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检索条件"任意字段=Proceedings of the 5th ACM Conference on Data and Application Security and Privacy"

共 1522 条记录，以下是781-790 订阅

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Custom-made Anonymization by data Analysis Program Provided by Recipient 19

Custom-made Anonymization by Data Analysis Program Provided ...

引用

9th acm conference on data and application security and privacy (CODASPY)

作者： Maeda, Wakana Yamaoka, Yuji Fujitsu Labs Ltd Kawasaki Kanagawa Japan

ISBN: (纸本)9781450360999

Anonymization is a method used in privacy-preserving data publishing. Previous studies show that anonymization based on the request of a data recipient, the priority of attributes, helps to maintain data utility. However, it is difficult for recipients to generate requests because they can not know which attribute important without data analysis. To address this issue, we propose a framework for performing custom-made anonymization by data analysis program provided by recipient. this enables the recipient to generate a request after creating a program and performing an indirect analysis of an original dataset by the program. Moreover, we describe an inference attack model for this framework and propose a secure method for restraining such an attack.

关键词： privacy-preserving data publishing indirect analysis anonymiazation

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Aviation Scenarios for 5G and Beyond 39

Aviation Scenarios for 5G and Beyond

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39th AIAA/IEEE Digital Avionics Systems conference (DASC)

作者： Matti, Erik Johns, Oliver Khan, Suleman Gurtov, Andrei Josefsson, Billy Linkoping Univ Dept Comp & Informat Sci Linkoping Sweden Luftfartsverket Norrkoping Sweden

ISBN: (纸本)9781728198255

Aviation (both manned and unmanned) offers many novel application scenarios for 5th and 6th (XG) generation mobile networks. For drones (Unmanned Aircraft), navigation in challenging environments, such as urban with tall buildings with GNSS satellite position is problematic. XG could offer positioning as a free add-on thanks to advanced radio techniques such as beam-forming. therefore, it could provide energy-efficient positioning service for UAs. Furthermore, drones could be used as portable base stations or relay points to rapidly deploy a network, for example in natural disaster environment. With proper signal direction, XG base stations can also provide Internet connectivity to passengers and planes over ground, to save expensive satellite communications. It could be even possible for messages to cross oceans with hop-by-hop data relay between airplanes. Finally, aviation itself includes the need for data exchange between pilots, controllers and plane manufacturers. Current air traffic communication systems are very slow, unreliable and suffer from a complete lack of security. therefore, XG could be an excellent replacement by providing ultra-reliable and authenticated data exchange in critical scenarios, such as pilot and plane communication during landing. In this paper, we perform a literature survey to explore possible XG scenarios for aviation, with special focus on security.

关键词： Aviation security UA Air Traffic 6G

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Preserving privacy of data with Efficient Attribute-based Encryption Schemes 21

Preserving Privacy of Data with Efficient Attribute-based En...

引用

Adjunct proceedings of the 29th acm conference on User Modeling, Adaptation and Personalization

作者： Nikos Komninos City University of London United Kingdom

ISBN: (纸本)9781450383677

Attribute-based encryption (ABE) schemes and their variations are often applied to preserve the privacy of data. In particular, ABE schemes proposals are resilient to multiple attacks, including attacks in interception, interruption, modification, fabrication, unauthorized authentication, and access of data. Existing proposals have several limitations, such as the generation, verification, and distribution of digital certificates incur extra computation and communication overhead which are not suitable for resource-constrained computing. Furthermore, in most of the ABE schemes, a certification authority (CA) generates the public/secret keys according to a set of attributes. However, the compromise of CA can endanger the secret keys, therefore, the secrecy of encrypted messages. Some of the existing ABE schemes are based on bilinear pairing that requires large security parameters, which make ABE schemes unsuitable for resource-constrained computing devices. the current ABE proposals [1, 2, 3, 4] are complex because they require implementing large-number security parameters (i.e., 2048-bit or 4096-bit size) to achieve 2128 security. Besides that, those ABE schemes consider a CA with an active role in the application process. the CA generates and distributes secret keys to devices or users. Nonetheless, sharing private attributes with the CA can risk data and user privacy, since the CA can also decrypt messages, depending on the application scenario, and retrieve the data. Moreover, the compromise of CA poses a risk to the communication secrecy between the sender and the receiver. In addition, some studies propose symmetric key schemes for resource-constrained devices. However, in large-scale networked systems, the symmetric key management becomes very complex and inefficient. the symmetric-key deployment often requires a separate protocol for session key agreement and generation. In IoT networks where mostly short-sized data is exchanged, symmetric key encryption sche

关键词： privacy preservation key update key revocation Attribute based encryption

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PrivStream: Differentially Private Event Detection on data Streams 19

PrivStream: Differentially Private Event Detection on Data S...

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9th acm conference on data and application security and privacy (CODASPY)

作者： Fanaeepour, Maryam Machanavajjhala, Ashwin Duke Univ Dept Comp Sci Durham NC 27706 USA

ISBN: (纸本)9781450360999

Event monitoring and detection in real-time systems is crucial. Protecting users' data while reporting an event in almost real-time will increase the level of this challenge. In this work, we adopt the strong notion of differential privacy to private stream counting for event detection with the aim of minimizing false positive and false negative rates as our utility metrics.

关键词： data Stream Differential privacy Event Detection Real-time Analytics

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Research and application of Blockchain Technology in Transportation Administrative Law Enforcement 5

Research and Application of Blockchain Technology in Transpo...

引用

5th IEEE Information Technology and Mechatronics Engineering conference, ITOEC 2020

作者： Wanhua, Luo China Academy of Transportation Sciences Room 810 Office Building 1 No. 10 Hepingli East Street Dongcheng District Beijing China

ISBN: (纸本)9781728143224

According to the overall goal of rule the society by law, combined with specific requirements such as the records of the entire process of law enforcement in the three systems, the information such as law enforcement evidence plays a key supporting role. When design a law enforcement case handling information system, it is necessary to fully consider the collection, generation, storage, and transmission of law enforcement information how to ensure that the information is safe and reliable and not tampered. 'Let law enforcement data runs on the blockchain' which use blockchain, big data and other related technologies to store and transmit information such as law enforcement evidence securely, and comprehensively improve the effectiveness and security of law enforcement data. © 2020 IEEE.

关键词： Informatization

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Review of Image encryption techniques using neural network for optical security in the healthcare sector - PNO System 5

Review of Image encryption techniques using neural network f...

引用

5th IEEE International conference on Innovative Technologies in Intelligent Systems and Industrial applications, CITISIA 2020

作者： Su, Jinfeng Kankani, Anup Zajko, George Elchouemi, Amr Kurniawan, Hendra Study Group Australia Sydney Australia American Public University System United States IIB Darmajaya Lampung Indonesia

ISBN: (纸本)9781728194370

Image encryption is used to encrypt patient images that contain diagnostic information about patients in healthcare. the healthcare sector uses electronic media to support the transmission of scanning results, such as X-rays, MRI scans and ultrasound images. the primary purpose of this paper is to investigate encryption of images through techniques utilising neural networks to maintain security and privacy of patient records. Patient image data, neural network-based encryption, and optical security (PNO) systems are examined in this research work. these components will provide some validation in the use of neural network-enabled image encryption in healthcare. the evaluation of the PNO system is based on different quality factors, which are compared in a classification of the 30 state-of-the-art solutions in image encryption. the effectiveness of the encryption process can be increased in terms of high accuracy, less noise and enhanced security. We conclude that using neural network-based encryption techniques can increase security in visual media in the healthcare sector. © 2020 IEEE.

关键词： Cryptography

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Unsupervised Pixel-level Crack Detection Based on Generative Adversarial Network 20

Unsupervised Pixel-level Crack Detection Based on Generative...

引用

5th International conference on Multimedia Systems and Signal Processing, ICMSSP 2020

作者： Duan, Lijuan Geng, Huiling Pang, Junbiao Zeng, Jun Beijing University of Technology Beijing China Beijing Key Laboratory of Trusted Computing Beijing China Natl. Engineering Laboratory for Critical Technologies of Information Security Classified Protection Beijing China

ISBN: (纸本)9781450377485

Automatic crack detection from pavement images is an import research field. Meanwhile, crack detection is a challenge task: (1) manual labels are subjective because of low contrast between crack and the surrounding pavement and heavy workload;(2) the excessive dependence of supervised deep learning training on labels. To address these problems, we present an unsupervised method for learning mapping to translate crack images to binary images based on generative adversarial network. We introduce the cyclic consistent loss to increase accuracy of crack localization. Eight residual blocks connected convolutional neural network for feature extraction is used as generator and a 5-layer fully convolutional network is used as discriminator. We analyze the proposed framework and provide qualitative and quantitative comparison. the experimental results show that the proposed method achieves a better performance than several existing methods. © 2020 acm.

关键词： Crack detection

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Detecting Android Malware Based on Dynamic Feature Sequence and Attention Mechanism

Detecting Android Malware Based on Dynamic Feature Sequence ...

引用

Cryptography, security and privacy (CSP), IEEE International conference on

作者： Hanlin Long Zhicheng Tian Yang Liu College of Computer Science and Technology Harbin Institute of Technology Shenzhen China Cyberspace Security Research Center Peng Cheng Laboratory

ISBN: (数字)9781728186214

ISBN: (纸本)9781728186221

the mechanism of running software on virtual machines partly ensures the security of Android system. However, with all kinds of malicious codes being developed, there has been a huge number of massive security incidents caused by malware on Android. Malware has various code patterns, but their behaviors are measurable. In this paper, a new method of detecting Android malware by analyzing malware's behaviors is proposed. the method is characterized by the ability to mine the contextual relationships between system calls and network activities. Besides, the method requires only a small data set to achieve good classification performance. We propose a set of methods for automatically collecting and organizing dynamic features from Android application Based on the collected features, deep neural network is used to classify software samples. We validate the effectiveness of the proposed method on a set of 2210 applications obtained from Androzoo. the experimental results demonstrate that the proposed method has high detection accuracy against wild malware as compared with other methods. We propose a set of methods for automatically collecting and organizing dynamic features from Android application Based on the collected features, deep neural network is used to classify software samples. We validate the effectiveness of the proposed method on a set of 2210 applications obtained from Androzoo. the experimental results demonstrate that the proposed method has high detection accuracy against wild malware as compared with other methods.

关键词： Neural networks Alarm systems Feature extraction Malware data models data mining Smart phones

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proceedings of 2020 7th International conference on Networking, Systems and security, NSysS 2020

Proceedings of 2020 7th International Conference on Networki...

引用

7th International conference on Networking, Systems and security, NSysS 2020

ISBN: (纸本)9781450389051

the proceedings contain 15 papers. the topics discussed include: can COVID-19 change the Big5 personality traits of healthcare workers?;attacks on health workers during COVID-19 pandemic - data exploration and news article detection using NLP and GRU model;application of machine learning based hospital up-gradation policy for Bangladesh;a benchmark study on machine learning methods using several feature extraction techniques for news genre detection from Bangla news articles & titles;machine learning based malware detection on encrypted traffic: a comprehensive performance study;efficient feature selection for detecting botnets based on network traffic and behavior analysis;and solving the maze of diagnosing Parkinson’s disease based on portable EEG sensing to be adaptable to go in-the-wild.

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Study of security and privacy issues in internet of things 5

Study of security and privacy issues in internet of things

引用

5th IEEE International conference on Innovative Technologies in Intelligent Systems and Industrial applications, CITISIA 2020

作者： Khalid, Muhammad Hassam Murtaza, Mohsin Habbal, Mostafa Study Group Australia

ISBN: (纸本)9781728194370

With the advancement of technology and the internet, almost every device is connected to internet. Internet of things (IoT) can be explained as an extension of the internet in which smart devices are interconnected with each other. While each smart device has unique identifiers, which makes every device unique. Now, IoT has helped in developing smart architectures whether its home, healthcare, financial institutions or industries. there are smart devices everywhere. these smart devices can also communicate to each other in a network and they work together thus eliminating the need for human interaction. IoT is relatively new and is still developing rapidly. So, there are numerous privacy concerns in IoT. IoT can be divided into different architectural layers depending where the IoT is being used. the IoT model discussed in this research report is Service Oriented Architecture (SOA) which is divided into three layers, application, Network and perception layer. In 2020, during the COVID pandemic the reliability on IoT has increased as people are working from home and many of the tasks has been automated using IoT. the number of security attacks on IoT has also been increased in 2020 alone, which has affected many IoT devices. the objective of this research report is to discuss a number of security and privacy challenges in IoT based on the three SOA layers, the objective of this report also covers discussion on the above mentioned three layers, different technologies used in each layer for communication and different attacks and methods which target each specific layer also discussing different security attacks on IoT which occur ed in 2020 during the COVID pandemic phase. this topic is chosen because Internet of things is becoming important and is impacting everything around us. It is expected that the total number of IoT devices will cross 20 Billion in 2020 and will have an impact of more than $11 Trillion by 2025. thus, the security of IoT is to be discussed. © 20

关键词： Internet of things

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