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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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Building privacy-Preserving Cryptographic Credentials from Federated Online Identities 16

Building Privacy-Preserving Cryptographic Credentials from F...

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

作者： Maheswaran, John Jackowitz, Daniel Zhai, Ennan Wolinsky, David Isaac Ford, Bryan Yale Univ New Haven CT 06520 USA Ecole Polytech Fed Lausanne Swiss Fed Inst Technol Lausanne Switzerland

ISBN: (纸本)9781450339353

Federated identity providers, e.g., Facebook and PayPal, offer a convenient means for authenticating users to third-party applications. Unfortunately such cross-site authentications carry privacy and tracking risks. For example, federated identity providers can learn what applications users are accessing;meanwhile, the applications can know the users' identities in reality. This paper presents Crypto-Book, an anonymizing layer enabling federated identity authentications while preventing these risks. Crypto-Book uses a set of independently managed servers that employ a (t, n)-threshold cryptosystem to collectively assign credentials to each federated identity (in the form of either a public/private key-pair or blinded signed messages). With the credentials in hand, clients can then leverage anonymous authentication techniques such as linkable ring signatures or partially blind signatures to log into third-party applications in an anonymous yet accountable way. We have implemented a prototype of Crypto-Book and demonstrated its use with three applications: a Wiki system, an anonymous group communication system, and a whistleblower submission system. Crypto-Book is practical and has low overhead: in a deployment within our research group, Crypto-Book group authentication took 1.607s end-to-end, an overhead of 1.2s compared to traditional non-privacy-preserving federated authentication.

关键词： anonymity anonymous communication authentication online social networks

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On the Origin of Mobile Apps: Network Provenance for Android applications 16

On the Origin of Mobile Apps: Network Provenance for Android...

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

作者： Stevens, Ryan Crussell, Jonathan Chen, Hao Univ Calif Davis Davis CA 95616 USA ShanghaiTech Univ Shanghai Shi Peoples R China

ISBN: (纸本)9781450339353

Many mobile services consist of two components: a server providing an API, and an application running on smart phones and communicating with the API. An unresolved problem in this design is that it is difficult for the server to authenticate which app is accessing the API. This causes many security problems. For example, the provider of a private network API has to embed secrets in its official app to ensure that only this app can access the API;however, attackers can uncover the secret by reverse-engineering. As another example, malicious apps may send automatic requests to ad servers to commit ad fraud. In this work, we propose a system that allows network API to authenticate the mobile app that sends each request so that the API can make an informed access control decision. Our system, the Mobile Trusted-Origin Policy, consists of two parts: 1) an app provenance mechanism that annotates outgoing HTTP(S) requests with information about which app generated the network traffic, and 2) a code isolation mechanism that separates code within an app that should have different app provenance signatures into mobile origin. As motivation for our work, we present two previously-unknown families of apps that perform click fraud, and examine how the lack of mobile origin information enables the attacks. Based on our observations, we propose Trusted Cross-Origin Requests to handle point (1), which automatically includes mobile origin information in outgoing HTTP requests. Servers may then decide, based on the mobile origin data, whether to process the request or not. We implement a prototype of our system for Android and evaluate its performance, security, and deployability. We find that our system can achieve our security and utility goals with negligible overhead.

关键词： mobile security advertising security mobile advertising app authentication

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SMASheD: Sniffing and Manipulating Android Sensor data 16

SMASheD: Sniffing and Manipulating Android Sensor Data

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

作者： Mohamed, Manar Shrestha, Babins Saxena, Nitesh Univ Alabama Birmingham 1300 Univ Blvd Birmingham AL 35487 USA

ISBN: (纸本)9781450339353

The current Android sensor security model either allows only restrictive read access to sensitive sensors (e.g., an app can only read its own touch data) or requires special install-time permissions (e.g., to read microphone, camera or GPS). Moreover, Android does not allow write access to any of the sensors. Sensing-based security applications therefore crucially rely upon the sanity of the Android sensor security model. In this paper, we show that such a model can be effectively circumvented. Specifically, we build SMASheD, a legitimate framework under the current Android ecosystem that can be used to stealthily sniff as well as manipulate many of the Android's restricted sensors (even touch input). SMASheD exploits the Android Debug Bridge (ADB) functionality and enables a malicious app with only the INTERNET permission to read, and write to, multiple different sensor data files at will. SMASheD is the first framework, to our knowledge, that can sniff and manipulate protected sensors on unrooted Android devices, without user awareness, without constant device-PC connection and without the need to infect the PC. The primary contributions of this work are two-fold. First, we design and develop the SMASheD framework. Second, as an offensive implication of the SMASheD framework, we introduce a wide array of potentially devastating attacks. Our attacks against the touchsensor range from accurately logging the touchscreen input (TouchLogger) to injecting touch events for accessing restricted sensors and resources, installing and granting special permissions to other malicious apps, accessing user accounts, and authenticating on behalf of the user - essentially almost doing whatever the device user can do (secretively). Our attacks against various physical sensors (motion, position and environmental) can subvert the functionality provided by numerous existing sensing-based security applications, including those used for (continuous) authentication, and authorization.

关键词： sensors android

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Detecting Malicious Exploit Kits using Tree-based Similarity Searches 16

Detecting Malicious Exploit Kits using Tree-based Similarity...

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

作者： Taylor, Teryl Hu, Xin Wang, Ting Jang, Jiyong Stoecklin, Marc Ph. Monrose, Fabian Sailer, Reiner Univ North Carolina Chapel Hill Chapel Hill NC 27514 USA IBM TJ Watson Res Ctr Armonk NY 10504 USA Lehigh Univ Bethlehem PA USA

ISBN: (纸本)9781450339353

Unfortunately, the computers we use for everyday activities can be infiltrated while simply browsing innocuous sites that, unbeknownst to the website owner, may be laden with malicious advertisements. So-called malvertising, redirects browsers to web-based exploit kits that are designed to find vulnerabilities in the browser and subsequently download malicious payloads. We propose a new approach for detecting such malfeasance by leveraging the inherent structural patterns in HTTP traffic to classify exploit kit instances. Our key insight is that an exploit kit leads the browser to download payloads using multiple requests from malicious servers. We capture these interactions in a "tree-like" form, and using a scalable index of malware samples, model the detection process as a sub-tree similarity search problem. The approach is evaluated on 3800 hours of real-world traffic including over 4 billion flows and reduces false positive rates by four orders of magnitude over current state-of-the-art techniques with comparable true positive rates. We show that our approach can operate in near real-time, and is able to handle peak traffic levels on a large enterprise network-identifying 28 new exploit kit instances during our analysis period.

关键词： network security exploit kit subtree similarity search intrusion detection security information retrieval

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Context Matters?: How Adding the Obfuscation Option Affects End Users' data Disclosure Decisions 16

Context Matters?: How Adding the Obfuscation Option Affects ...

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21st International conference on Intelligent User Interfaces (IUI)

作者： Wang, Jing Wang, Na Jin, Hongxia Samsung Res Amer Mountain View CA 94043 USA

ISBN: (纸本)9781450341370

Recent advancement of smart devices and wearable technologies greatly enlarges the variety of personal data people can track. applications and services can leverage such data to provide better life support, but also impose privacy and security threats. Obfuscation schemes, consequently, have been developed to retain data access while mitigate risks. Compared to offering choices of releasing raw data and not releasing at all, we examine the effect of adding a data obfuscation option on users' disclosure decisions when configuring applications' access, and how that effect varies with data types and application contexts. Our online user experiment shows that users are less likely to block data access when the obfuscation option is available except for locations. This effect significantly differs between applications for domain-specific dynamic tracking data, but not for generic personal traits. We further unpack the role of context and discuss the design opportunities.

关键词： data obfuscation privacy tracking user behavior mobile

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Multi cloud iaas with domain trust in OpenStack 16

Multi cloud iaas with domain trust in OpenStack

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6th acm conference on data and application security and privacy, CODASPY 2016

作者： Pustchi, Navid Patwa, Farhan Sandhu, Ravi Institute for Cyber Security Dept. of Computer Science Univ. of Texas San Antonio United States Institute for Cyber Security Univ. of Texas San Antonio United States

ISBN: (纸本)9781450339353

As cloud services have been firmly accepted by enterprises, the current challenge is how to share these resources among increasing number of cloud platforms. Currently, cloud platforms such as OpenStack, the de facto open-source platform for cloud Infrastructure-as-a-Service (IaaS), offer limited cross-cloud access capabilities in their federation APIs. In this paper, we present a fine-grained cross-cloud domaintrust model enabling resource sharing between domains across distinct homogeneous clouds. We further present a formalized description of core multi-cloud OpenStack access control (MC-OSAC) with proposed domain trust extension. We have implemented a proof of concept with extending Open Stack identity and federation services to support cross-cloud domain trust. Our approach does not introduce any authorization overhead within current OpenStack federation model.

关键词： Authorization

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