finally, I will present a code transformation technique for low-end embedded devices to enable execute-only memory, which is a strong security policy to protect secrets and harden the computing device against code reuse attacks.컴퓨터 메모리는 컴퓨터 시스템의 보안을 위해 보호되어야 하는 중요한 컴포넌트이다. 컴퓨터 메모리는 보안상 중요한 데이터를 담고 있을 뿐만 아니라, 시스템의 올바른 동작을 위해 공격자에 의해 조작되어서는 안되는 중요한 데이터 값들을 저장한다. 따라서 많은 보안 솔루션은 메모리를 보호하여 컴퓨터 시스템에서 중요한 데이터가 유출되거나 컴퓨터 데이터에 대한 불법적인 접근을 방지하는 데 중점을 둔다. 본 논문에서는 메모리 보호를 위한 보안 정책을 시행하기 위한 다양한 코드 변환 기술을 제시한다. 먼저, 프로그램에서 분기문을 통해 보안에 민감한 데이터가 유출되지 않도록 암시적 데이터 흐름을 추적하는 코드 변환 기술을 제시한다. 그 다음으로 C / C ++ 프로그램을 변환하여 use-after-free 오류를 완화하는 컴파일러 기술을 제시한다. 마지막으로, 중요 데이터를 보호하고 코드 재사용 공격으로부터 디바이스를 강화할 수 있는 강력한 보안 정책인 실행 전용 메모리(execute-only memory)를 저사양 임베디드 디바이스에 구현하기 위한 코드 변환 기술을 제시한다.1 Introduction 1 2 Background 4 3 A Hardware-based Technique for Efficient Implicit Information Flow Tracking 8 3.1 Introduction 8 3.2 Related Work 10 3.3 Our Approach for Implicit Flow Tracking 12 3.3.1 Implicit Flow Tracking Scheme with Program Counter Tag 12 3.3.2 tP C Management Technique 15 3.3.3 Compensation for the Untaken Path 20 3.4 Architecture Design of IFTU 22 3.4.1 Overall System 22 3.4.2 Tag Computing Core 24 3.5 Performance and Area Analysis 26 3.6 Security Analysis 28 3.7 Summary 30 4 CRCount: Pointer Invalidation with Reference Counting to Mitigate Useafter-free in Legacy C/C++ 31 4.1 Introduction 31 4.2 Related Work 36 4.3 Threat Model 40 4.4 Implicit Pointer Invalidation 40 4.4.1 Invalidation with Reference Counting 40 4.4.2 Reference Counting in C/C++ 42 4.5 Design 44 4.5.1 Overview 45 4.5.2 Pointer Footprinting 46 4.5.3 Delayed Object Free 50 4.6 Implementation 53 4.7 Evaluation 56 4.7.1 Statistics 56 4.7.2 Performance Overhead 58 4.7.3 Memory Overhead 62 4.8 Security Analysis 67 4.8.1 Attack Prevention 68 4.8.2 Security considerations 69 4.9 Limitations 69 4.10 Summary 71 5 uXOM: Efficient eXecute-Only Memory on ARM Cortex-M 73 5.1 Introduction 73 5.2 Background 78 5.2.1 ARMv7-M Address Map and the Private Peripheral Bus (PPB) 78 5.2.2 Memory Protection Unit (MPU) 79 5.2.3 Unprivileged Loads/Stores 80 5.2.4 Exception Entry and Return 80 5.3 Threat Model and Assumptions 81 5.4 Approach and Challenges 82 5.5 uXOM 85 5.5.1 Basic Design 85 5.5.2 Solving the Challenges 89 5.5.3 Optimizations 98 5.5.4 Security Analysis 99 5.6 Evaluation 100 5.6.1 Runtime Overhead 103 5.6.2 Code Size Overhead 106 5.6.3 Energy Overhead 107 5.6.4 Security and Usability 107 5.6.5 Use Cases 108 5.7 Discussion 110 5.8 Related Work 111 5.9 Summary 113 6 Conclusion and Future Work 114 6.1 Future Work 115 Abstract (In Korean) 132 Acknowlegement 133Docto

Security and trust in cloud computing and IoT through applying obfuscation, diversification, and trusted computing technologies

Cloud computing and Internet of Things (IoT) are very widely spread and commonly used technologies nowadays. The advanced services offered by cloud computing have made it a highly demanded technology. Enterprises and businesses are more and more relying on the cloud to deliver services to their customers. The prevalent use of cloud means that more data is stored outside the organization’s premises, which raises concerns about the security and privacy of the stored and processed data. This highlights the significance of effective security practices to secure the cloud infrastructure. The number of IoT devices is growing rapidly and the technology is being employed in a wide range of sectors including smart healthcare, industry automation, and smart environments. These devices collect and exchange a great deal of information, some of which may contain critical and personal data of the users of the device. Hence, it is highly significant to protect the collected and shared data over the network; notwithstanding, the studies signify that attacks on these devices are increasing, while a high percentage of IoT devices lack proper security measures to protect the devices, the data, and the privacy of the users. In this dissertation, we study the security of cloud computing and IoT and propose software-based security approaches supported by the hardware-based technologies to provide robust measures for enhancing the security of these environments. To achieve this goal, we use obfuscation and diversification as the potential software security techniques. Code obfuscation protects the software from malicious reverse engineering and diversification mitigates the risk of large-scale exploits. We study trusted computing and Trusted Execution Environments (TEE) as the hardware-based security solutions. Trusted Platform Module (TPM) provides security and trust through a hardware root of trust, and assures the integrity of a platform. We also study Intel SGX which is a TEE solution that guarantees the integrity and confidentiality of the code and data loaded onto its protected container, enclave. More precisely, through obfuscation and diversification of the operating systems and APIs of the IoT devices, we secure them at the application level, and by obfuscation and diversification of the communication protocols, we protect the communication of data between them at the network level. For securing the cloud computing, we employ obfuscation and diversification techniques for securing the cloud computing software at the client-side. For an enhanced level of security, we employ hardware-based security solutions, TPM and SGX. These solutions, in addition to security, ensure layered trust in various layers from hardware to the application. As the result of this PhD research, this dissertation addresses a number of security risks targeting IoT and cloud computing through the delivered publications and presents a brief outlook on the future research directions.Pilvilaskenta ja esineiden internet ovat nykyään hyvin tavallisia ja laajasti sovellettuja tekniikkoja. Pilvilaskennan pitkälle kehittyneet palvelut ovat tehneet siitä hyvin kysytyn teknologian. Yritykset enenevässä määrin nojaavat pilviteknologiaan toteuttaessaan palveluita asiakkailleen. Vallitsevassa pilviteknologian soveltamistilanteessa yritykset ulkoistavat tietojensa käsittelyä yrityksen ulkopuolelle, minkä voidaan nähdä nostavan esiin huolia taltioitavan ja käsiteltävän tiedon turvallisuudesta ja yksityisyydestä. Tämä korostaa tehokkaiden turvallisuusratkaisujen merkitystä osana pilvi-infrastruktuurin turvaamista. Esineiden internet -laitteiden lukumäärä on nopeasti kasvanut. Teknologiana sitä sovelletaan laajasti monilla sektoreilla, kuten älykkäässä terveydenhuollossa, teollisuusautomaatiossa ja älytiloissa. Sellaiset laitteet keräävät ja välittävät suuria määriä informaatiota, joka voi sisältää laitteiden käyttäjien kannalta kriittistä ja yksityistä tietoa. Tästä syystä johtuen on erittäin merkityksellistä suojata verkon yli kerättävää ja jaettavaa tietoa. Monet tutkimukset osoittavat esineiden internet -laitteisiin kohdistuvien tietoturvahyökkäysten määrän olevan nousussa, ja samaan aikaan suuri osuus näistä laitteista ei omaa kunnollisia teknisiä ominaisuuksia itse laitteiden tai niiden käyttäjien yksityisen tiedon suojaamiseksi. Tässä väitöskirjassa tutkitaan pilvilaskennan sekä esineiden internetin tietoturvaa ja esitetään ohjelmistopohjaisia tietoturvalähestymistapoja turvautumalla osittain laitteistopohjaisiin teknologioihin. Esitetyt lähestymistavat tarjoavat vankkoja keinoja tietoturvallisuuden kohentamiseksi näissä konteksteissa. Tämän saavuttamiseksi työssä sovelletaan obfuskaatiota ja diversifiointia potentiaalisiana ohjelmistopohjaisina tietoturvatekniikkoina. Suoritettavan koodin obfuskointi suojaa pahantahtoiselta ohjelmiston takaisinmallinnukselta ja diversifiointi torjuu tietoturva-aukkojen laaja-alaisen hyödyntämisen riskiä. Väitöskirjatyössä tutkitaan luotettua laskentaa ja luotettavan laskennan suoritusalustoja laitteistopohjaisina tietoturvaratkaisuina. TPM (Trusted Platform Module) tarjoaa turvallisuutta ja luottamuksellisuutta rakentuen laitteistopohjaiseen luottamukseen. Pyrkimyksenä on taata suoritusalustan eheys. Työssä tutkitaan myös Intel SGX:ää yhtenä luotettavan suorituksen suoritusalustana, joka takaa suoritettavan koodin ja datan eheyden sekä luottamuksellisuuden pohjautuen suojatun säiliön, saarekkeen, tekniseen toteutukseen. Tarkemmin ilmaistuna työssä turvataan käyttöjärjestelmä- ja sovellusrajapintatasojen obfuskaation ja diversifioinnin kautta esineiden internet -laitteiden ohjelmistokerrosta. Soveltamalla samoja tekniikoita protokollakerrokseen, työssä suojataan laitteiden välistä tiedonvaihtoa verkkotasolla. Pilvilaskennan turvaamiseksi työssä sovelletaan obfuskaatio ja diversifiointitekniikoita asiakaspuolen ohjelmistoratkaisuihin. Vankemman tietoturvallisuuden saavuttamiseksi työssä hyödynnetään laitteistopohjaisia TPM- ja SGX-ratkaisuja. Tietoturvallisuuden lisäksi nämä ratkaisut tarjoavat monikerroksisen luottamuksen rakentuen laitteistotasolta ohjelmistokerrokseen asti. Tämän väitöskirjatutkimustyön tuloksena, osajulkaisuiden kautta, vastataan moniin esineiden internet -laitteisiin ja pilvilaskentaan kohdistuviin tietoturvauhkiin. Työssä esitetään myös näkemyksiä jatkotutkimusaiheista