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The Good, the Bad and the (Not So) Ugly of Out-Of-Band Authentication with eID Cards and Push Notifications 20

The Good, the Bad and the (Not So) Ugly of Out-Of-Band Authe...

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10th acm conference on data and application security and privacy (CODASPY)

作者： Pernpruner, Marco Carbone, Roberto Ranise, Silvio Sciarretta, Giada Fdn Bruno Kessler Secur & Trust Res Unit Trento Italy

ISBN: (纸本)9781450371070

Everyday life is permeated by new technologies allowing people to perform almost any kind of operation from their smart devices. Although this is amazing from a convenience perspective, it may result in several security issues concerning the need for authenticating users in a proper and secure way. Electronic identity cards (also called eID cards) play a very important role in this regard, due to the high level of assurance they provide in identification and authentication processes. However, authentication solutions relying on them are still uncommon and suffer from many usability limitations. In this paper, we thus present the design and implementation of a novel passwordless, multi-factor authentication protocol based on eID cards. To reduce known usability issues while keeping a high level of security, our protocol leverages push notifications and mobile devices equipped with NFC, which can be used to interact with eID cards. In addition, we evaluate the security of the protocol through a formal security analysis and a risk analysis, whose results emphasize the acceptable level of security.

关键词： eID cards Formal analysis Multi-factor authentication Passwordless Push notifications Risk analysis security protocols

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eThor: Practical and Provably Sound Static Analysis of Ethereum Smart Contracts 20

eThor: Practical and Provably Sound Static Analysis of Ether...

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acm SIGSAC conference on Computer and Communications security (acm CCS)

作者： Schneidewind, Clara Grishchenko, Ilya Scherer, Markus Maffei, Matteo TU Wien Vienna Austria

ISBN: (纸本)9781450370899

Ethereum has emerged as the most popular smart contract platform, with hundreds of thousands of contracts stored on the blockchain and covering diverse application scenarios, such as auctions, trading platforms, or elections. Given the financial nature of smart contracts, security vulnerabilities may lead to catastrophic consequences and, even worse, can hardly be fixed as data stored on the blockchain, including the smart contract code itself, are immutable. An automated security analysis of these contracts is thus of utmost interest, but at the same time technically challenging. This is as e.g., Ethereum's transaction-oriented programming mechanisms feature a subtle semantics, and since the blockchain data at execution time, including the code of callers and callees, are not statically known. In this work, we present eThor, the first sound and automated static analyzer for EVM bytecode, which is based on an abstraction of the EVM bytecode semantics based on Horn clauses. In particular, our static analysis supports reachability properties, which we show to be sufficient for capturing interesting security properties for smart contracts (e.g., single-entrancy) as well as contract-specific functional properties. Our analysis is proven sound against a complete semantics of EVM bytecode, and a large-scale experimental evaluation on real-world contracts demonstrates that eThor is practical and outperforms the state-of-the-art static analyzers: specifically, eThor is the only one to provide soundness guarantees, terminates on 94% of a representative set of real-world contracts, and achieves an F-measure (which combines sensitivity and specificity) of 89%.

关键词： ethereum specification language smart contracts security analysis automated reasoning abstract interpretation cryptocurrencies static analysis

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TrustAV: Practical and privacy-Preserving Malware Analysis in the Cloud 20

TrustAV: Practical and Privacy-Preserving Malware Analysis i...

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10th acm conference on data and application security and privacy (CODASPY)

作者： Deyannis, Dimitris Papadogiannaki, Eva Kalivianakis, Giorgos Vasiliadis, Giorgos Ioannidis, Sotiris FORTH ICS Iraklion Greece Univ Crete Dept Comp Sci Rethimnon Crete Greece

ISBN: (纸本)9781450371070

While the number of connected devices is constantly growing, we observe an increased incident rate of cyber attacks that target user data. Typically, personal devices contain the most sensitive information regarding their users, so there is no doubt that they can be a very valuable target for adversaries. Typical defense solution to safeguard user devices and data, are based in malware analysis mechanisms. To amortize the processing and maintenance overheads, the outsourcing of network inspection mechanisms to the cloud has become very popular recently. However, the majority of such cloud-based applications usually offers limited privacy preserving guarantees for data processing in third-party environments. In this work, we propose TrustAV, a practical cloud-based malware detection solution destined for a plethora of device types. TrustAV is able to offload the processing of malware analysis to a remote server, where it is executed entirely inside, hardware supported, secure enclaves. By doing so, TrustAV is capable to shield the transfer and processing of user data even in untrusted environments with tolerable performance overheads, ensuring that private user data are never exposed to malicious entities or honestbut-curious providers. TrustAV also utilizes various techniques in order to overcome performance overheads, introduced by the Intel SGX technology, and reduce the required enclave memory -a limiting factor for malware analysis executed in secure enclave environments- offering up to 3x better performance.

关键词： Intel SGX trusted execution environment antivirus data processing mobile privacy

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proceedings of the 15th acm Asia conference on Computer and Communications security, ASIA CCS 2020

Proceedings of the 15th ACM Asia Conference on Computer and ...

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15th acm Asia conference on Computer and Communications security, ASIA CCS 2020

ISBN: (纸本)9781450367509

The proceedings contain 85 papers. The topics discussed include: proofs or remote execution and mitigation of TOCTOU attacks;global communication guarantees in the presence of adversaries;the Lazarus effect: healing compromised devices in the Internet of small things;AuthCTC: defending against waveform emulation attack in heterogeneous IoT environments;DeepPower: non-intrusive and deep learning-based detection of IoT malware using power side channels;your smart home can’t keep a secret: towards automated fingerprinting of IoT Traffic;PassTag: a graphical-textual hybrid fallback authentication system;provable-security model for strong proximity-based attacks: with application to contactless payments;skeptic: automatic, justified and privacy-preserving password composition policy selection;preparing network intrusion detection deep learning models with minimal data using adversarial domain adaptation;creating character-based templates for log data to enable security event classification;and in-network filtering of distributed denial-of-service traffic with near-optimal rule selection.

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A Hypothesis Testing Approach to Sharing Logs with Confidence 20

A Hypothesis Testing Approach to Sharing Logs with Confidenc...

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10th acm conference on data and application security and privacy (CODASPY)

作者： Long, Yunhui Xu, Le Gunter, Carl A. Univ Illinois Urbana IL 61801 USA

ISBN: (纸本)9781450371070

Logs generated by systems and applications contain a wide variety of heterogeneous information that is important for performance profiling, failure detection, and security analysis. There is a strong need for sharing the logs among different parties to outsource the analysis or to improve system and security research. However, sharing logs may inadvertently leak confidential or proprietary information. Besides sensitive information that is directly saved in logs, such as user-identifiers and software versions, indirect evidence like performance metrics can also lead to the leakage of sensitive information about the physical machines and the system. In this work, we introduce a game-based definition of the risk of exposing sensitive information through released logs. We propose log indistinguishability, a property that is met only when the logs leak little information about the protected sensitive attributes. We design an end-to-end framework that allows a user to identify risk of information leakage in logs, to protect the exposure with log redaction and obfuscation, and to release the logs with a much lower risk of exposing the sensitive attribute. Our framework contains a set of statistical tests to identify violations of the log indistinguishability property and a variety of obfuscation methods to prevent the leakage of sensitive information. The framework views the log-generating process as a black-box and can therefore be applied to different systems and processes. We perform case studies on two different types of log datasets: Spark event log and hardware counters. We show that our framework is effective in preventing the leakage of the sensitive attribute with a reasonable testing time and an acceptable utility loss in logs.

关键词： indistinguishability hypothesis test log obfuscation privacy

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POSTER: Blockchain-Based Differential privacy Cost Management System 20

POSTER: Blockchain-Based Differential Privacy Cost Managemen...

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15th acm Asia conference on Computer and Communications security, ASIA CCS 2020

作者： Han, Leong Mei Zhao, Yang Zhao, Jun Nanyang Technological University Singapore Singapore

ISBN: (纸本)9781450367509

privacy preservation is a big concern for various sectors. To protect individual user data, one emerging technology is differential privacy. However, it still has limitations for datasets with frequent queries, such as the fast accumulation of privacy cost. To tackle this limitation, this paper explores the integration of a secured decentralised ledger, blockchain. Blockchain will be able to keep track of all noisy responses generated with differential privacy algorithm and allow for certain queries to reuse old responses. In this paper, a demo of a proposed blockchain-based privacy management system is designed as an interactive decentralised web application (DApp). The demo created illustrates that leveraging on blockchain will allow the total privacy cost accumulated to decrease significantly. © 2020 Owner/Author.

关键词： Blockchain

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Explore the Transformation Space for Adversarial Images 20

Explore the Transformation Space for Adversarial Images

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10th acm conference on data and application security and privacy (CODASPY)

作者： Chen, Jiyu Wang, David Chen, Hao Univ Calif Davis Davis CA 95616 USA Vestavia Hills High Sch Vestavia Hills AL USA

ISBN: (纸本)9781450371070

Deep learning models are vulnerable to adversarial examples. Most of current adversarial attacks add pixel-wise perturbations restricted to some L-p -norm, and defense models are evaluated also on adversarial examples restricted inside L-p-norm balls. However, we wish to explore adversarial examples exist beyond L-p-norm balls and their implications for attacks and defenses. In this paper, we focus on adversarial images generated by transformations. We start with color transformation and propose two gradient-based attacks. Since L-p-norm is inappropriate for measuring image quality in the transformation space, we use the similarity between transformations and the Structural Similarity Index. Next, we explore a larger transformation space consisting of combinations of color and affine transformations. We evaluate our transformation attacks on three data sets - CIFAR10, SVHN, and ImageNet - and their corresponding models. Finally, we perform retraining defenses to evaluate the strength of our attacks. The results show that transformation attacks are powerful. They find high-quality adversarial images that have higher transferability and misclassification rates than C&W's L-p attacks, especially at high confidence levels. They are also significantly harder to defend against by retraining than C&W's L-p attacks. More importantly, exploring different attack spaces makes it more challenging to train a universally robust model.

关键词： Adversarial attacks Image transformation Deep learning security

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Can AI be for Good in the Midst of Cyber Attacks and privacy Violations?: A Position Paper 10

Can AI be for Good in the Midst of Cyber Attacks and Privacy...

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10th acm conference on data and application security and privacy, CODASPY 2020

作者： Thuraisingham, Bhavani M. University of Texas at Dallas Richardson TX United States

ISBN: (纸本)9781450371070

Artificial Intelligence (AI) is affecting every aspect of our lives from healthcare to finance to driving to managing the home. Sophisticated machine learning techniques with a focus on deep learning are being applied successfully to detect cancer, to make the best choices for investments, to determine the most suitable routes for driving as well as to efficiently manage the electricity in our homes. We expect AI to have even more influence as advances are made with technology as well as in learning, planning, reasoning and explainable systems. While these advances will greatly advance humanity, organizations such as the United Nations have embarked on initiatives such as "AI for Good" and we can expect to see more emphasis on applying AI for the good of humanity especially in developing countries. However, the question that needs to be answered is Can AI be for Good when when the AI techniques can be attacked and the AI techniques themselves can cause privacy violations? This position paper will provide an overview of this topic with protecting children and children's rights as an example. © 2020 Owner/Author.

关键词： adversarial machine learning ai for good children's rights cyber attacks privacy protection

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N-m-Variant Systems: Adversarial-Resistant Software Rejuvenation for Cloud-Based Web applications 10

N-m-Variant Systems: Adversarial-Resistant Software Rejuvena...

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10th acm conference on data and application security and privacy, CODASPY 2020

作者： Polinsky, Isaac Martin, Kyle Enck, William Reiter, Michael K. North Carolina State University Raleigh NC United States University of North Carolina at Chapel Hill Chapel Hill NC United States

ISBN: (纸本)9781450371070

Web servers are a popular target for adversaries as they are publicly accessible and often vulnerable to compromise. Compromises can go unnoticed for months, if not years, and recovery often involves a complete system rebuild. In this paper, we propose n-m-Variant Systems, an adversarial-resistant software rejuvenation framework for cloud-based web applications. We improve the state-of-the-art by introducing a variable m that provides a knob for administrators to tune an environment to balance resource usage, performance overhead, and security guarantees. Using m, security guarantees can be tuned for seconds, minutes, days, or complete resistance. We design and implement an n-m-Variant System prototype to protect a Mediawiki PHP application serving dynamic content from an external SQL persistent storage. Our performance evaluation shows a throughput reduction of 65% for 108 seconds of resistance and 83% for 12 days of resistance to sophisticated adversaries, given appropriate resource allocation. Furthermore, we use theoretical analysis and simulation to characterize the impact of system parameters on resilience to adversaries. Through these efforts, our work demonstrates how properties of cloud-based servers can enhance the integrity of Web servers. © 2020 acm.

关键词： cloud security intrusion resilience n-variant systems

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Poster: pFilter - Retrofitting Legacy applications for data privacy 26

Poster: pFilter - Retrofitting Legacy Applications for Data ...

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acm SIGSAC conference on Computer and Communications security (CCS)

作者： Shukla, Manish Vidhani, Kumar Sirigireddy, Gangadhara Banahatti, Vijayanand Lodha, Sachin TCS Res Lab Pune Maharashtra India

ISBN: (纸本)9781450367479

Enterprise needs to process customer data for providing tailored services to them, however, the data often includes sensitive and personally identifiable information. This leads to a difficult situation wherein the enterprise has to balance the necessity to process the sensitive data with the requirement to safeguard its privacy. The problem is more prominent in legacy applications with almost no privacy controls in place. A well-studied technique to retrofit legacy application is to mask sensitive content before it is rendered on the screen using path based methods. In this work we show the gap in the existing state of art and describe a dynamic system which utilizes a context to perform locality based searching and masking of sensitive content.

关键词： legacy application data privacy context based masking

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