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

共 557 条记录，以下是311-320 订阅

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10th International Workshop on Artificial Intelligence and security (AISec 2017) 17

10th International Workshop on Artificial Intelligence and S...

引用

24th acm-SIGSAC conference on Computer and Communications security (acm CCS)

作者： Biggio, Battista Freeman, David Miller, Brad Sinha, Arunesh Univ Cagliari Cagliari Italy Facebook Inc Menlo Pk CA USA Google Inc Mountain View CA USA Univ Michigan Ann Arbor MI 48109 USA

ISBN: (纸本)9781450349468

Artificial Intelligence (AI) and Machine Learning (ML) provide a set of useful analytic and decision-making techniques that are being leveraged by an ever-growing community of practitioners, including many whose applications have security-sensitive elements. However, while security researchers often utilize such techniques to address problems and AI/ML researchers develop techniques for Big data analytics applications, neither community devotes much attention to the other. Within security research, AI/ML components are usually regarded as black-box solvers. Conversely, the learning community seldom considers the security/privacy implications entailed in the application of their algorithms when they are designing them. While these two communities generally focus on different directions, where these two fields do meet, interesting problems appear. Researchers working in this intersection have raised many novel questions for both communities and created a new branch of research known as secure learning. The AISec workshop has become the primary venue for this unique fusion of research.

关键词： Adversarial Learning Secure Learning Malware Detection

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Prioritized Analysis of Inter-App Communication Risks 17

Prioritized Analysis of Inter-App Communication Risks

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7th acm conference on data and application security and privacy (CODASPY)

作者： Liu, Fang Cai, Haipeng Wang, Gang Yao, Danfeng (Daphne) Elish, Karim O. Ryder, Barbara G. Virginia Tech Dept Comp Sci Blacksburg VA 24061 USA Washington State Univ Sch Elect Engn & Comp Sci Pullman WA 99164 USA Florida Polytech Univ Dept Comp Sci Lakeland FL USA

ISBN: (纸本)9781450345231

Inter-Component Communication (ICC) enables useful interactions between mobile apps. However, misuse of ICC exposes users to serious threats such as intent hijacking/spoofing and app collusions, allowing malicious apps to access privileged user data via another app. Unfortunately, existing ICC analyses are largely incompetent in both accuracy and scale. This poster points out the need and technical challenges of prioritized analysis of inter-app ICC risks. We propose MR-Droid, a MapReduce-based computing framework for accurate and scalable inter-app ICC analysis in Android. MR-Droid extracts data-flow features between multiple communicating apps and the target apps to build a large-scale ICC graph. Our approach is to leverage the ICC graph to provide contexts for inter-app communications to produce precise alerts and prioritize risk assessments. This process requires large app-pair data, which is enabled by our MapReduce-based program analysis. Our initial extensive experiments on 11,996 apps from 24 app categories (13 million pairs) demonstrate the scalability of our approach.

关键词： hijacking spoofing android security MapReduce ICC risk analysis

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The Human Capital Model for security Research New Insights into Technology Transition 17

The Human Capital Model for Security Research New Insights i...

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7th acm conference on data and application security and privacy (CODASPY)

作者： Rajagopalan, S. Raj Honeywell Phoenix AZ 85034 USA

ISBN: (纸本)9781450345231

As a security researcher, have you ever wondered how much of security research that is done and presented at research conferences is ever used by practitioners or is incorporated into products? Four years ago we formed a team with diverse backgrounds and embarked on a systematic study on the question of which technological solutions would security practitioners actually use if we built them. To carry this out program, we embedded our students who worked inside several security Operation Centers (SOCs) both in universities and corporations, to learn how security solutions get used in reality. Previous efforts at improving the efficiency of SOCs have emphasized building tools for analysts or understanding the human and organizational factors involved, but they have not significantly changed the status quo - solutions are built or bought but seldom used. This was because these efforts did not view these solutions from multiple contextual perspectives of the local participants, the analysts and their managers. After some initial failures, we realized that this kind of study is beyond the reach of conventional Computer Science approaches, so we worked with a Professor in Socio-cultural Anthropology to get a fresh look at the problem and get a new set of tools to use in our research. In our 4-year project we have used Anthropological fieldwork methods to study SOCs and in the process uncovered inherent contradictions between the multiple objectives a SOC has to meet as an organization and the conflicts between the goals of the human participants. This discovery was guided by Activity Theory, a theory proposed by the famous social scientist Y. Engestrom [1], which provides a framework for analyzing such kinds of fieldwork data. We discovered that successful SOC innovations must continually resolve the extant conflicts to be effective in improving operational efficiency. Our analysis provides evidence of the importance of conflict resolution as a prerequisite for operations

关键词： security SOC practitioners Anthropology Activity Theory field study

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A privacy assessment of social media aggregators 9

A privacy assessment of social media aggregators

引用

9th IEEE/acm International conference on Advances in Social Networks Analysis and Mining, ASONAM 2017

作者： Misra, Gaurav Such, Jose M. Gill, Lauren Security Lancaster Research Center Lancaster University Lancaster United Kingdom Department of Informatics King’s College London London United Kingdom School of Computing and Communications Lancaster University Lancaster United Kingdom

ISBN: (纸本)9781450349932

Social Media Aggregator (SMA) applications present a platform enabling users to manage multiple Social Networking Sites (SNS) in one convenient application, which results in a unique concentration of data from several SNS accounts in addition to the user’s mobile phone data available to them. In this paper, we provide a detailed privacy assessment of 13 popular SMAs from 3 app stores by using a three-step methodology by inspecting the mobile data and social media data accessed by these applications, checking for privacy policies and their compliance with distributors’ vetting policies and performing a qualitative assessment of traceability between privacy policies and the actual transparency and control mechanisms offered to users by the apps’ interfaces. Our results demonstrate a variation in data accessed by the individual applications, an absence of privacy policies for 5 of the SMAs evaluated, and a lack of traceability between privacy policies and transparency and control of interface operations. © 2017 Association for Computing Machinery.

关键词： Transparency

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UiRef: Analysis of Sensitive User Inputs in Android applications 17

UiRef: Analysis of Sensitive User Inputs in Android Applicat...

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10th acm conference on security and privacy in Wireless and Mobile Networks (WiSec)

作者： Andow, Benjamin Acharya, Akhil Li, Dengfeng Enck, William Singh, Kapil Xie, Tao North Carolina State Univ Raleigh NC 27695 USA Univ Illinois Champaign IL USA IBM TJ Watson Res Ctr Ossining NY USA

ISBN: (纸本)9781450350846

Mobile applications frequently request sensitive data. While prior work has focused on analyzing sensitive-data uses originating from well-defined API calls in the system, the security and privacy implications of inputs requested via application user interfaces have been widely unexplored. In this paper, our goal is to understand the broad implications of such requests in terms of the type of sensitive data being requested by applications. To this end, we propose UiRef (User Input REsolution Framework), an automated approach for resolving the semantics of user inputs requested by mobile applications. UiRef's design includes a number of novel techniques for extracting and resolving user interface labels and addressing ambiguity in semantics, resulting in significant improvements over prior work. We apply UiRef to 50,162 Android applications from Google Play and use outlier analysis to triage applications with questionable input requests. We identify concerning developer practices, including insecure exposure of account passwords and non-consensual input disclosures to third parties. These findings demonstrate the importance of user-input semantics when protecting end users.

关键词： Sensitive data

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Research Issues and Approaches for Connected and Automated Vehicles 17

Research Issues and Approaches for Connected and Automated V...

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7th acm conference on data and application security and privacy (CODASPY)

作者： Shin, Kang G. Univ Michigan Ann Arbor Ann Arbor MI 48109 USA

ISBN: (纸本)9781450345231

Driverless and/or environment-friendly cars have recently received a great deal of attention from media and almost all industry and government sectors due mainly to their great potential impacts on safety, economy, and environments. In particular, enabling vehicles to communicate with one another via wireless devices holds the potential to automate vehicles while dramatically improving safety, reducing congestion, and conserving energy. To move toward realization of this potential, we have been conducting research into various issues, including: Automation of vehicle sensing and control;Vehicle safety and passenger comfort;Securing information communication and computation;Developing environment-friendly solutions. In this talk, I will discuss various issues and approaches related to security of connected and automated vehicles.

关键词： Connected and/or automated cars security of in-vehicle networks intrusion detection

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Vulnerable Implicit Service: A Revisit 17

Vulnerable Implicit Service: A Revisit

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24th acm-SIGSAC conference on Computer and Communications security (acm CCS)

作者： Lei, Lingguang He, Yi Sun, Kun Jing, Jiwu Wang, Yuewu Li, Qi Weng, Jian Chinese Acad Sci Data Assurance & Commun Secur Res Ctr Beijing Peoples R China Chinese Acad Sci Inst Informat Engn State Key Lab Informat Secur Beijing Peoples R China George Mason Univ Fairfax VA 22030 USA Tsinghua Univ Grad Sch Shenzhen Dept Comp Sci Beijing Peoples R China Jinan Univ Guangzhou Guangdong Peoples R China

ISBN: (纸本)9781450349468

fThe services in Android applications can be invoked either explicitly or implicitly before Android 5.0. However, since the implicit service invocations suffer service hijacking attacks and thus lead to sensitive information leakage, they have been forbidden since Android 5.0. Thereafter since the Android system will simply throw an exception and crash the application that still invokes services implicitly, it was expected that application developers will be forced to convert the implicit service invocations to explicit ones by specifying the package name of the service to be called. In this paper, we revisit the service invocations by analyzing two sets of the same 1390 applications downloaded from Google Play Store before and after the the implicit service forbidden policy is enforced. We develop a static analysis framework called ISA to perform our study. Our analysis results show that the forbidden policy effectively reduces the number of vulnerable service invocations from 643 to 112, namely, 82.58% reduction. However, after a detailed analysis of the remaining 112 vulnerable invocations, we discover that the forbidden policy fails to resolve the service hijacking attacks. Among the 1390 applications downloaded in May 2017, we find 36 popular applications still vulnerable to service hijacking attacks, which can lead to the loss of user bank account and VPN login credentials, etc. Moreover, we find that the forbidden policy introduces a new type of denial of service attacks. Finally, we discuss the root challenges on resolving service hijacking attacks and propose countermeasures to help mitigate the service hijacking attacks.

关键词： Implicit Intent Service Hijacking Attacks Denial of Service Attacks

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Statistical security Incident Forensics against data Falsification in Smart Grid Advanced Metering Infrastructure 17

Statistical Security Incident Forensics against Data Falsifi...

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7th acm conference on data and application security and privacy (CODASPY)

作者： Bhattacharjee, Shameek Thakur, Aditya Silvestri, Simone Das, Sajal K. Missouri Univ Sci & Technol Dept Comp Sci Rolla MO 65409 USA Missouri Univ Sci & Technol Dept Elect Engn Rolla MO 65409 USA

ISBN: (纸本)9781450345231

Compromised smart meters reporting false power consumption data in Advanced Metering Infrastructure (AMI) may have drastic consequences on a smart grid's operations. Most existing works only deal with electricity theft from customers. However, several other types of data falsification attacks are possible, when meters are compromised by organized rivals. In this paper, we first propose a taxonomy of possible data falsification strategies such as additive, deductive, camouflage and conflict, in AMI micro-grids. Then, we devise a statistical anomaly detection technique to identify the incidence of proposed attack types, by studying their impact on the observed data. Subsequently, a trust model based on Kullback-Leibler divergence is proposed to identify compromised smart meters for additive and deductive attacks. The resultant detection rates and false alarms are minimized through a robust aggregate measure that is calculated based on the detected attack type and successfully discriminating legitimate changes from malicious ones. For conflict and camouflage attacks, a generalized linear model and Weibull function based kernel trick is used over the trust score to facilitate more accurate classification. Using real data sets collected from AMI, we investigate several trade-offs that occur between attacker's revenue and costs, as well as the margin of false data and fraction of compromised nodes. Experimental results show that our model has a high true positive detection rate, while the average false alarm rate is just 8%, for most practical attack strategies, without depending on the expensive hardware based monitoring.

关键词： Statistical Anomaly Detection security Incident Forensics Trust Models data Falsification Information Theory Supervised Learning Smart Grid Advanced Metering Infrastructure Relative Entropy

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Secure and privacy-Aware data Dissemination for Cloud-Based applications 17

Secure and Privacy-Aware Data Dissemination for Cloud-Based ...

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10th International conference on Utility and Cloud Computing (UCC) / 4th International conference on Big data Computing, applications and Technologies (BDCAT)

作者： Sampaio, Lilia Silva, Fabio Souza, Amanda Brito, Andrey Felber, Pascal Univ Fed Campina Grande Campina Grande Paraiba Brazil Univ Neuchatel Neuchatel Switzerland

ISBN: (纸本)9781450351492

In this paper we propose a data dissemination platform that supports data security and different privacy levels even when the platform and the data are hosted by untrusted infrastructures. The proposed system aims at enabling an application ecosystem that uses off-the-shelf trusted platforms (in this case, Intel SGX), so that users may allow or disallow third parties to access the live data stream with a specific sensitivity-level. Moreover, this approach does not require users to manage the encryption keys directly. Our experiments show that such an approach is indeed practical for medium scale systems, where participants disseminate small volumes of data at a time, such as in smart grids and IoT environments.

关键词： smart grids privacy Intel SGX publish/subscribe

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RT-SANE : Real Time security Aware Scheduling on the Network Edge 17

<i>RT</i>-<i>SANE</i> : Real Time Security Aware Scheduling ...

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10th International conference on Utility and Cloud Computing (UCC) / 4th International conference on Big data Computing, applications and Technologies (BDCAT)

作者： Singh, Anil Auluck, Nitin Rana, Omer Jones, Andrew Nepal, Surya Indian Inst Technol Dept Comp Sci & Engn Ropar India Cardiff Univ Sch Comp Sci & Informat Cardiff Wales CSIRO Distributed Syst Secur Grp Sydney NSW Australia

ISBN: (纸本)9781450351492

Edge computing extends a traditional cloud data centre model often by using a microdata centre (mdc) at the network edge for computation and storage. As these edge devices are in proximity to users, this results in improved application response times and reduces load on the cloud data center (cdc). In this paper, we propose a security and deadline aware scheduling algorithm called RT-SANE (Real-Time security Aware scheduling on the Network Edge). applications with stringent privacy requirements are scheduled on an mdc closer to the user, whereas others can be scheduled on a cdc or a remotemdc. We also discuss how application performance and network latency influence the choice of an mdc or cdc. The intuition is that due to a lower communication latency between the user & the mdc, more applications are able to meet their deadlines when run on themdc. Conversely, applications with loose deadlines may be executed on a cdc. In order to facilitate this, we also propose a distributed orchestration architecture and protocol that is both performance & security aware. Simulation results show that RT-SANE offers superior real-time performance compared to a number of other scheduling policies in an Edge computing environment, while meeting application privacy requirements.

关键词： Internet of Things IoT Fog Computing Edge Computing Cloud omputing Cloudlets Micro data Centers Cloud data Center Distributed Orchestration Real-Time security

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