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检索条件"任意字段=Proceedings of the Twelfth ACM Conference on Data and Application Security and Privacy"

共 560 条记录，以下是151-160 订阅

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Secure Pull Printing with QR Codes and National eID Cards: A Software-oriented Design and an Open-source Implementation 21

Secure Pull Printing with QR Codes and National eID Cards: A...

引用

11th acm conference on data and application security and privacy, CODASPY 2021

作者： Leonelli, Matteo Morelli, Umberto Sciarretta, Giada Ranise, Silvio Fondazione Bruno Kessler Trento Italy Fondazione Bruno Kessler University of Trento Trento Italy

ISBN: (纸本)9781450381437

With more systems becoming digitised, enterprises are adopting cloud technologies and outsourcing non-critical services to reduce the pressure on IT departments. In this process, it is crucial to achieving the right balance between costs, usability and security;prioritising security over the rest when handling sensitive data. Considering the print management, often off-premise, many enterprises report at least one print-related security incident that led to data loss in the past year. This problem can damage the enterprise business, especially considering the fines prescribed by current regulations or its reputation. Focusing on securing enterprise printing, pull printing is the set of technologies and processes that allow the release of print jobs according to specific conditions;typically user authentication and proximity to a printer. We design a software-oriented pull printing infrastructure that supports a print release mechanism using QR codes and electronic IDentity cards as a second-factor authenticator. Our solution addresses the costs, as any medium-size organisation can adopt our open-source solution without additional devices or access badges;and the user experience, as we offer a driverless print environment and a user-friendly mobile application. © 2021 acm.

关键词： Sensitive data

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The Ephemeral Threat: Assessing the security of Algorithmic Trading Systems powered by Deep Learning 25

The Ephemeral Threat: Assessing the Security of Algorithmic ...

引用

proceedings of the Fifteenth acm conference on data and application security and privacy

作者： Advije Rizvani Giovanni Apruzzese Pavel Laskov Liechtenstein Business School University of Liechtenstein Vaduz Liechtenstein

ISBN: (纸本)9798400714764

We study the security of stock price forecasting using Deep Learning (DL) in computational finance. Despite abundant prior research on vulnerability of DL to adversarial perturbations, such work has hitherto hardly addressed practical adversarial threat models in the context of DL-powered algorithmic trading systems (ATS).Specifically, we investigate the vulnerability of ATS to adversarial perturbations launched by a realistically constrained attacker. We first show that existing literature has paid limited attention to DL security in the financial domain---which is naturally attractive for adversaries. Then, we formalize the concept of ephemeral perturbations (EP), which can be used to stage a novel type of attack tailored for DL-based ATS. Finally, we carry out an end-to-end evaluation of our EP against a profitable ATS. Our results reveal that the introduction of small changes to the input stock-prices not only (i)~induces the DL model to behave incorrectly but also (ii)~leads to the whole ATS to make suboptimal buy/sell decisions, resulting in a worse financial performance of the targeted ATS.

关键词： attack

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MLHat: Deployable Machine Learning for security Defense 21

MLHat: Deployable Machine Learning for Security Defense

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27th acm SIGKDD International conference on Knowledge Discovery and data Mining (KDD)

作者： Wang, Gang Ciptadi, Arridhana Ahmadzadeh, Ali UIUC Champaign IL 61820 USA TruEra Redmond WA USA Blue Hexagon San Francisco CA USA

ISBN: (纸本)9781450383325

The MLHat workshop aims to bring together academic researchers and industry practitioners to discuss the open challenges, potential solutions, and best practices to deploy machine learning at scale for security defense. The workshop will discuss related topics from both defender perspectives (white-hat) and the attacker perspectives ( black-hat). We call the workshop MLHats, to serve as a place for people who are interested in using machine learning to solve practical security problems. The workshop will focus on defining new machine learning paradigms under various security application contexts and identifying exciting new future research directions. At the same time, the workshop will also have a strong industry presence to provide insights into the challenges in deploying and maintaining machine learning models and the much-needed discussion on the capabilities that the state-of-the-arts failed to provide.

关键词： security and privacy Deployable Machine Learning Adversarial Machine Learning

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Enabling data Interoperability for Decentralized, Smart, and Connected Health applications 23

Enabling Data Interoperability for Decentralized, Smart, and...

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proceedings of the 8th acm/IEEE International conference on Connected Health: applications, Systems and Engineering Technologies

作者： Oshani Seneviratne Rensselaer Polytechnic Institute Troy NY USA

ISBN: (纸本)9798400701023

The digitization of healthcare is increasing, providing a wealth of data that can improve patient care and outcomes. However, different systems and formats often silo this data, presenting a significant challenge to achieving a connected and interoperable healthcare ecosystem. data interoperability is crucial for realizing the full potential of smart and connected health, which can improve patient outcomes and reduce costs. In this paper, we describe the key concepts and technologies enabling interoperability, including health information exchange, interoperability standards, and application programming interfaces enabling connected health applications built on blockchains. We also discuss the challenges and barriers to achieving data interoperability, such as privacy and security concerns, organizational and cultural barriers, and technical limitations. Furthermore, we highlight the benefits of data interoperability in healthcare, such as better patient outcomes, improved population health management, reduced costs, and increased efficiency. Finally, we discuss the potential future of data interoperability in healthcare, including the role of emerging privacy-preserving technologies.

关键词： interoperability

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Role-Based Deception in Enterprise Networks 21

Role-Based Deception in Enterprise Networks

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11th acm conference on data and application security and privacy (CODASPY)

作者： Anjum, Iffat Zhu, Mu Polinsky, Isaac Enck, William Reiter, Michael K. Singh, Munindar P. North Carolina State Univ Raleigh NC 27695 USA Duke Univ Durham NC USA

ISBN: (纸本)9781450381437

Historically, enterprise network reconnaissance is an active process, often involving port scanning. However, as routers and switches become more complex, they also become more susceptible to compromise. From this vantage point, an attacker can passively identify high-value hosts such as the workstations of IT administrators, C-suite executives, and. nance personnel. The goal of this paper is to develop a technique to deceive and dissuade such adversaries. We propose HoneyRoles, which uses honey connections to build metaphorical haystacks around the network traffic of client hosts belonging to high-value organizational roles. The honey connections also act as network canaries to signal network compromise, thereby dissuading the adversary from acting on information observed in network flows. We design a prototype implementation of HoneyRoles using an OpenFlow SDN controller and evaluate its security using the PRISM probabilistic model checker. Our performance evaluation shows that HoneyRoles has a small effect on network request completion time, and security analysis demonstrates that once an alert is raised, HoneyRoles can quickly identify the compromised switch with high probability. In doing so, we show that role-based network deception is a promising approach for defending against adversaries in compromised network devices.

关键词： deception software defined network cyber security data plane

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Probabilistic data Structures in the Wild: A security Analysis of Redis 25

Probabilistic Data Structures in the Wild: A Security Analys...

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proceedings of the Fifteenth acm conference on data and application security and privacy

作者： Mia Fili? Jonas Hofmann Sam A. Markelon Kenneth G. Paterson Anupama Unnikrishnan ETH Zurich Zurich Switzerland ETH Zurich Zurich Germany and Technische Universität Darmstadt Darmstadt Germany University of Florida Gainesville FL USA

ISBN: (纸本)9798400714764

Redis (Remote Dictionary Server) is a general purpose, in-memory database that supports a rich array of functionality, including various Probabilistic data Structures (PDS), such as Bloom filters, Cuckoo filters, as well as cardinality and frequency estimators. These PDS typically perform well in the average case. However, given that Redis is intended to be used across a diverse array of applications, it is crucial to evaluate how these PDS perform under worst-case scenarios, i.e., when faced with adversarial inputs. We offer a comprehensive analysis to address this question. We begin by carefully documenting the different PDS implementations in Redis, explaining how they deviate from those PDS as described in the literature. Then we show that these deviations enable a total of 10 novel attacks that are more severe than the corresponding attacks for generic versions of the PDS. We highlight the critical role of Redis' decision to use non-cryptographic hash functions in the severity of these attacks. We conclude by discussing countermeasures to the attacks

关键词： PDS attack countermeasures

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Assessing the Alignment of Social Robots with Trustworthy AI Design Guidelines: A Preliminary Research Study 21

Assessing the Alignment of Social Robots with Trustworthy AI...

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11th acm conference on data and application security and privacy (CODASPY)

作者： Chattopadhyay, Ankur Ali, Abdikadar Thaxton, Danielle Northern Kentucky Univ Comp Sci Dept Highland Hts KY 41099 USA

ISBN: (纸本)9781450381437

The last few years have seen a strong movement supporting the need of having intelligent consumer products align with specific design guidelines for trustworthy artificial intelligence (AI). This global movement has led to multiple institutional recommendations for ethically aligned trustworthy design of the AI driven technologies, like consumer robots and autonomous vehicles. There has been prior research towards finding security and privacy related vulnerabilities within various types of social robots. However, none of these previous works has studied the implications of these vulnerabilities in terms of the robot design aligning with trustworthy AI. In an attempt to address this gap in existing literature, we have performed a unique research study with two social robots - Zumi and Cozmo. In this study, we have explored flaws within the robot's system, and have analyzed these flaws to assess the overall alignment of the robot system design with the IEEE global standards on the design of ethically aligned trustworthy autonomous intelligent systems (IEEE A/IS Standards). Our initial research shows that the vulnerabilities and design weaknesses, which we found in these robots, can lead to hacking, injection attacks, and other malfunctions that might affect the technology users negatively. We test the intelligent functionalities in these robots to find faults, and conduct a preliminary examination of how these flaws can potentially result in non-adherence with the IEEE A/IS principles. Through this novel study, we demonstrate our approach towards determining alignment of social robots with benchmarks for trustworthy AI, thereby creating a case for prospective design improvements to address unique risks leading to issues with robot ethics and trust.

关键词： security and privacy Assessment Preliminary Research Study Alignment Social Robots Trustworthy AI Ethics IEEE A/IS Principles Standards Vulnerabilities Risks Design Flaws

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A dataset for Evaluating LLMs Vulnerability Repair Performance in Android applications: data/Toolset paper 25

A Dataset for Evaluating LLMs Vulnerability Repair Performan...

引用

proceedings of the Fifteenth acm conference on data and application security and privacy

作者： Elisa Braconaro Eleonora Losiouk Universita degli Studi di Padova Padua Italy

ISBN: (纸本)9798400714764

Automated Program Repair (APR) is a well-established research area that enhances software reliability and security by automatically fixing bugs, reducing manual effort, and accelerating debugging. Despite progress in publishing benchmarks to evaluate APR tools, datasets specifically targeting Android are *** address this gap, we introduce a dataset of 272 real-world violations of Google's Android security Best Practices, identified by statically analyzing 113 real-world Android apps. In addition to the faulty code, we manually crafted repairs based on Google's guidelines, covering 176 Java-based and 96 XML-based violations from Android Java classes and Manifest files, respectively. Additionally, we leveraged our novel dataset to evaluate Large Language Models (LLMs) as they are the latest promising APR tools. In particular, we evaluated GPT-4o, Gemini 1.5 Flash and Gemini in Android Studio and we found that GPT-4o outperforms Google's models, demonstrating higher accuracy and robustness across a range of violations types. Hence, with this dataset, we aim to provide valuable insights for advancing APR research and improving tools for Android security.

关键词： android vulnerabilities

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Using Venom to Flip the Coin and Peel the Onion: Measurement Tool and dataset for Studying the Bitcoin - Dark Web Synergy: data/Toolset Paper 25

Using Venom to Flip the Coin and Peel the Onion: Measurement...

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proceedings of the Fifteenth acm conference on data and application security and privacy

作者： Lukas Ingmarsson Karl Duckert Karlsson Niklas Carlsson Linköping University Linköping Sweden

ISBN: (纸本)9798400714764

Bitcoin and the Dark Web present an interesting synergy that enables both legitimate anonymity and illicit activities, making it an important landscape to understand, especially as the Dark Web, with its hidden services, relies heavily on Bitcoin as a pseudonymous currency for transactions. However, a lack of scalable tools and timely datasets has limited systematic analysis of this ecosystem. To address this gap, we introduce Venom, a scalable framework for mapping Bitcoin activity on the Dark Web. Venom integrates multithreaded crawling, data extraction, and dataset generation, resulting in a comprehensive resource that allows us to easily collect snapshots of over 177,000 onion sites in roughly 24 hours. With the paper, we share both the tool and an example snapshot containing both per-site metadata and Bitcoin transaction data. Preliminary analysis reveals concentrated activity among key players and widespread content mirroring, offering new insights into the Dark Web's economic structure. Venom provides a critical resource for advancing research and monitoring in this domain.

关键词： Bitcoin

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Formal Analysis of ReBAC Policy Mining Feasibility 21

Formal Analysis of ReBAC Policy Mining Feasibility

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11th acm conference on data and application security and privacy (CODASPY)

作者： Chakraborty, Shuvra Sandhu, Ravi Univ Texas San Antonio Inst Cyber Secur ICS San Antonio TX 78249 USA Univ Texas San Antonio NSF Ctr Secur & Privacy Enhanced Cloud Comp C SPE Dept Comp Sci San Antonio TX 78249 USA

ISBN: (纸本)9781450381437

Relationship-Based Access Control (ReBAC) expresses authorization in terms of various direct and indirect relationships amongst entities, most commonly between users. The need for ReBAC policy mining arises when an existing access control system is reformulated in ReBAC. This paper considers the feasibility of ReBAC policy mining in context of user to user authorization, such as arises in various social and business contexts. In accordance with the policy mining literature, we assume that complete data is provided regarding user to user authorizations for a given user set, along with complete relationship data amongst these users comprising a labeled relationship graph. A ReBAC policy language is also specified. ReBAC policy mining seeks to formulate a ReBAC policy with the given policy language and relationship graph, which is exactly equivalent to the given authorizations. ReBAC policy mining feasibility problem asks whether such a policy exists and if so to provide the policy. We investigate this problem in context of different ReBAC policy languages which differ in the relationships, inverse relationships and non-relationships that can be used to build the policy. We develop a feasibility detection algorithm and analyze its complexity. We show that our policy languages are progressively more expressive as we introduce additional capability. In case of infeasibility, various solution approaches are discussed.

关键词： Access control Policy mining Relationship-Based Access Control

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