2018 IEEE 31st Computer Security Foundations Symposium (CSF)最新文献_第3页

Secure Compilation of Side-Channel Countermeasures: The Case of Cryptographic “Constant-Time” 边信道对抗的安全编译:密码学“恒时”情况

2018 IEEE 31st Computer Security Foundations Symposium (CSF) Pub Date : 2018-07-01 DOI: 10.1109/CSF.2018.00031

G. Barthe, B. Grégoire, Vincent Laporte

引用次数: 74

Computer-Aided Proofs for Multiparty Computation with Active Security 主动安全多方计算的计算机辅助证明

2018 IEEE 31st Computer Security Foundations Symposium (CSF) Pub Date : 2018-06-19 DOI: 10.1109/CSF.2018.00016

Helene Haagh, Aleksandr Karbyshev, Sabine Oechsner, Bas Spitters, Pierre-Yves Strub

{"title":"Computer-Aided Proofs for Multiparty Computation with Active Security","authors":"Helene Haagh, Aleksandr Karbyshev, Sabine Oechsner, Bas Spitters, Pierre-Yves Strub","doi":"10.1109/CSF.2018.00016","DOIUrl":"https://doi.org/10.1109/CSF.2018.00016","url":null,"abstract":"Secure multi-party computation (MPC) is a general cryptographic technique that allows distrusting parties to compute a function of their individual inputs, while only revealing the output of the function. It has found applications in areas such as auctioning, email filtering, and secure teleconference. Given their importance, it is crucial that the protocols are specified and implemented correctly. In the programming language community, it has become good practice to use computer proof assistants to verify correctness proofs. In the field of cryptography, EasyCrypt is the state of the art proof assistant. It provides an embedded language for probabilistic programming, together with a specialized logic, embedded into an ambient general purpose higher-order logic. It allows us to conveniently express cryptographic properties. EasyCrypt has been used successfully on many applications, including public-key encryption, signatures, garbled circuits and differential privacy. Here we show for the first time that it can also be used to prove security of MPC against a malicious adversary. We formalize additive and replicated secret sharing schemes and apply them to Maurer's MPC protocol for secure addition and multiplication. Our method extends to general polynomial functions. We follow the insights from EasyCrypt that security proofs can often be reduced to proofs about program equivalence, a topic that is well understood in the verification of programming languages. In particular, we show that for a class of MPC protocols in the passive case the non-interference-based (NI) definition is equivalent to a standard simulation-based security definition. For the active case, we provide a new non-interference based alternative to the usual simulation-based cryptographic definition that is tailored specifically to our protocol.","PeriodicalId":417032,"journal":{"name":"2018 IEEE 31st Computer Security Foundations Symposium (CSF)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115497278","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 22

Types for Information Flow Control: Labeling Granularity and Semantic Models 信息流控制的类型:标记粒度和语义模型

2018 IEEE 31st Computer Security Foundations Symposium (CSF) Pub Date : 2018-04-30 DOI: 10.1109/CSF.2018.00024

Vineet Rajani, D. Garg

{"title":"Types for Information Flow Control: Labeling Granularity and Semantic Models","authors":"Vineet Rajani, D. Garg","doi":"10.1109/CSF.2018.00024","DOIUrl":"https://doi.org/10.1109/CSF.2018.00024","url":null,"abstract":"Language-based information flow control (IFC) tracks dependencies within a program using sensitivity labels and prohibits public outputs from depending on secret inputs. In particular, literature has proposed several type systems for tracking these dependencies. On one extreme, there are fine-grained type systems (like Flow Caml) that label all values individually and track dependence at the level of individual values. On the other extreme are coarse-grained type systems (like HLIO) that track dependence coarsely, by associating a single label with an entire computation context and not labeling all values individually. In this paper, we show that, despite their glaring differences, both these styles are, in fact, equally expressive. To do this, we show a semantics- and type-preserving translation from a coarse-grained type system to a fine-grained one and vice-versa. The forward translation isn't surprising, but the backward translation is: It requires a construct to arbitrarily limit the scope of a context label in the coarse-grained type system (e.g., HLIO's ``toLabeled'' construct). As a separate contribution, we show how to extend work on logical relation models of IFC types to higher-order state. We build such logical relations for both the fine-grained type system and the coarse-grained type system. We use these relations to prove the two type systems and our translations between them sound.","PeriodicalId":417032,"journal":{"name":"2018 IEEE 31st Computer Security Foundations Symposium (CSF)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129990376","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 23

Formal Security Proof of CMAC and Its Variants CMAC及其变体的正式安全性证明

2018 IEEE 31st Computer Security Foundations Symposium (CSF) Pub Date : 2018-04-28 DOI: 10.1109/CSF.2018.00014

Cécile Baritel-Ruet, François Dupressoir, Pierre-Alain Fouque, B. Grégoire

引用次数: 6

Automated Unbounded Verification of Stateful Cryptographic Protocols with Exclusive OR 具有异或的有状态加密协议的自动无界验证

2018 IEEE 31st Computer Security Foundations Symposium (CSF) Pub Date : 2018-04-27 DOI: 10.1109/CSF.2018.00033

Jannik Dreier, L. Hirschi, S. Radomirovic, R. Sasse

{"title":"Automated Unbounded Verification of Stateful Cryptographic Protocols with Exclusive OR","authors":"Jannik Dreier, L. Hirschi, S. Radomirovic, R. Sasse","doi":"10.1109/CSF.2018.00033","DOIUrl":"https://doi.org/10.1109/CSF.2018.00033","url":null,"abstract":"Exclusive-or (XOR) operations are common in cryptographic protocols, in particular in RFID protocols and electronic payment protocols. Although there are numerous applications, due to the inherent complexity of faithful models of XOR, there is only limited tool support for the verification of cryptographic protocols using XOR. The Tamarin prover is a state-of-the-art verification tool for cryptographic protocols in the symbolic model. In this paper, we improve the underlying theory and the tool to deal with an equational theory modeling XOR operations. The XOR theory can be freely combined with all equational theories previously supported, including user-defined equational theories. This makes Tamarin the first tool to support simultaneously this large set of equational theories, protocols with global mutable state, an unbounded number of sessions, and complex security properties including observational equivalence. We demonstrate the effectiveness of our approach by analyzing several protocols that rely on XOR, in particular multiple RFID-protocols, where we can identify attacks as well as provide proofs.","PeriodicalId":417032,"journal":{"name":"2018 IEEE 31st Computer Security Foundations Symposium (CSF)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129119153","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 15

A Little More Conversation, a Little Less Action, a Lot More Satisfaction: Global States in ProVerif 多一点对话，少一点行动，多一点满足:ProVerif的全球状态

2018 IEEE 31st Computer Security Foundations Symposium (CSF) Pub Date : 2018-04-23 DOI: 10.1109/CSF.2018.00032

Vincent Cheval, V. Cortier, Mathieu Turuani

引用次数: 31

An Extensive Formal Analysis of Multi-factor Authentication Protocols 多因素认证协议的广泛形式化分析

2018 IEEE 31st Computer Security Foundations Symposium (CSF) Pub Date : 2018-04-20 DOI: 10.1145/3440712

Charlie Jacomme, S. Kremer

{"title":"An Extensive Formal Analysis of Multi-factor Authentication Protocols","authors":"Charlie Jacomme, S. Kremer","doi":"10.1145/3440712","DOIUrl":"https://doi.org/10.1145/3440712","url":null,"abstract":"Passwords are still the most widespread means for authenticating users, even though they have been shown to create huge security problems. This motivated the use of additional authentication mechanisms used in so-called multi-factor authentication protocols. In this paper we define a detailed threat model for this kind of protocols: while in classical protocol analysis attackers control the communication network, we take into account that many communications are performed over TLS channels, that computers may be infected by different kinds of malwares, that attackers could perform phishing, and that humans may omit some actions. We formalize this model in the applied pi calculus and perform an extensive analysis and comparison of several widely used protocols — variants of Google 2-step and FIDO’s U2F. The analysis is completely automated, generating systematically all combinations of threat scenarios for each of the protocols and using the P ROVERIF tool for automated protocol analysis. Our analysis highlights weaknesses and strengths of the different protocols, and allows us to suggest several small modifications of the existing protocols which are easy to implement, yet improve their security in several threat scenarios.","PeriodicalId":417032,"journal":{"name":"2018 IEEE 31st Computer Security Foundations Symposium (CSF)","volume":"105 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134562223","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 43

A Permission-Dependent Type System for Secure Information Flow Analysis 安全信息流分析的权限依赖型系统

2018 IEEE 31st Computer Security Foundations Symposium (CSF) Pub Date : 2017-09-27 DOI: 10.1109/CSF.2018.00023

Hongxu Chen, Alwen Tiu, Zhiwu Xu, Yang Liu

引用次数: 12

Privacy Risk in Machine Learning: Analyzing the Connection to Overfitting 机器学习中的隐私风险:与过拟合的关系分析

2018 IEEE 31st Computer Security Foundations Symposium (CSF) Pub Date : 2017-09-05 DOI: 10.1109/CSF.2018.00027

Samuel Yeom, Irene Giacomelli, Matt Fredrikson, S. Jha

{"title":"Privacy Risk in Machine Learning: Analyzing the Connection to Overfitting","authors":"Samuel Yeom, Irene Giacomelli, Matt Fredrikson, S. Jha","doi":"10.1109/CSF.2018.00027","DOIUrl":"https://doi.org/10.1109/CSF.2018.00027","url":null,"abstract":"Machine learning algorithms, when applied to sensitive data, pose a distinct threat to privacy. A growing body of prior work demonstrates that models produced by these algorithms may leak specific private information in the training data to an attacker, either through the models' structure or their observable behavior. However, the underlying cause of this privacy risk is not well understood beyond a handful of anecdotal accounts that suggest overfitting and influence might play a role. This paper examines the effect that overfitting and influence have on the ability of an attacker to learn information about the training data from machine learning models, either through training set membership inference or attribute inference attacks. Using both formal and empirical analyses, we illustrate a clear relationship between these factors and the privacy risk that arises in several popular machine learning algorithms. We find that overfitting is sufficient to allow an attacker to perform membership inference and, when the target attribute meets certain conditions about its influence, attribute inference attacks. Interestingly, our formal analysis also shows that overfitting is not necessary for these attacks and begins to shed light on what other factors may be in play. Finally, we explore the connection between membership inference and attribute inference, showing that there are deep connections between the two that lead to effective new attacks.","PeriodicalId":417032,"journal":{"name":"2018 IEEE 31st Computer Security Foundations Symposium (CSF)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128458770","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 733