The proceedings contain 43 papers. The topics discussed include: estimating the runtime and global network traffic of SMPC protocols;a unified time series analytics based intrusion detection framework for CAN BUS atta...
ISBN:
(纸本)9798400704215
The proceedings contain 43 papers. The topics discussed include: estimating the runtime and global network traffic of SMPC protocols;a unified time series analytics based intrusion detection framework for CAN BUS attacks;investigating TLS version downgrade in enterprise software;examining cryptography and randomness failures in open-source cellular cores;nothing personal: understanding the spread and use of personally identifiable information in the financial ecosystem;CCSM: building cross-cluster security models for edge-core environments involving multiple Kubernetes clusters;process-aware intrusion detection in MQTT networks;accelerating performance of bilinear map cryptography using FPGA;exploiting update leakage in searchable symmetric encryption;and the avg-act swap and plaintext overflow detection in fully homomorphic operations over deep circuits.
The proceedings contain 30 papers. The topics discussed include: comparative privacy analysis of mobile browsers;IdDecoder: a face embedding inversion tool and its privacy and security implications on facial recogniti...
ISBN:
(纸本)9798400700675
The proceedings contain 30 papers. The topics discussed include: comparative privacy analysis of mobile browsers;IdDecoder: a face embedding inversion tool and its privacy and security implications on facial recognition systems;attribute inference attacks in online multiplayer video games: a case study on DOTA2;AutoSpill: credential leakage from mobile password managers;multi-modality mobile datasets for behavioral biometrics research: data/toolset paper;a tenant-based two-stage approach to auditing the integrity of virtual network function chains hosted on third-party clouds;CloudShield: real-time anomaly detection in the cloud;Grote: group testing for privacy-preserving face identification;anonymous system for fully distributed and robust secure multi-party computation;and protecting encrypted virtual machines from nested page fault controlled channel.
The proceedings contain 45 papers. The topics discussed include: how (not) to deploy cryptography on the Internet;GINN: fast GPU-TEE based integrity for neural network training;leveraging synthetic data and PU learnin...
ISBN:
(纸本)9781450392204
The proceedings contain 45 papers. The topics discussed include: how (not) to deploy cryptography on the Internet;GINN: fast GPU-TEE based integrity for neural network training;leveraging synthetic data and PU learning for phishing email detection;DP-UTIL: comprehensive utility analysis of differential privacy in machine learning;privacy-preserving maximum matching on general graphs and its application to enable privacy-preserving kidney exchange;towards automated content-based photo privacy control in user-centered social networks;genomic data sharing under dependent local differential privacy;prediction of mobile app privacy preferences with user profiles via federated learning;building a commit-level dataset of real-world vulnerabilities;and ReSIL: revivifying function signature inference using deep learning with domain-specific knowledge.
The proceedings contain 38 papers. The topics discussed include: membership inference attacks and defenses in classification models;using single-step adversarial training to defend iterative adversarial examples;real-...
ISBN:
(纸本)9781450381437
The proceedings contain 38 papers. The topics discussed include: membership inference attacks and defenses in classification models;using single-step adversarial training to defend iterative adversarial examples;real-time evasion attacks against deep learning-based anomaly detection from distributed system logs;we can pay less: coordinated false data injection attack against residential demand response in smart grids;brittle features of device authentication;role-based deception in enterprise networks;security threats from bitcoin wallet smartphone applications: vulnerabilities, attacks, and countermeasures;and adaptive fingerprinting: website fingerprinting over few encrypted traffic.
The proceedings contain 35 papers. The topics discussed include: understanding the responsiveness of mobile app developers to software library updates;acminer: extraction and analysis of authorization checks in androi...
ISBN:
(纸本)9781450360999
The proceedings contain 35 papers. The topics discussed include: understanding the responsiveness of mobile app developers to software library updates;acminer: extraction and analysis of authorization checks in android’s middleware;verifiable round-robin scheme for smart homes;dynamic groups and attribute-based access control for next-generation smart cars;a study of data store-based home automation;detection of threats to iot devices using scalable VPN-forwarded honeypots;deep neural networks classification over encrypted data;curie: policy-based secure data exchange;result-based detection of insider threats to relational databases;custom-made anonymization by data analysis program provided by recipient;and toward efficient spammers gathering in twitter social networks.
Despite the enormous data processing capacity available in big data frameworks, obtaining appropriate and private responses to large-scale queries without revealing sensitive information is still a challenging problem...
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ISBN:
(纸本)9798400704215
Despite the enormous data processing capacity available in big data frameworks, obtaining appropriate and private responses to large-scale queries without revealing sensitive information is still a challenging problem. In this paper, we address the problem of combining offline sampling techniques for space efficiency in multidimensional databases and Differential privacy (DP) to protect sensitive data. We present our framework SLIM-View, which uses a novel sampling technique relying on a bi-objective optimization to decide the best sample size and the exponential mechanism to select the best sample while ensuring privacy. Our extensive experiments demonstrate that SLIM-View outperforms existing approaches by orders of magnitude in terms of utility and scalability while ensuring the same level of privacy.
With the increasing usage of mental health applications (MHAs), there is growing concern regarding their dataprivacy practices. Analyzing 437 user reviews from 83 apps, we outline users' predominant privacy and s...
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ISBN:
(纸本)9798400703300
With the increasing usage of mental health applications (MHAs), there is growing concern regarding their dataprivacy practices. Analyzing 437 user reviews from 83 apps, we outline users' predominant privacy and security concerns with currently available apps. We then compare those concerns to criteria from two prominent app evaluation websites - privacy Not Included and One Mind PsyberGuide. Our findings show that MHA users have myriad dataprivacy and security concerns including a user's control over their own data, but these concerns do not often overlap with those of experts from evaluation websites who focus more on issues such as required password strength. We highlight this disconnect and propose solutions in how the mental health care ecosystem can provide better guidance to MHA users and experts from the fields of privacy and security and mental health technology in choosing and evaluating, respectively, potentially useful mental health apps.
The notion of epsilon-differential privacy is a widely used concept of providing quantifiable privacy to individuals. However, it is unclear how to explain the level of privacy protection provided by a differential pr...
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ISBN:
(纸本)9798400704215
The notion of epsilon-differential privacy is a widely used concept of providing quantifiable privacy to individuals. However, it is unclear how to explain the level of privacy protection provided by a differential privacy mechanism with a set epsilon. In this study, we focus on users' comprehension of the privacy protection provided by a differential privacy mechanism. To do so, we study three variants of explaining the privacy protection provided by differential privacy: (1) the original mathematical definition;(2) epsilon translated into a specific privacy risk;and (3) an explanation using the randomized response technique. We compare users' comprehension of privacy protection employing these explanatory models with their comprehension of privacy protection of kappa-anonymity as baseline comprehensibility. Our findings suggest that participants' comprehension of differential privacy protection is enhanced by the privacy risk model and the randomized response-based model. Moreover, our results confirm our intuition that privacy protection provided by :-anonymity is more comprehensible.
This paper investigates an underexplored avenue of cybersecurity threats in mobile computing, with a particular focus on the Android platform which, due to its open nature and widespread adoption, is a fertile ground ...
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ISBN:
(纸本)9798400704215
This paper investigates an underexplored avenue of cybersecurity threats in mobile computing, with a particular focus on the Android platform which, due to its open nature and widespread adoption, is a fertile ground for cyber threats. We present a Proof-of-Concept (PoC) Android application that, while ostensibly benign, can execute covert malicious operations by exploiting the process of permission granted. Specifically, the app manipulates accessibility permissions to autonomously acquire additional permissions needed for executing unauthorized activities without the user's knowledge. Our work outlines conditions for minimal detection risk, leveraging periods when users are less likely to interact with their devices. The study provides a deeper understanding of the abuse potential of Android's accessibility features and highlights the critical need for comprehensive security measures to counteract such exploitations.
Biometric authentication eliminates the need for users to remember secrets and serves as a convenient mechanism for user authentication. Traditional implementations of biometric-based authentication store sensitive us...
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ISBN:
(纸本)9798400704215
Biometric authentication eliminates the need for users to remember secrets and serves as a convenient mechanism for user authentication. Traditional implementations of biometric-based authentication store sensitive user biometry on the server and the server becomes an attractive target of attack and a source of large-scale unintended disclosure of biometric data. To mitigate the problem, we can resort to privacy-preserving computation and store only protected biometrics on the server. While a variety of secure computation techniques is available, our analysis of privacy-preserving biometric authentication constructions revealed that available solutions fall short of addressing the challenges of privacy-preserving biometric authentication. Thus, in this work we put forward new constructions to address the challenges. Our solutions employ a helper server and use strong threat models, where a client is always assumed to be malicious, while the helper server can be semi-honest or malicious. We also determined that standard secure multi-party computation definitions are insufficient to properly demonstrate security in the two-phase (enrollment and authentication) entity authentication application. We thus extend the model and formally show security in the multi-phase setting, where information can flow from one phase to another and the set of participants can change between the phases. We implement our constructions and show that they exhibit practical performance for authentication in real time.
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