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Towards Automated Content-based Photo privacy Control in User-Centered Social Networks 22

Towards Automated Content-based Photo Privacy Control in Use...

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

作者： Vishwamitra, Nishant Li, Yifang Hu, Hongxin Caine, Kelly Cheng, Long Zhao, Ziming Ahn, Gail-Joon Univ Buffalo Buffalo NY 14260 USA Clemson Univ Clemson SC USA Arizona State Univ Tempe AZ USA

ISBN: (纸本)9781450392204

A large number of photos shared online often contain private user information, which can cause serious privacy breaches when viewed by unauthorized users. Thus, there is a need for more efficient privacy control that requires automatic detection of users' private photos. However, the automatic detection of users' private photos is a challenging task, since different users may have different privacy concerns and a generalized one-size-fits-all approach for private photo detection would not be suitable for most users. User-specific detection of private photos should, therefore, be investigated. Furthermore, for effective privacy control, the exact sensitive regions in private photos need to be pinpointed, so that sensitive content can be protected via different privacy control methods. In this paper, we propose a novel system, AutoPri, to enable automatic and user-specific content-based photo privacy control in online social networks. We collect a large dataset of 31, 566 private and public photos from real-world users and present important observations on photo privacy concerns. Our system can automatically detect private photos in a user-specific manner using a detection model based on a multimodal variational autoencoder and pinpoint sensitive regions in private photos with an explainable deep learning-based approach. Our evaluations show that AutoPri can effectively determine user-specific private photos with high accuracy (94.32%) and pinpoint exact sensitive regions in them to enable effective privacy control in user-centered online social networks.

关键词： privacy control social media deep learning

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Toward Deep Learning Based Access Control 22

Toward Deep Learning Based Access Control

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

作者： Nobi, Mohammad Nur Krishnan, Ram Huang, Yufei Shakarami, Mehrnoosh Sandhu, Ravi Univ Texas San Antonio Inst Cyber Secur ICS San Antonio TX 78285 USA Univ Texas San Antonio Dept Comp Sci San Antonio TX 78285 USA Univ Texas San Antonio ICS NSF Ctr Secur & Privacy Enhanced Cloud Comp C San Antonio TX USA Univ Texas San Antonio Dept Elect & Comp Engn San Antonio TX USA Univ Pittsburgh Dept Med Pittsburgh PA USA UPMC Hillman Canc Ctr Pittsburgh PA USA Univ Texas San Antonio ICS C SPECC San Antonio TX USA

ISBN: (纸本)9781450392204

A common trait of current access control approaches is the challenging need to engineer abstract and intuitive access control models. This entails designing access control information in the form of roles (RBAC), attributes (ABAC), or relationships (ReBAC) as the case may be, and subsequently, designing access control rules. This framework has its benefits but has significant limitations in the context of modern systems that are dynamic, complex, and large-scale, due to which it is difficult to maintain an accurate access control state in the system for a human administrator. This paper proposes Deep Learning Based Access Control (DLBAC) by leveraging significant advances in deep learning technology as a potential solution to this problem. We envision that DLBAC could complement and, in the long-term, has the potential to even replace, classical access control models with a neural network that reduces the burden of access control model engineering and updates. Without loss of generality, we conduct a thorough investigation of a candidate DLBAC model, called DLBAC(alpha), using both real-world and synthetic datasets. We demonstrate the feasibility of the proposed approach by addressing issues related to accuracy, generalization, and explainability. We also discuss challenges and future research directions.

关键词： Access control Deep learning Automation

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Towards Resiliency of Heavy Vehicles through Compromised Sensor data Reconstruction 22

Towards Resiliency of Heavy Vehicles through Compromised Sen...

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

作者： Shirazi, Hossein Pickard, William Ray, Indrakshi Wang, Haonan Colorado State Univ Ft Collins CO 80523 USA

ISBN: (纸本)9781450392204

Almost all aspects of modern automobiles are controlled by embedded computers, known as Electronic Control Units (ECUs). ECUs are connected with each other over a Controller Area Network (CAN) network. ECUs communicate with each other and control the automobile's behavior using messages. Heavy vehicles, unlike passenger cars, are constructed using ECUs manufactured by different Original Equipment Manufacturers (OEMs). For reasons of interoperability, the Society of Automotive Engineers (SAE) mandates that all ECUs should communicate using the standardized SAE-J1939 protocol that gives semantics to the signals transmitted on the CAN network. security concerns have been historically ignored in protocols and standards. Consequently, an ECU having malicious code can spoof other ECUs, e.g., a message can be injected through the OBD-II port or the telematics unit into the internal network to interfere with the behavior of the vehicle. Intrusion Detection Systems (IDS) have been proposed and utilized to detect various types of security attacks. However, such systems are only capable of detecting attacks and cannot mitigate them. A compromised ECU may generate invalid data values;even if such invalid values are detected, there is still a need to counter their effects. Almost all prior works focus on detecting attacks. We demonstrate how to make the vehicle resilient to attacks. We analyze the log files of real driving scenarios and show ECUs are significantly dependent on other ECUs to operate. We demonstrate that parameters of a compromised ECU can be reconstructed from those of other non-compromised ECUs to allow the vehicle to continue operation and make it resilient to attacks. We achieve this by modeling the behavior of an ECU using the multivariate Long Short-Term Memory (LSTM) neural network. We then reconstruct compromised ECU values using information obtained from trustworthy ECUs. Despite some levels of errors, our model can reconstruct trustworthy data values tha

关键词： Heavy Vehicle security Resiliency LSTM Network

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Conan: Distributed Proofs of Compliance for Anonymous data Collection 24

Conan: Distributed Proofs of Compliance for Anonymous Data C...

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31st conference on Computer and Communications security

作者： Zhou, Mingxun Fanti, Giulia Shi, Elaine Carnegie Mellon Univ Pittsburgh PA 15213 USA IC3 New York NY 10044 USA CyLab Secure Blockchain Initiat Pittsburgh PA 15213 USA

ISBN: (纸本)9798400706363

We consider how to design an anonymous data collection protocol that enforces compliance rules. Imagine that each client contributes multiple data items (e.g., votes, location crumbs, or secret shares of its input) to an abstraction of an anonymous network, which mixes all clients' data items so that the receiver cannot determine which data items belong to the same user. Now, each user must prove to an auditor that the set it contributed satisfies a compliance predicate, without identifying which items it contributed. For example, the auditor may want to ensure that no voter voted for the same candidate twice, or that a user's location crumbs are not too far apart in a given time interval. Our main contribution is a novel anonymous, compliant data collection protocol that realizes the above goal. In comparison with naive approaches such as generic multi-party computation or earlier constructions of collaborative zero-knowledge proofs, the most compelling advantage of our approach is that each client's communication and computation overhead do not grow with respect to the number of clients... In this sense, we save a factor of at least.. over prior work, which allows our technique to scale to applications with a large number of clients, such as anonymous voting and privacy-preserving federated learning. We first describe our protocol using generic cryptographic primitives that can be realized from standard assumptions. We then suggest a concrete instantiation called Conan which we implement and evaluate. In this concrete instantiation, we are willing to employ SNARKs and the random oracle model for better practical efficiency. Notably, in this practical instantiation, each client's additional communication overhead (not counting the overhead of sending its data items over the anonymous network) is only (O) over tilde ( 1). We evaluated our technique in various application settings, including secure voting, and secure aggregation protocols for histogram, summation, an

关键词： Distributed Zero Knowledge Proofs Anonymous data Collection

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IIoT-ARAS: IIoT/ICS Automated Risk Assessment System for Prediction and Prevention 21

IIoT-ARAS: IIoT/ICS Automated Risk Assessment System for Pre...

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

作者： Zahran, Bassam Hussaini, Adamu Ali-Gombe, Aisha Towson Univ Towson MD 21252 USA

ISBN: (纸本)9781450381437

As IT/OT convergence continues to evolve, the traditionally isolated ICS/OT systems are increasingly exposed to a myriad of online and offline threats. Although IIoT enhances the reachability in ICS, improved data analytics, ensuring ease of access and decision making, it unwittingly opens the ICS environment to attackers. The design of IIoT introduces multiple entry points to an isolated system, which is used to protect itself via air-gapping and risk avoidance strategies. This study explores a comprehensive mapping of threats and risks for IT/OT convergence. Additionally, we propose IIoT-ARAS - an automated risk assessment system based on OCTAVE Allegro and ISO/IEC 27030 methodologies. The design of IIoT-ARAS is aimed to be agentless, with minimum interruptions to the OT environment. Furthermore, the system performs automated regular asset inventory checks, threshold optimization, probability computation, risk evaluations, and contingency plan configuration.

关键词： Cybersecurity security IIoT ICS IT/OT Convergence

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security Threats from Bitcoin Wallet Smartphone applications: Vulnerabilities, Attacks, and Countermeasures 21

Security Threats from Bitcoin Wallet Smartphone Applications...

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

作者： Hu, Yiwen Wang, Sihan Tu, Guan-Hua Xiao, Li Xie, Tian Lei, Xinyu Li, Chi-Yu Michigan State Univ Dept Comp Sci & Engn E Lansing MI 48824 USA Natl Chiao Tung Univ Dept Comp Sci Hsinchu Taiwan

ISBN: (纸本)9781450381437

Nowadays, Bitcoin is the most popular cryptocurrency. With the proliferation of smartphones and the high-speed mobile Internet, more and more users have started accessing their Bitcoin wallets on their smartphones. Users can download and install a variety of Bitcoin wallet applications (e.g., Coinbase, Luno, Bitcoin Wallet) on their smartphones and access their Bitcoin wallets anytime and anywhere. However, it is still unknown whether these Bitcoin wallet smartphone applications are secure or if they are new attack surfaces for adversaries to attack these application users. In this work, we explored the insecurity of the 10 most popular Bitcoin wallet smartphone applications and discovered three security vulnerabilities. By exploiting them, adversaries can launch various attacks including Bitcoin deanonymization, reflection and amplification spamming, and wallet fraud attacks. To address the identified security vulnerabilities, we developed a phone-side Bitcoin security Rectifier to secure Bitcoin wallet smartphone application users. The developed rectifier does not require any modifications to current wallet applications and is compliant with Bitcoin standards.

关键词： Bitcoin wallets Blockchain security Mobile networks

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We Can Pay Less : Coordinated False data Injection Attack Against Residential Demand Response in Smart Grids 21

We Can Pay Less : Coordinated False Data Injection Attack Ag...

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

作者： Dayaratne, Thusitha Rudolph, Carsten Liebman, Ariel Salehi, Mahsa Monash Univ Clayton Vic Australia

ISBN: (纸本)9781450381437

Advanced metering infrastructure, along with home automation processes, is enabling more efficient and effective demand-side management opportunities for both consumers and utility companies. However, tight cyber-physical integration also enables novel attack vectors for false data injection attacks (FDIA) as home automation/home energy management systems reside outside the utilities' control perimeter. Authentic users themselves can manipulate these systems without causing significant security breaches compared to traditional FDIAs. This work depicts a novel FDIA that exploits one of the commonly utilised distributed device scheduling architectures. We evaluate the attack impact using a realistic dataset to demonstrate that adversaries gain significant benefits, independently from the actual algorithm used for optimisation, as long as they have control over a sufficient amount of demand. Compared to traditional FDIAs, reliable security mechanisms such as proper authentication, security protocols, security controls or, sealed/controlled devices cannot prevent this new type of FDIA. Thus, we propose a set of possible impact alleviation solutions to thwart this type of attack.

关键词： Demand response False data injection attack Impact alleviation Smart grid vulnerabilities

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PeriScope: Comprehensive Vulnerability Analysis of Mobile App-defined Bluetooth Peripherals 22

PeriScope: Comprehensive Vulnerability Analysis of Mobile Ap...

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17th acm ASIA conference on Computer and Communications security 2022 (acm ASIACCS)

作者： Zhao, Qingchuan Zuo, Chaoshun Blasco, Jorge Lin, Zhiqiang City Univ Hong Kong Hong Kong Peoples R China Ohio State Univ Columbus OH 43210 USA Royal Holloway Univ London Egham Surrey England

ISBN: (纸本)9781450391405

Many IoT devices today talk to each other via Bluetooth Low Energy (BLE), a wireless communication technology often used to exchange data between a paired central and peripheral. These peripheral devices include not only firmware-defined bare-metal peripherals but also mobile application defined peripherals where a mobile app turns a smartphone into a peripheral instead of their usual central role. However, this role reversal increases the attack surface and brings vulnerabilities in bare-metal Bluetooth peripherals to mobile apps where relevant security and privacy have not been well studied. To fill this knowledge gap, this paper presents PeriScope, an automated tool to unveil the security and privacy vulnerabilities at the link layer of app-defined Bluetooth peripherals in the procedures of broadcasting, pairing, and communication by systematically analyzing their companion mobile apps. PeriScope has analyzed 1,160 Bluetooth peripheral apps from Google Play and identified 69.13% of them that broadcast device or personal identifiable information in cleartext, and, in addition, there are 95% pieces of data managed by these apps (e.g., personal health data and digital keys to unlock doors) to exchange with connected devices can be accessed without authentication. Finally, a set of guidelines for secure app-defined Bluetooth peripherals development is also provided.

关键词： Bluetooth low energy mobile app analysis IoT security

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Towards Accurate Labeling of Android Apps for Reliable Malware Detection 21

Towards Accurate Labeling of Android Apps for Reliable Malwa...

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

作者： Salem, Aleieldin Tech Univ Munich Garching Germany

ISBN: (纸本)9781450381437

In training their newly-developed malware detection methods, researchers rely on threshold-based labeling strategies that interpret the scan reports provided by online platforms, such as VirusTotal. The dynamicity of this platform renders those labeling strategies unsustainable over prolonged periods, which leads to inaccurate labels. Using inaccurately labeled apps to train and evaluate malware detection methods significantly undermines the reliability of their results, leading to either dismissing otherwise promising detection approaches or adopting intrinsically inadequate ones. The infeasibility of generating accurate labels via manual analysis and the lack of reliable alternatives force researchers to utilize VirusTotal to label apps. In the paper, we tackle this issue in two manners. Firstly, we reveal the aspects of VirusTotal's dynamicity and how they impact threshold-based labeling strategies and provide actionable insights on how to use these labeling strategies given VirusTotal's dynamicity reliably. Secondly, we motivate the implementation of alternative platforms by (a) identifying VirusTotal limitations that such platforms should avoid, and (b) proposing an architecture of how such platforms can be constructed to mitigate VirusTotal's limitations.

关键词： android security malware detection machine learning virustotal

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privacy - From the Ivory Tower to the Trenches in the Parliament 25

Privacy - From the Ivory Tower to the Trenches in the Parlia...

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

作者： Orr Dunkelman Computer Science Dept. University of Haifa Haifa Israel and Security in Telecommunications (SecT) Technische Universität Berlin Berlin Germany

ISBN: (纸本)9798400714764

privacy is a fundamental human right, but it is also one of the more complicated rights. Not only privacy is very context-oriented and society-oriented, it is hard to define privacy without involving adversaries trying to break it. The conceived tension between ''national security'' or ''public order'' and the basic human right of privacy, impacts the adoption of privacy Enhancing Technologies (PETs), and at times, hinders the ability to offer privacy to *** this talk, we will discuss a few topics where such a conflict exists, such as biometric data, contact tracing, and COVID certificates. We will discuss the importance of incorporating privacy into our technical work, thus making a real-life impact by offering solutions that offer better privacy. We will discuss the problems in disseminating state-of-the-art scientific knowledge to the *** will then consider the problem of discussing these issues with policy makers, as they are the ones making the call, while not necessarily understanding the impact of complicated technologies for (and on) privacy.

关键词： biometrics

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