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检索条件"任意字段=Proceedings of the first ACM conference on Data and application security and privacy"

共 1089 条记录，以下是31-40 订阅

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Mutual TLS in Practice: A Deep Dive into Certificate Configurations and privacy Issues 24

Mutual TLS in Practice: A Deep Dive into Certificate Configu...

引用

acm Internet Measurement conference (IMC)

作者： Dong, Hongying Zhang, Yizhe Lee, Hyeonmin Du, Kevin Tu, Guancheng Sun, Yixin Univ Virginia Charlottesville VA 22904 USA

ISBN: (纸本)9798400705922

Transport Layer security (TLS) is widely recognized as the essential protocol for securing Internet communications. While numerous studies have focused on investigating server certificates used in TLS connections, our study delves into the less explored territory of mutual TLS (mTLS) where both parties need to provide certificates to each other. By utilizing TLS connection logs collected from a large campus network over 23 months, we identify over 2.2 million unique server certificates and over 3.4 million unique client certificates used in over 1.2 billion mutual TLS connections. By jointly analyzing TLS connection data (e.g., port numbers) and certificate data (e.g., issuers for server/client certificates), we quantify the prevalent use of untrusted certificates and uncover potential security concerns resulting from misconfigured certificates, sharing of certificates between servers and clients, and long-expired certificates. Furthermore, we present the first in-depth study on the wide range of information included in CommonName (CN) and Subject Alternative Name (SAN), drawing comparison between client and server certificates, as well as revealing sensitive information.

关键词： Measurement Mutual Transport Layer security Mutual TLS Digital certificates privacy

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(In)visible privacy Indicator: security Analysis of privacy Indicator on Android Devices 19

(In)visible Privacy Indicator: Security Analysis of Privacy ...

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19th acm Asia conference on Computer and Communications security (acm AsiaCCS)

作者： Choe, Yurak Yu, Hyungseok Kim, Taeho Lee, Shinjae Lee, Hojoon Kim, Hyoungshick Sungkyunkwan Univ Suwon Gyeonggi Do South Korea Samsung Elect Suwon Gyeonggi Do South Korea

ISBN: (纸本)9798400704826

In Android 12, Google introduced a new security feature called the privacy indicator to protect users from spyware. The privacy indicator visually alerts users by displaying a green circle in the notification bar when an application accesses the camera. While this feature initially appears effective, our work has identified two possible attack scenarios that can undermine it. The first attack uses screen overlay techniques with a higher Z-order and deceptive status bar layouts to make it difficult to see the privacy indicator. In a user study involving 44 participants, only 13.6% of participants recognized the indicator under UI overlay attacks, compared to 63.6% in default Android 12 settings. The second attack exploits device configurations to disable the privacy indicator. Our findings were reported to the developers of the Android system UI at Samsung Electronics and the Google Issue Tracker, and we received acknowledgments from both parties. As countermeasures, we recommend ensuring the integrity of the privacy indicator using trusted execution facilities. We introduce a proof-of-concept solution called SEPI (security-Enhanced privacy Indicator), which utilizes a secure hypervisor and ARM TrustZone. SEPI is designed to detect camera and microphone activities, subsequently displaying the relevant indicator with the highest Z-order in a securely isolated display buffer. Our experimental findings revealed only a minimal 3.3% reduction in benchmark scores compared to the device's default operational state. The SEPI privacy indicator is displayed with a negligible mean delay of 20.92 ms.

关键词： Android privacy indicator Mobile platform security TrustZone

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DroidDefender: An Image-based Android Antimalware Proof-of-Concept 24

DroidDefender: An Image-based Android Antimalware Proof-of-C...

引用

14th acm conference on data and application security and privacy (acm CODASPY)

作者： Ciaramella, Giovanni Martinelli, Fabio Mercaldo, Francesco Santone, Antonella IMT Sch Adv Studies Lucca Lucca Italy CNR IIT Lucca Italy CNR IIT Pisa Italy Univ Molise Campobasso Italy CNR IIT Campobasso Italy

ISBN: (纸本)9798400704215

Malware analysis researchers are currently focused on the design and development of innovative approaches to detect zero-day malware, with particular regard to mobile environments. It is widely recognized that existing free and commercial anti-malware tools struggle to detect unknown threats, operating within the constraints of the signature-based paradigm. Among the set of techniques frequently exploited by researchers for spotting malware, machine learning, with particular regard to deep learning, is quickly gaining prominence as a highly promising method for zero-day malware detection. Unfortunately, many of the proposed methods are not effectively implemented in research prototypes and, therefore, do not truly become usable by end users. For this reason, in this paper, we present the DroidDefender proof-of-concept, an Android antimalware specifically designed and developed to detect zero-day malware. DroidDefender is based on representing an Android application as an image and employs a deep learning model. The DroidDefender research prototype is freely available for research purposes at the following URL: https://***/ Services/***?lang=en.

关键词： malware security Android testing deep learning

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application of Secure data Storage and Transmission in Cloud Computing Based on Blockchain Technology 24

Application of Secure Data Storage and Transmission in Cloud...

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2024 International conference on Intelligent Education and Computer Technology, IECT 2024

作者： Zhang, Yadong Zheng, Yujuan Yin, Chen Shi, Chunju School of Information Engineering Shandong Vocational University of Foreign Affairs Shandong Weihai China Information Center Shandong Drug and Food Vocational College Shandong Weihai China

ISBN: (纸本)9798400709920

How to solve data security and privacy protection in cloud computing is a very difficult issue, and data security is currently being paid more and more attention to. This article applies blockchain to cloud computing to realize the secure storage and transmission of data. This paper uses literature review and case analysis methods to study the application of secure data storage and transmission based on Blockchain technology in cloud computing. This paper first examines the existing relevant research results and practical application cases through a literature review. Then, this article selects several representative cases for in-depth analysis, including blockchain cloud storage, blockchain data transmission, and privacy protection. Finally, this article designed an experiment to test the feasibility of blockchain technology. Experiments have found that the data transmission speed of Blockchain technology is about 5-10gbps, which is highly secure and *** technology performs well in data security and privacy protection. © 2024 acm.

关键词： Cloud security

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A Unified Time Series Analytics based Intrusion Detection Framework for CAN BUS Attacks 24

A Unified Time Series Analytics based Intrusion Detection Fr...

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14th acm conference on data and application security and privacy (acm CODASPY)

作者： Maliha, Maisha Bhattacharjee, Shameek Western Michigan Univ Kalamazoo MI 49008 USA

ISBN: (纸本)9798400704215

Modern smart vehicles have a Controller Area Network (CAN) that supports intra-vehicle communication between intelligent Electronic Control Units (ECUs). The CAN is known to be vulnerable to various cyber attacks. In this paper, we propose a unified framework that can detect multiple types of cyber attacks (viz., Denial of Service, Fuzzy, Impersonation) affecting the CAN. Specifically, we construct a feature by observing the timing information of CAN packets exchanged over the CAN bus network over partitioned time windows to construct a low dimensional representation of the entire CAN network as a time series latent space. Then, we apply a two tier anomaly based intrusion detection model that keeps track of short term and long term memory of deviations in the initial time series latent space, to create a 'stateful latent space'. Then, we learn the boundaries of the benign stateful latent space that specify the attack detection criterion. To find hyper-parameters of our proposed model, we formulate a preference based multi-objective optimization problem that optimizes security objectives tailored for a network-wide time series anomaly based intrusion detector by balancing trade-offs between false alarm count, time to detection, and missed detection rate. We use real benign and attack datasets collected from a Kia Soul vehicle to validate our framework and show how our performance outperforms existing works.

关键词： anomaly detection intrusion detection vehicle CAN bus security

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IdDecoder: A Face Embedding Inversion Tool and its privacy and security Implications on Facial Recognition Systems 23

IdDecoder: A Face Embedding Inversion Tool and its Privacy a...

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13th acm conference on data and application security and privacy (CODASPY)

作者： Minh-Ha Le Carlsson, Niklas Linkoping Univ Linkoping Sweden

ISBN: (纸本)9798400700675

Most state-of-the-art facial recognition systems (FRS:s) use face embeddings. In this paper, we present the IdDecoder framework, capable of effectively synthesizing realistic-neutralized face images from face embeddings, and two effective attacks on state-of-the-art facial recognition models using embeddings. The first attack is a black-box version of a model inversion attack that allows the attacker to reconstruct a realistic face image that is both visually and numerically (as determined by the FRS:s) recognized as the same identity as the original face used to create a given face embedding. This attack raises significant privacy concerns regarding the membership of the gallery dataset of these systems and highlights the importance of both the people designing and deploying FRS:s paying greater attention to the protection of the face embeddings than currently done. The second attack is a novel attack that performs the model inversion, so to instead create the face of an alternative identity that is visually different from the original identity but has close identity distance (ensuring that it is recognized as being of the same identity). This attack increases the attacked system's false acceptance rate and raises significant security concerns. Finally, we use IdDecoder to visualize, evaluate, and provide insights into differences between three state-of-the-art facial embedding models.

关键词： Face embedding inversion Black-box attack Facial recognition

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SCAtt-man: Side-Channel-Based Remote Attestation for Embedded Devices that Users Understand 23

SCAtt-man: Side-Channel-Based Remote Attestation for Embedde...

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13th acm conference on data and application security and privacy (CODASPY)

作者： Surminski, Sebastian Niesler, Christian Linsner, Sebastian Davi, Lucas Reuter, Christian Univ Duisburg Essen Essen Germany Tech Univ Darmstadt Darmstadt Germany

ISBN: (纸本)9798400700675

From the perspective of end-users, IoT devices behave like a black box: As long as they work as intended, users will not detect any compromise. Users have minimal control over the software. Hence, it is very likely that the user misses that illegal recordings and transmissions occur if a security camera or a smart speaker is hacked. In this paper, we present SCAtt-man, the first remote attestation scheme that is specifically designed with the user in mind. SCAtt-man deploys software-based attestation to check the integrity of remote devices, allowing users to verify the integrity of IoT devices with their smartphones. The key novelty of SCAtt-man resides in the utilization of user-observable side-channels such as light or sound in the attestation protocol. Our proof-of-concept implementation targets a smart speaker and an attestation protocol that is based on a data-over-sound protocol. Our evaluation demonstrates the effectiveness of SCAtt-man against a variety of attacks and its usability based on a user study with 20 participants.

关键词： attestation firmware security IoT smart speaker

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All Your IoT Devices Are Belong to Us: securityWeaknesses in IoT Management Platforms 23

All Your IoT Devices Are Belong to Us: SecurityWeaknesses in...

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13th acm conference on data and application security and privacy (CODASPY)

作者： Tejaswi, Bhaskar Mannan, Mohammad Youssef, Amr Concordia Univ Montreal PQ Canada

ISBN: (纸本)9798400700675

IoT devices have become an integral part of our day to day activities, and are also being deployed to fulfil a number of industrial, enterprise and agricultural use cases. To efficiently manage and operate these devices, the IoT ecosystem relies on several IoT management platforms. Given the security-sensitive nature of the operations performed by these platforms, analyzing them for security vulnerabilities is critical to protect the ecosystem from potential cyber threats. In this work, by exploring the core functionalities offered by leading platforms, we first design a security evaluation framework. Subsequently, we use our framework to analyze 42 IoT management platforms. Our analysis uncovers a number of high severity unauthorized access vulnerabilities in 9/42 platforms, which could lead to attacks such as remote SIM deactivation, IoT SIM overcharging and device data forgery. Furthermore, we find broken authentication in 11/42 platforms, including complete account takeover on 7/42 platforms, along with remote code execution on one of the platforms. Overall, on 11/42 platforms, we find vulnerabilities that could lead to platform-wide attacks, that affect all users and all devices connected to those platforms.

关键词： IoT management platforms IoT security Web security

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ELSEIR: A privacy-Preserving Large-Scale Image Retrieval Framework for Outsourced data Sharing 24

ELSEIR: A Privacy-Preserving Large-Scale Image Retrieval Fra...

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4th Annual International conference on Multimedia Retrieval (ICMR)

作者： Tang, Zixin Fan, Haihui Gu, Xiaoyan Li, Yang Li, Bo Wang, Xin Chinese Acad Sci Univ Chinese Acad Sci Inst Informat Engn Sch Cyber SecurKey Lab Cyberspace Secur Def Beijing Peoples R China Chinese Acad Sci Inst Informat Engn Key Lab Cyberspace Secur Def Beijing Peoples R China China Mobile Informat Technol Ctr Shenzhen Peoples R China

ISBN: (纸本)9798400706028

privacy-preserving content-based image retrieval aims to safeguard the security of outsourced private images while maintaining their searchability. However, existing schemes encounter challenges in striking a balance between security, accuracy, and efficiency, as well as difficulties in scaling to large-scale image retrieval in multi-user settings. In this paper, we propose a novel Efficient Large-Scale Encrypted Image Retrieval (ELSEIR) framework for outsourced data sharing. We first utilize a deep hashing model for image feature extraction. Building upon this, we design an irreversible random hash code generation method that incorporates permutation keys for personalized access and integrates differential privacy to further enhance data security. In our multi-user implementation, we distribute the switch keys to the cloud to standardize each key, enabling the accurate search. In addition, we have theoretically proven that our ELSEIR guarantees both outsourced data security and query user privacy. Extensive experiments on real-world datasets demonstrate that our ELSEIR yields comparable accuracy to the unprotected baseline while outperforming existing methods in terms of both retrieval accuracy and efficiency.

关键词： privacy-Preserving Content-Based Image Retrieval Outsourcing Deep Hashing Differential privacy

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GROTE: Group Testing for privacy-Preserving Face Identification 23

GROTE: Group Testing for Privacy-Preserving Face Identificat...

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13th acm conference on data and application security and privacy (CODASPY)

作者： Ibarrondo, Alberto Chabanne, Herve Despiegel, Vincent Onen, Melek Idemia Paris France EURECOM Sophia Antipolis France

ISBN: (纸本)9798400700675

This paper proposes a novel method to perform privacy-preserving face identification based on the notion of group testing, and applies it to a solution using the Cheon-Kim-Kim-Song (CKKS) homomorphic encryption scheme. Securely computing the closest reference template to a given live template requires.. comparisons, as many as there are identities in a biometric database. Our solution, named GROTE, replaces element-wise testing by group testing to drastically reduce the number of such costly, non-linear operations in the encrypted domain from K to up to 2 root K. More specifically, we approximate the max of the coordinates of a large vector by raising to the alpha-th power and cumulative sum in a 2D layout, incurring a small impact in the accuracy of the system while greatly speeding up its execution. We implement GROTE and evaluate its performance.

关键词： Secure Biometrics Face Identification Homomorphic Encryption privacy Enhancing Technologies

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