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SKA-CaNPT: Secure Key Agreement using Cancelable and Noninvertible Biometrics based on Periodic Transformation 19

SKA-CaNPT: Secure Key Agreement using Cancelable and Noninve...

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

作者： Eskandarian, Laleh Akdogan, Dilara Karaoglan Altop, Duygu Levi, Albert Sabanci Univ Fac Engn & Nat Sci Istanbul Turkey

ISBN: (纸本)9781450360999

Nowadays, many of the security-providing applications use biometrics-based authentication. However, since each person's biometrics is unique and non-replaceable, once it is compromised, it will be compromised forever. therefore, it is hard for the users to trust biometrics. To overcome this problem, in this paper, we propose a novel secure key agreement protocol SKA-CaNPT. Here, we use a periodic transformation function to make biometrics cancelable and noninvertible. At the very end of our SKA-CaNPT protocol, the user and the server make an agreement on a symmetric shared key that is based on the feature points of the user's biometrics. therefore, if the transformed data is compromised, then just by changing one of the inputs of the transformation function, we can renew the cryptographic key. As a proof of concept, we apply our SKA-CaNPT protocol on fingerprints. Besides, we apply different security analyses on our protocol. We use Shannon's entropy and Hamming distance metrics to analyze the randomness and the distinctiveness of the agreed keys. Moreover, according to the low IKGR (Incorrect Key Generation Rate), high CKGR (Correct Key Generation Rate) and high attack complexity possessed by our SKA-CaNPT protocol, we can conclude that our scheme is secure against brute-force, replay and impersonation attacks.

关键词： Biometrics bio-cryptography cancelable biometrics noninvertible biometrics periodic transformation fingerprints key agreement security analysis

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Probabilistic Modeling and Simulation of Vehicular Cyber Attacks: An application of the Meta Attack Language 5th

Probabilistic Modeling and Simulation of Vehicular Cyber Att...

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5th International conference on Information Systems security and privacy (ICISSP)

作者： Katsikeas, Sotirios Johnson, Pontus Hacks, Simon Lagerstrom, Robert KTH Royal Inst Technol Dept Network & Syst Engn Stockholm Sweden Rhein Westfal TH Aachen Res Grp Software Construct Aachen Germany

ISBN: (纸本)9789897583599

Attack simulations are a feasible means to assess the cyber security of systems. the simulations trace the steps taken by an attacker to compromise sensitive system assets. Moreover, they allow to estimate the time conducted by the intruder from the initial step to the compromise of assets of interest. One commonly accepted approach for such simulations are attack graphs, which model the attack steps and their dependencies in a formal way. To reduce the effort of creating new attack graphs for each system of a given type, domain-specific attack languages may be employed. they codify common attack logics of the considered domain. Consequently, they ease the reuse of models and, thus, facilitate the modeling of a specific system in the domain. Previously, MAL (the Meta Attack Language) was proposed, which serves as a framework to develop domain specific attack languages. In this article, we present vehicleLang, a Domain Specific Language (DSL) which can be used to model vehicles with respect to their IT infrastructure and to analyze their weaknesses related to known attacks. To model domain specifics in our language, we rely on existing literature and verify the language using an interview with a domain expert from the automotive industry. To evaluate our results, we perform a Systematic Literature Review (SLR) to identify possible attacks against vehicles. those attacks serve as a blueprint for test cases checked against the vehicleLang specification.

关键词： Domain Specific Language Cyber security threat Modeling Attack Graphs Vehicular security

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Maia: A Language for Mandatory Integrity Controls of Structured data 5th

Maia: A Language for Mandatory Integrity Controls of Structu...

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5th International conference on Information Systems security and privacy (ICISSP)

作者： Al-Mawee, Wassnaa Bonamy, Paul J. Carr, Steve Mayo, Jean Western Michigan Univ Dept Comp Sci 1903 W Michigan Ave Kalamazoo MI 49008 USA Washington State Univ Dept Comp Sci 14204 NE Salmon Creek Ave Vancouver WA 98686 USA Michigan Technol Univ Dept Comp Sci 1400 Townsend Dr Hougton MI 49931 USA

ISBN: (纸本)9789897583599

the integrity of systems files is necessary for the secure functioning of an operating system. Integrity is not generally discussed in terms of complete computer systems. Instead, integrity issues tend to be either tightly coupled to a particular domain (e.g. database constraints), or else so broad as to be useless except after the fact (e.g. backups). Often, file integrity is determined by who modifies the file or by a checksum. this paper focuses on a general model of the internal integrity of a file. Even if a file is modified by a subject with trust or has a valid checksum, it may not meet the specification of a valid file. An example would be a password file with no user assigned a user id of 0. In this paper, we describe a language called Maia that provides a means to specify what the contents of a valid file should be. Maia can be used to specify the format and valid properties of system configuration files, PNG files and others. We give a structural operational semantics of Maia and discuss an initial implementation within a mandatory integrity system.

关键词： security Structured data Integrity Structural Operational Semantics

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State of the Sandbox: Investigating macOS application security 18

State of the Sandbox: Investigating macOS Application Securi...

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2019 Workshop on privacy in the Electronic Society

作者： Blochberger, Maximilian Rieck, Jakob Burkert, Christian Mueller, Tobias Federrath, Hannes Univ Hamburg Hamburg Germany

ISBN: (纸本)9781450368308

Sandboxing is a way to deliberately restrict applications accessing resources that they do not need to function properly. Sandboxing is intended to limit the effect of potential exploits and to mitigate overreach to personal data. Since June 1, 2012, sandboxing is a mandatory requirement for apps distributed through the Mac App Store (MAS). In addition, Apple has made it easier for developers to specify sandbox entitlements - capabilities that allow the app to access certain resources. However, sandboxing is still optional for macOS apps distributed outside Apple's official app store. this paper provides two contributions. First, the sandbox mechanism of macOS is analyzed and a critical sandbox-bypass is identified. Second, the general adoption of the sandbox mechanism, as well as app-specific sandbox configurations are evaluated. For that purpose all 8366 free apps of the MAS, making 25 % of all apps available on the MAS, as well as 4672 apps retrieved from MacUpdate (MU), a third-party app store, were analyzed dynamically. the dataset is over eight times larger than the second biggest study of macOS apps. It is shown that more than 94 % of apps on the MAS are sandboxed. However, more than 89 % of apps distributed through MU do not make use of sandboxing, putting users' data at risk.

关键词： sandboxing capabilities entitlements macOS

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Research On 3d Interactive Model Selection And Customization Of ceramic Products Based On Big data Cloud Service Platform 5

Research On 3d Interactive Model Selection And Customization...

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5th IEEE Int Conf on Big data security on Cloud (Bigdatasecurity) / 5th IEEE Int Conf on High Performance and Smart Computing (IEEE HPSC) / 4th IEEE Int Conf on Intelligent data and security (IEEE IDS)

作者： Hu, Kaihua Hua, Huang Zhang, Yujing Jingdezhen Ceram Inst Sch Informat Engn Jingdezhen Peoples R China Jingdezhen Ceram Inst Coll Technol & Art Sch Informat Engn Jingdezhen Peoples R China

ISBN: (纸本)9781728100067

In the new economic era led by big data, enterprises face many consumers with various product requirements. It is important for enterprises to timely meet these personalized product needs to improve their market competitiveness. In this paper, to show how to satisfy users' personalized product customization needs through the Internet and big data technologies, a ceramic product online interactive design system based on bigdata cloud service platform is implemented by adopting Web3D technology and storing a mass of various 3d digital models of ceramic products designed beforehand in the cloud server for designing users' personalized ceramic products. the procedure of online designing a ceramic product using this system includes choosing ceramic product 3d model in cloud server and calling the cloud decoration pattern resources or independent online design decorative pattern. In order to protect the intellectual property rights of users' design works, the platform provides privacy protection mechanism for users' personal information and works' information by setting three kinds of design works' sharing modes: free sharing, non-sharing and paid sharing. With the growth of 3d model data of ceramic products, the platform can also provide online 3d displaying services of ceramic product. the real application of this system demonstrate it can efficiently satisfy users' personalized product customization needs without disclose users' privacy information.

关键词： Big data Web3D Product interactive design privacy protection

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Practical security and privacy threat Analysis in the Automotive Domain: Long Term Support Scenario for Over-the-Air Updates 5

Practical Security and Privacy Threat Analysis in the Automo...

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5th International conference on Vehicle Technology and Intelligent Transport Systems (VEHITS)

作者： Vasenev, Alexandr Stahl, Florian Hamazaryan, Hayk Ma, Zhendong Shan, Lijun Kemmerich, Joerg Loiseaux, Claire ESI TNO Eindhoven Netherlands AVL Software & Funct Regensburg Germany ZF Friedrichshafen AG Friedrichshafen Germany AVL Graz Austria Internet Trust Paris France

ISBN: (纸本)9789897583742

Keeping a vehicle secure implies provide of a long-term support, where over-the-air updates (OTA) play an essential role. Clear understanding of OTA threats is essential to counter them efficiently. Existing research on OTA threats often exclude human actors, such as drivers and maintenance personnel, as well as leave aside privacy threats. this paper addresses the gap by investigates security and privacy OTA threats relevant for vehicle manufacturers for the whole product lifecycle. We report on a practical scenario "long term support", its data flow elements, and outcomes of threat analyses. We apply state of the art approaches, such as STRIDE (extended with an automotive template) and LINDDUN, to an automotive case and consider an automotive-specific UNECE OTA threat catalogue. Outcomes indicate complementarity of these methods and provide inputs to studies how well they address practical automotive cases.

关键词： data Flow Diagram STRIDE Taxonomy LINDDUN Methodology UNECE threat Catalogue Risk Management

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APDPk-means: A new differential privacy clustering algorithm based on arithmetic progression privacy budget allocation 21

APDPk-means: A new differential privacy clustering algorithm...

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21st IEEE International conference on High Performance Computing and Communications, 17th IEEE International conference on Smart City and 5th IEEE International conference on data Science and Systems, HPCC/SmartCity/DSS 2019

作者： Fan, Zexuan Xu, Xiaolong Jiangsu Key Laboratory of Big Data Security AND Intelligent Processing Nanjing University of Posts and Telecommunications Nanjing China School of Computer Science Nanjing University of Posts and Telecommunications Nanjing China

ISBN: (纸本)9781728120584

How to protect users' private data during network data mining has become a hot issue in the fields of big data and network information security. Most current researches on differential privacy k-means clustering algorithms focus on optimizing the selection of initial centroids. However, the traditional privacy budget allocation has the problem that the random noise becomes too large as the number of iterations increases, which will reduce the performance of data clustering. To solve the problem, we improved the way of privacy budget allocation in differentially private clustering algorithm DPk-means, and proposed APDPk-means, a new differential privacy clustering algorithm based on arithmetic progression privacy budget allocation. APDPk-means decomposes the total privacy budget into a decreasing arithmetic progression, allocating the privacy budgets from large to small in the iterative process, so as to ensure the rapid convergence in early iteration. the experiment results show that compared with the other differentially private k-means algorithms, APDPk-means has better performance in availability and quality of the clustering result under the same level of privacy protection. © 2019 IEEE.

关键词： data mining

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A study on Blockchain enabled applications and its security Issues 5

A study on Blockchain enabled Applications and its Security ...

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IEEE 5th International conference for Convergence in Technology (I2CT)

作者： Pai, Nilima D. Mondal, Shaheen NMIMS Mukesh Patel Sch Technol Management & Engn Mumbai Maharashtra India

ISBN: (纸本)9781538680759

Blockchain technology was first established because of its use in cryptocurrencies, but its applications are not limited just to this field. We have explored other fields like Finance, Auditing, Digital identity, Digital Voting and Healthcare where blockchain can be used to increase efficiency, and how it fares compared to the traditional systems. the paper compares the traditional and blockchain enabled systems based on parameters like privacy, data and application security, consensus algorithms and mining computations. However, like any other technology, this one too might have flaws which can be exploited. this paper also lists the security challenges that need to be kept in mind while implementing these systems.

关键词： security blockchain shared ledger key management consensus cryptocurrency bitcoin healthcare finance auditing identity digital voting comparison

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Zero-sum Distinguishers for Round-reduced GIMLI Permutation 5th

Zero-sum Distinguishers for Round-reduced GIMLI Permutation

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5th International conference on Information Systems security and privacy (ICISSP)

作者： Cai, Jiahao Wei, Zihao Zhang, Yingjie Sun, Siwei Hu, Lei Chinese Acad Sci Inst Informat Engn State Key Lab Informat Secur Beijing Peoples R China Chinese Acad Sci Data Assurance & Commun Secur Res Ctr Beijing Peoples R China Univ Chinese Acad Sci Sch Cyber Secur Beijing Peoples R China

ISBN: (纸本)9789897583599

GIMLI is a 384-bit permutation proposed by Bernstein et al. at CHES 2017. It is designed with the goal of achieving both high security and high performance across a wide range of hardware and software platforms. Since GIMLI can be used as a building block for many cryptographic schemes, it is important to understand its concrete security. To the best of our knowledge, third party cryptanalysis of GIMLI is limited. In this paper, we identify some zero-sum distinguishers for 14-round GIMLI with the inside-out technique, which are one-round longer than the integral distinguishers presented by the designers. Although we obtain improved cryptanalysis results, these zero-sum distinguishers are far from threatening the full version of GIMLI.

关键词： GIMLI Integral Division Property Zero-sum Degree evaluation MILP

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SecHadoop: A privacy preserving hadoop 19

SecHadoop: A privacy preserving hadoop

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12th IEEE/acm International conference on Utility and Cloud Computing, UCC 2019

作者： Shyamasundar, Rudrapatna K. Satheesan, Swatish Mittal, Deepali Chaudhary, Aakash Department of Computer Science and Engineering Indian Institute of Technology Bombay Mumbai Maharashtra400076 India

ISBN: (纸本)9781450368940

With the generation of vast amounts of data, there has been a tremendous need for processing the same in an economical way. MapReduce paradigm provides an economical processing of huge datasets in an effective way. Hadoop is a framework for managing huge amounts of data, and facilitates parallel computations on data using commodity hardware, through an integration of MapReduce paradigm with the HDFS file system. Due to intrinsic data divisions during parallel processing, there is a possibility of data leaks. thus, in the context of Hadoop, if processing has to keep the privacy invariant over the computation, it is necessary to guarantee privacy not only of the MapReduce process but also assure that the HDFS file system does leak any information. the focus of our work is on data security and privacy in such cloud environments. Our main thrust is to preserve data confidentiality and privacy as per specifications notwithstanding data divisions or scheduling for fault tolerance. We realise privacy invariance on Hadoop by monitoring the information flow from subjects to objects created in Hadoop using the readers writers flow model (RWFM). In this paper, we describe the design, implementation and performance of a security enhanced Hadoop, called SecHadoop. We illustrate our approach with various case studies corresponding to infection of map/reduce tasks, failure of nodes etc., and demonstrate how end-to-end security of programs is realised. It is further shown that the overall overhead is less than 5% on single/multi-node setup. © 2019 Association for Computing Machinery.

关键词： MapReduce

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