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Representing cloud security and privacy policies and detecting potential problems 5

Representing cloud security and privacy policies and detecti...

引用

5th IEEE International conference on Big data Intelligence and Computing, dataCom 2019

作者： Opara, Anthony Song, Youngsang Cho, Seong-Je Chung, Lawrence University of Texas Dallas United States Dankook University Korea Republic of

ISBN: (纸本)9781728141176

Cloud computing involves multiple stakeholders, each with its own security, privacy and trust requirements, where policy enforcement is shared between the various stakeholders, in contrast to on-premise computing, where an organizations policies are enforced using internal resources. To effectively manage and integrate security requirements in the cloud, the provider and customer needs to negotiate and agree upon the applied security policies. However, there is no standard way of expressing cloud security policies in a vendor-agnostic manner. Cloud security and privacy policies are often stated in an informal and ad-hoc manner, which leads to policy conflicts, incompleteness, ambiguity and inconsistencies. In this paper, we present CERBERUS, a framework for representing cloud security and privacy policies and detecting potential problems in the policies. CERBERUS adopts an object-oriented approach and consists of an ontology and notation, policies, guidelines and rules, and a tool for capturing and detecting policy errors. Using CERBERUS, policies can be analyzed for potential problems, including policy conflicts, inconsistencies, ambiguities, and incompleteness. An application of CERBERUS shows that it indeed helps to discover policy errors, which otherwise would go undetected or in many cases would be detected a posteriori at runtime. © 2019 IEEE.

关键词： Cloud security

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MagneticSpy: Exploiting Magnetometer in Mobile Devices for Website and application Fingerprinting 18

MagneticSpy: Exploiting Magnetometer in Mobile Devices for W...

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2019 Workshop on privacy in the Electronic Society

作者： Matyunin, Nikolay Wang, Yujue Arul, Tolga Kullmann, Kristian Szefer, Jakub Katzenbeisser, Stefan Tech Univ Darmstadt Darmstadt Germany CYSEC Darmstadt Germany Yale Univ New Haven CT 06520 USA Univ Passau Chair Comp Engn Passau Germany

ISBN: (纸本)9781450368308

Recent studies have shown that aggregate CPU usage and power consumption traces on smartphones can leak information about applications running on the system or websites visited. In response, access to such data has been blocked for mobile applications starting from Android 8. In this work, we explore a new source of side-channel leakage for this class of attacks. Our method is based on the fact that electromagnetic activity caused by mobile processors leads to noticeable disturbances in magnetic sensor measurements on mobile devices, with the amplitude being proportional to the CPU workload. therefore, recorded sensor data can be analyzed to reveal information about ongoing activities. the attack works on a number of devices: we evaluated 80 models of modern smartphones and tablets and observed the reaction of the magnetometer to the CPU activity on 56 of them. On selected devices we were able to successfully identify which application has been opened (with up to 90% accuracy) or which web page has been loaded (up to 91% accuracy). the presented side channel poses a significant risk to end users' privacy, as the sensor data can be recorded from native apps or even from web pages without user permissions. Finally, we discuss possible countermeasures to prevent the presented information leakage.

关键词： information leakage smartphone sensors hardware side channels application fingerprinting website fingerprinting mobile security magnetometer

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Result-Based Detection of Insider threats to Relational databases 19

Result-Based Detection of Insider Threats to Relational Data...

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

作者： Sallam, Asmaa Bertino, Elisa Purdue Univ Dept Comp Sci W Lafayette IN 47906 USA

ISBN: (纸本)9781450360999

Insiders misuse of resources is a real threat to organizations. According to recent security reports, data has been the most vulnerable to attacks by insiders, especially data located in databases and corporate file servers. Although anomaly detection is an effective technique for flagging early signs of insider attacks, modern techniques for the detection of anomalies in database access are not able to detect several sophisticated data misuse scenarios such as attempts to track data updates and the aggregation of data by an insider that exceeds his/her need to perform job functions. In such scenarios, if the insider does not have prior knowledge of the distribution of the target data, many of his/her queries may extract no data or small amounts of data. therefore, monitoring the total size of data retrieved by each user and comparing it to normal levels will either result in low anomaly detection accuracy or long time to anomaly detection. In this paper, we propose anomaly detection techniques designed to detect data aggregation and attempts to track data updates. Our techniques infer the normal rates of tables references and tuples retrievals from past database access logs. User queries are then analyzed to detect queries that lead to exceeding the normal data access rates. We evaluated the proposed techniques on the query logs of a real database. the results of the evaluation indicate that when the system configuration parameters are adequately selected and sufficient data is available for training, our techniques have low false alarm generation rate and high anomaly detection accuracy.

关键词： Insider threats data Analytics for security Relational databases Anomaly Detection Temporal Attacks

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Dynamic Groups and Attribute-Based Access Control for Next-Generation Smart Cars 19

Dynamic Groups and Attribute-Based Access Control for Next-G...

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

作者： Gupta, Maanak Benson, James Patwa, Farhan Sandhu, Ravi Univ Texas San Antonio Dept Comp Sci Inst Cyber Secur Ctr Secur & Privacy Enhanced Cloud Comp San Antonio TX 78249 USA

ISBN: (纸本)9781450360999

Smart cars are among the essential components and major drivers of future cities and connected world. the interaction among connected entities in this vehicular internet of things (IoT) domain, which also involves smart traffic infrastructure, restaurant beacons, emergency vehicles, etc., offer several real-time applications and provide safer and pleasant driving experience to consumers. With more than 100 million lines of code and hundreds of sensors, these connected vehicles (CVs) expose a large attack surface, which can be remotely compromised and exploited by malicious attackers. security and privacy are big concerns that deter the adoption of smart cars, which if not properly addressed will have grave implications with risk to human life and limb. In this paper, we present a formalized dynamic groups and attribute-based access control (ABAC) model (referred as CV-ABAC(G)) for smart cars ecosystem, where the model not only considers system wide attributes-based security policies but also takes into account the individual user privacy preferences for allowing or denying service notifications, alerts and operations to on-board resources. Further, we introduce a novel notion of groups in vehicular IoT, which are dynamically assigned to moving entities like connected cars, based on their current GPS coordinates, speed or other attributes, to ensure relevance of location and time sensitive notification services, to provide administrative benefits to manage large numbers of entities, and to enable attributes inheritance for fine-grained authorization policies. We present proof of concept implementation of our model in AWS cloud platform demonstrating real-world uses cases along with performance metrics.

关键词： Access Control Smart Cars Connected Vehicles Internet of things Authorization Attribute-Based Access Control Amazon Web Services (AWS) Autonomous Cars security privacy Cloud Computing

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Risk and security practices: Experiences from the e-land project 30

Risk and security practices: Experiences from the e-land pro...

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30th European Safety and Reliability conference, ESREL 2020 and 15th Probabilistic Safety Assessment and Management conference, PSAM15 2020

作者： Esnoul, Coralie Olsen, Silje Arendt Gran, Bjørn Axel Gao, Xueli Jørgensen, Per-Arne Simensen, John Eidar Institute for Energy Technology Os Alle 5 Halden1777 Norway

ISBN: (纸本)9789811485930

the increasing availability of renewable energy sources and the high expectations from end-users regarding energy dependability has forced a re-thinking of how the full potential of energy supplies can be released. E-LAND is a European project which concept is to develop a service bus application enabling energy islands to optimize the management of energy production and consumption, which focuses on communities of end-users’ needs instead of addressing the system operators’ requirements. In this new organization of the energy market, the risk ownership on devices and energy costs are shared by the energy islands, the grid owner and the energy supplier. To support the energy islands in their new role, the E-LAND final product must not add risk in the management of energy. thereby, a risk assessment is performed to ensure that the concept, the solution, and the application to be delivered in E-LAND are safe, secure, and reliable. this paper describes the project risk management for the E-LAND project and gives examples of future potential users, best practices on how to access, communicate and manage project risks with multi-disciplinary and international partners. As the E-LAND solution needs to collect data from the users, this article also addresses the risk regarding privacy/security, how this particular risk is understood and communicated through mitigations to ensure that the final product is in agreement with the standards. © ESREL2020-PSAM15 *** by Research Publishing, Singapore.

关键词： Risk management

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Future security of Smart Speaker and IoT Smart Home Devices 5

Future Security of Smart Speaker and IoT Smart Home Devices

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5th International conference on Mobile and Secure Services (MobiSecServ)

作者： Godwin, Shawn Glendenning, Brett Gagneja, Kanwalinderjit Florida Polytech Univ Dept Comp Sci Lakeland FL 33805 USA

ISBN: (纸本)9781538677001

the main idea in this research paper is to break the security of Echo by Amazon. Initially, we learned about how the Echo functions, and what security measures Amazon has implemented through hands-on testing and research. We then apply what we have learned about the Echo in order to create an attack platform that can be used to obtain access to the trove of potential data that can be gathered with the Echo.

关键词： IoT security attacks privacy smart devices

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ShinyAnonymizer: A Tool for Anonymizing Health data 5

ShinyAnonymizer: A Tool for Anonymizing Health Data

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5th International conference on Information and Communication Technologies for Ageing Well and e-Health (ICT4AWE)

作者： Vardalachakis, Marios Kondylakis, Haridimos Koumakis, Lefteris Kouroubali, Angelina Katehakis, Dimitrios G. FORTH ICS Computat Biomed Lab Iraklion Crete Greece Technol Educ Inst Crete Dept Informat Engn Iraklion Greece FORTH ICS Ctr eHlth Applicat & Serv Iraklion Crete Greece

ISBN: (纸本)9789897583681

Processing and managing sensitive health data requires a high standard of security and privacy measures to ensure that all ethical and legal requirements are respected. data anonymization is one of the key technologies to this purpose. However, the plethora and the complexity of the available anonymization techniques make it difficult for a non-expert to select and apply the appropriate technique. In this paper, we report on Shiny database Anonymizer, a tool enabling the easy and flexible anonymization of available health data, providing access to state of the art anonymization techniques, incorporating also multiple data analysis visualization paradigms. In addition, a number of encryption and hashing techniques are presented.

关键词： Personal Health data security privacy data Anonymization

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Limitless HTTP in an HTTPS World: Inferring the Semantics of the HTTPS Protocol without Decryption 19

Limitless HTTP in an HTTPS World: Inferring the Semantics of...

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

作者： Anderson, Blake Chi, Andrew Dunlop, Scott McGrew, David Cisco San Jose CA 95134 USA Univ N Carolina Chapel Hill NC 27515 USA

ISBN: (纸本)9781450360999

We present new analytic techniques for inferring HTTP semantics from passive observations of HTTPS that can infer the value of important fields including the status-code, Content-Type, and Server, and the presence or absence of several additional HTTP header fields, e.g., Cookie and Referer. Our goals are to improve the understanding of the confidentiality limitations of HTTPS, and to explore benign uses of traffic analysis that could replace HTTPS interception and static private keys in some scenarios. We found that our techniques increase the efficacy of malware detection, but they do not enable more powerful website fingerprinting attacks against Tor. Our broader set of results raises concerns about the confidentiality goals of TLS relative to a user's expectation of privacy, warranting future research. We apply our methods to the semantics of both HTTP/1.1 and HTTP/2 on data collected from automated runs of Firefox 58.0, Chrome 63.0, and Tor Browser 7.0.11 in a lab setting, and from applications running in a malware sandbox. We obtain ground truth plaintext for a diverse set of applications from the malware sandbox by extracting the key material needed for decryption from RAM post-execution. We developed an iterative approach to simultaneously solve several multi-class (field values) and binary (field presence) classification problems, and we show that our inference algorithm achieves an unweighted F-1 score greater than 0.900 for most HTTP fields examined.

关键词： Transport Layer security Network Traffic Analysis Machine Learning Malware Detection Website Fingerprinting

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CCSW 2019 - proceedings of the 2019 acm SIGSAC conference on Cloud Computing security Workshop

CCSW 2019 - Proceedings of the 2019 ACM SIGSAC Conference on...

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10th acm SIGSAC conference on Cloud Computing security Workshop, CCSW 2019, co-located with the 26th acm conference on Computer and Communications security, CCS 2019

ISBN: (纸本)9781450368261

the proceedings contain 17 papers. the topics discussed include: verifiable computation using smart contracts;secure delegation of isogeny computations and cryptographic applications;ABSTRACT: cloud-based image classification service is not robust to affine transformation: a forgotten battlefield;MalPro: a learning-based malware propagation and containment modeling;PrivFL: practical privacy-preserving federated regressions on high-dimensional data over mobile networks;AppMine: behavioral analytics for web application vulnerability detection;efficient multi-party private set intersection against malicious adversaries;secure data exchange: a marketplace in the cloud;quantifying information leakage of deterministic encryption;and simple forward and backward private searchable symmetric encryption schemes with constant number of roundtrips.

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Sensing Danger: Exploiting Sensors to Build Covert Channels 5th

Sensing Danger: Exploiting Sensors to Build Covert Channels

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

作者： Ulz, thomas Feldbacher, Markus Pieber, thomas Steger, Christian Graz Univ Technol Inst Tech Informat Graz Austria

ISBN: (纸本)9789897583599

Recent incidents have shown that sensor-equipped devices can be used by adversaries to perform malicious activities, such as spying on end-users or for industrial espionage. In this paper, we present a novel attack scenario that uses unsecured embedded sensors to build covert channels that can be used to bypass security mechanisms and transfer information between isolated processes. We present covert channels that require read- and write-access for sensor registers as well as a covert channel that transfers data by just triggering sensor readings so that malicious behavior cannot be distinguished from normal sensor usage. For each presented covert channel we discuss the trade-off between data rate and the likelihood of being detected as well as potential countermeasures. the fastest covert channel we implemented achieves a data rate of 4844 bit/s while the stealthiest but slower covert channel cannot be distinguished from normal user behavior. To highlight the significance of these security issues, we used popular platforms, such as Linux and Android, to evaluate the presented covert channels. However, we do not make any assumption regarding the device's platform, and thus we believe that the presented exploits pose a significant security risk for any sensor-equipped device.

关键词： Sensor Exploit security Side-channel Covert Channel

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