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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341-350 订阅

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Differentially Private K-Means Clustering 16

Differentially Private K-Means Clustering

引用

6th acm conference on data and application security and privacy (CODASPY)

作者： Su, Dong Cao, Jianneng Li, Ninghui Bertino, Elisa Jin, Hongxia Purdue Univ W Lafayette IN 47907 USA Inst Infocomm Res Singapore Singapore Samsung Res Amer Mountain View CA USA

ISBN: (纸本)9781450339353

There are two broad approaches for differentially private data analysis. The interactive approach aims at developing customized differentially private algorithms for various data mining tasks. The non-interactive approach aims at developing differentially private algorithms that can output a synopsis of the input dataset, which can then be used to support various data mining tasks. In this paper we study the effectiveness of the two approaches on differentially private k-means clustering. We develop techniques to analyze the empirical error behaviors of the existing interactive and non-interactive approaches. Based on the analysis, we propose an improvement of DPLloyd which is a differentially private version of the Lloyd algorithm. We also propose a non-interactive approach EUGkM which publishes a differentially private synopsis for k-means clustering. Results from extensive and systematic experiments support our analysis and demonstrate the effectiveness of our improvement on DPLloyd and the proposed EUGkM algorithm.

关键词： Differential privacy k-means clustering Private data publishing

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Hacking the DBMS to Prevent Injection Attacks 16

Hacking the DBMS to Prevent Injection Attacks

引用

6th acm conference on data and application security and privacy (CODASPY)

作者： Medeiros, Iberia Beatriz, Miguel Neves, Nuno Correia, Miguel Univ Lisbon Fac Ciencias INESC ID Lisbon Portugal Univ Lisbon Inst Super Tecn INESC ID Lisbon Portugal Univ Lisbon Fac Ciencias LaSIGE Lisbon Portugal

ISBN: (纸本)9781450339353

After more than a decade of research, web application security continues to be a challenge and the backend database the most appetizing target. The paper proposes preventing injection attacks against the database management system (DBMS) behind web applications by embedding protections in the DBMS itself. The motivation is twofold. First, the approach of embedding protections in operating systems and applications running on top of them has been effective to protect these applications. Second, there is a semantic mismatch between how SQL queries are believed to be executed by the DBMS and how they are actually executed, leading to subtle vulnerabilities in protection mechanisms. The approach SEPTIC was implemented in MySQL and evaluated experimentally with web applications written in PHP and Java/Spring. In the evaluation SEPTIC has shown neither false negatives nor false positives, on the contrary of alternative approaches, causing also a low performance overhead in the order of 2.2%.

关键词： web applications injection attacks DBMS self-protection security software security

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Neuralyzer: Flexible Expiration Times for the Revocation of Online data 16

Neuralyzer: Flexible Expiration Times for the Revocation of ...

引用

6th acm conference on data and application security and privacy (CODASPY)

作者： Zarras, Apostolis Kohls, Katharina Duermuth, Markus Poepper, Christina Tech Univ Munich D-80290 Munich Germany Ruhr Univ Bochum Bochum Germany NYU Abu Dhabi New York NY USA

ISBN: (纸本)9781450339353

Once data is released to the Internet, there is little hope to successfully delete it, as it may have been duplicated, reposted, and archived in multiple places. This poses a significant threat to users' privacy and their right to permanently erase their very own data. One approach to control the implications on privacy is to assign a lifetime value to the published data and ensure that the data is no longer accessible after this point in time. However, such an approach suffers from the inability to successfully predict the right time when the data should vanish. Consequently, the author of the data can only estimate the correct time, which unfortunately can cause the premature or belated deletion of data. This paper tackles the problem of prefixed lifetimes in data deletion from a different angle and argues that alternative approaches are a desideratum for research. In our approach, we consider different criteria when data should be deleted, such as keeping data available as long as there is sufficient interest for it or untimely delete it in cases of excessive accesses. To assist the self-destruction of data, we propose a protocol and develop a prototype, called Neuralyzer, which leverages the caching mechanisms of the Domain Name System (DNS) to ensure the successful deletion of data. Our experimental results demonstrate that our approach can completely delete published data while at the same time achieving flexible expiration times varying from few days to several months depending on the users' interest.

关键词： encryption revocation systems flexible expiration times

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SPICE: A Software Tool for Bridging the Gap Between End-user's Insecure Cyber Behavior and Personality Traits 16

SPICE: A Software Tool for Bridging the Gap Between End-user...

引用

6th acm conference on data and application security and privacy (CODASPY)

作者： Tamrakar, Anjila Russell, Justin D. Ahmed, Irfan Richard, Golden G., III Weems, Carl F. Univ New Orleans 2000 Lakeshore Dr New Orleans LA 70122 USA Iowa State Univ Ames IA 50011 USA

ISBN: (纸本)9781450339353

End users are prone to insecure cyber behavior that may lead them to compromise the integrity, availability or confidentiality of their computer systems. For instance, replying to a phishing email may compromise an end user's login credentials. Identifying tendency toward insecure cyber behavior is critically important to improve cyber security posture and thesis of this paper is that the susceptibility of end-users to be a victim of a cyber-attack may be predicted using personality traits such as trait anxiety and callousness. This paper presents an easily configurable, script-based software tool to explore the relationships between the personality traits and insecure cyber behaviors of end users. The software utilizes well-established cognitive methods (such as dot probe) to identify a number of personality traits for a user and further allows researchers to design and conduct experiments through customizable scripting to study the end users' insecure cyber behaviors. The software also collects fine-grained data on users for analysis.

关键词： Software Psychology Personality traits computer security Human factor Test-bed

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Auditing security Compliance of the Virtualized Infrastructure in the Cloud: application to OpenStack 16

Auditing Security Compliance of the Virtualized Infrastructu...

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6th acm conference on data and application security and privacy (CODASPY)

作者： Madi, Taous Majumdar, Suryadipta Wang, Yushun Jarraya, Yosr Pourzandi, Makan Wang, Lingyu Concordia Univ CIISE Montreal PQ Canada Ericsson Canada Ericsson Secur Res Montreal PQ Canada

ISBN: (纸本)9781450339353

Cloud service providers typically adopt the multi-tenancy model to optimize resources usage and achieve the promised cost-effectiveness. Sharing resources between different tenants and the underlying complex technology increase the necessity of transparency and accountability. In this regard, auditing security compliance of the provider's infrastructure against standards, regulations and customers' policies takes on an increasing importance in the cloud to boost the trust between the stakeholders. However, virtualization and scalability make compliance verification challenging. In this work, we propose an automated framework that allows auditing the cloud infrastructure from the structural point of view while focusing on virtualization-related security properties and consistency between multiple control layers. Furthermore, to show the feasibility of our approach, we integrate our auditing system into OpenStack, one of the most used cloud infrastructure management systems. To show the scalability and validity of our framework, we present our experimental results on assessing several properties related to auditing inter-layer consistency, virtual machines co-residence, and virtual resources isolation.

关键词： Cloud Virtualization OpenStack security Auditing Formal Verification Co-residence Isolation

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Patching Logic Vulnerabilities for Web applications using LogicPatcher 16

Patching Logic Vulnerabilities for Web Applications using Lo...

引用

6th acm conference on data and application security and privacy (CODASPY)

作者： Monshizadeh, Maliheh Naldurg, Prasad Venkatakrishnan, V. N. Univ Illinois Dept Comp Sci Chicago IL 60607 USA IBM Res India Bangalore Karnataka India

ISBN: (纸本)9781450339353

Logic vulnerabilities are an important class of programming flaws in web applications. These vulnerabilities occur when a desired property pertaining to an application's logic does not hold along certain paths in the application's code. Many analysis tools have been developed to find logic vulnerabilities in web applications. Given a web application with logic vulnerabilities, the question is whether one can design methods to patch application code and prevent these vulnerabilities from being exploited. We answer this question by developing an approach and tool called LOGICPATCHER for patching of logic vulnerabilities. We focus on correct patch placement, i.e. identifying the precise location in code where the patch code can be introduced, based on path profiling. As we show in this paper, finding the appropriate location as well as generating the right patch can get complicated and require deep code analysis. We demonstrate the utility of LOGICPATCHER by automatically fixing several critical parameter tampering and authorization vulnerabilities in large web applications.

关键词： static program analysis logic vulnerabilities patch generation web security

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R-Droid: Leveraging Android App Analysis with Static Slice Optimization 16

R-Droid: Leveraging Android App Analysis with Static Slice O...

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11th acm Asia conference on Computer and Communications security (ASIA CCS)

作者： Backes, Michael Bugiel, Sven Derr, Erik Gerling, Sebastian Hammer, Christian Univ Saarland CISPA D-66123 Saarbrucken Germany MPI SWS Kaiserslautern Germany

ISBN: (纸本)9781450342339

Today's feature-rich smartphone apps intensively rely on access to highly sensitive (personal) data. This puts the user's privacy at risk of being violated by overly curious apps or libraries (like advertisements). Central app markets conceptually represent a first line of defense against such invasions of the user's privacy, but unfortunately we are still lacking full support for automatic analysis of apps' internal data flows and supporting analysts in statically assessing apps' behavior. In this paper we present a novel slice-optimization approach to leverage static analysis of Android applications. Building on top of precise application lifecycle models, we employ a slicing-based analysis to generate data-dependent statements for arbitrary points of interest in an application. As a result of our optimization, the produced slices are, on average, 49% smaller than standard slices, thus facilitating code understanding and result validation by security analysts. Moreover, by re-targeting strings, our approach enables automatic assessments for a larger number of use-cases than prior work. We consolidate our improvements on statically analyzing Android apps into a tool called R-DROID and conducted a large-scale data-leak analysis on a set of 22,700 Android apps from Google Play. R-DROID managed to identify a significantly larger set of potential privacy-violating information flows than previous work, including 2,157 sensitive flows of password-flagged UI widgets in 256 distinct apps.

关键词： constant propagation android string analysis mobile security app analysis slice optimization

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Novel Feature Extraction, Selection and Fusion for Effective Malware Family Classification 16

Novel Feature Extraction, Selection and Fusion for Effective...

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6th acm conference on data and application security and privacy (CODASPY)

作者： Ahmadi, Mansour Ulyanov, Dmitry Semenov, Stanislav Trofimov, Mikhail Giacinto, Giorgio Univ Cagliari Dept Elect & Elect Engn I-09124 Cagliari Italy Skolkovo Inst Sci & Technol Moskovsky Russia Natl Res Univ Higher Sch Econ Moscow Russia Moscow Inst Phys & Technol Dolgoprudnyi Moskovskaya Obl Russia

ISBN: (纸本)9781450339353

Modern malware is designed with mutation characteristics, namely polymorphism and metamorphism, which causes an enormous growth in the number of variants of malware samples. Categorization of malware samples on the basis of their behaviors is essential for the computer security community, because they receive huge number of malware everyday, and the signature extraction process is usually based on malicious parts characterizing malware families. Microsoft released a malware classification challenge in 2015 with a huge dataset of near 0.5 terabytes of data, containing more than 20K malware samples. The analysis of this dataset inspired the development of a novel paradigm that is effective in categorizing malware variants into their actual family groups. This paradigm is presented and discussed in the present paper, where emphasis has been given to the phases related to the extraction, and selection of a set of novel features for the effective representation of malware samples. Features can be grouped according to different characteristics of malware behavior, and their fusion is performed according to a per-class weighting paradigm. The proposed method achieved a very high accuracy (approximate to 0.998) on the Microsoft Malware Challenge dataset.

关键词： Windows Malware Machine learning Malware family Computer security Classification Microsoft Malware Classification Challenge

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To Fear or Not to Fear That is the Question: Code Characteristics of a Vulnerable Function with an Existing Exploit 16

To Fear or Not to Fear That is the Question: Code Characteri...

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6th acm conference on data and application security and privacy (CODASPY)

作者： Younis, Awad Malaiya, Yashwant K. Anderson, Charles Ray, Indrajit Colorado State Univ Dept Comp Sci Ft Collins CO 80523 USA

ISBN: (纸本)9781450339353

Not all vulnerabilities are equal. Some recent studies have shown that only a small fraction of vulnerabilities that have been reported has actually been exploited. Since finding and addressing potential vulnerabilities in a program can take considerable time and effort, recently effort has been made to identify code that is more likely to be vulnerable. This paper tries to identify the attributes of the code containing a vulnerability that makes the code more likely to be exploited. We examine 183 vulnerabilities from the National Vulnerability database for Linux Kernel and Apache HTTP server. These include eighty-two vulnerabilities that have been found to have an exploit according to the Exploit database. We characterize the vulnerable functions that have no exploit and the ones that have an exploit using eight metrics. The results show that the difference between a vulnerability that has no exploit and the one that has an exploit can potentially be characterized using the chosen software metrics. However, predicting exploitation of vulnerabilities is more complex than predicting just the presence of vulnerabilities and further research is needed using metrics that consider security domain knowledge for enhancing the predictability of vulnerability exploits.

关键词： Vulnerabilities Severity Exploitability Software security Exploits data mining and machine learning Feature selection Prediction Software metrics

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Program-object Level data Flow Analysis with applications to data Leakage and Contamination Forensics 16

Program-object Level Data Flow Analysis with Applications to...

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6th acm conference on data and application security and privacy (CODASPY)

作者： Xiao, Gaoyao Wang, Jun Liu, Peng Ming, Jiang Wu, Dinghao Penn State Univ Coll Informat Sci & Technol University Pk PA 16802 USA

ISBN: (纸本)9781450339353

We introduce a novel data Flow Analysis (DFA) technique, called PoL-DFA (Program-object Level data Flow Analysis), to analyze the dynamic data flows of server programs. PoL-DFA symbolically analyzes every instruction in the execution trace of a process to keep track of the data flows among program objects (e.g., integers, structures, arrays), and concatenates these pieces of data flows to obtain the overall data flow graph of the execution. We leverage PoL-DFA to identify malicious data flows in data leakage and contamination forensics. In two mocked digital forensic scenarios, for data leakage and contamination respectively, we tested the ability of PoL-DFA to identify data flows among multiple inputs and outputs of server programs. Our results show that PoL-DFA can accurately determine whether the data (or the processed results) from a source file or socket flow to a certain output channel. Based on this information, security administrators can pinpoint the path of data leakage or data contamination. Different from existing dynamic DFA techniques that require excessive amount of instrumentation, PoL-DFA only requires logging the execution traces of the processes being monitored. The measured performance overhead for server programs is 4.24%, on average. The results indicate PoL-DFA is a lightweight DFA solution for data leakage and contamination forensics.

关键词： information accountability information flow control usage control

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