Jianping He, Bin Liu, Deguang Kong, Xuan Bao, Na Wang, Hongxia Jin, G. Kesidis
Sharing photos through Online Social Networks is an increasingly popular fashion. However, it poses a seriousthreat to end users as private information in the photos maybe inappropriately shared with others without their consent. This paper proposes a design and implementation of a system using a dynamic privacy preserving partial image sharing technique (namely PUPPIES), which allows data owners to stipulate specific private regions (e.g., face, SSN number) in an image and correspondingly set different privacy policies for each user. As a generic technique and system, PUPPIES targets at threats about over-privileged and unauthorized sharing of photos at photo service provider (e.g., Flicker, Facebook, etc) side. To this end, PUPPIES leverages the image perturbation technique to "encrypt" the sensitive areas in the original images, and therefore it can naturally support popular image transformations (such as cropping, rotation) and is well compatible with most image processing libraries. The extensive experiments on 19,000 images demonstrate that PUPPIES is very effective for privacy protection and incurs only a small computational overhead. In addition, PUPPIES offers high flexibility for different privacy settings, and is very robust to different types of privacy attacks.
{"title":"PUPPIES: Transformation-Supported Personalized Privacy Preserving Partial Image Sharing","authors":"Jianping He, Bin Liu, Deguang Kong, Xuan Bao, Na Wang, Hongxia Jin, G. Kesidis","doi":"10.1109/DSN.2016.40","DOIUrl":"https://doi.org/10.1109/DSN.2016.40","url":null,"abstract":"Sharing photos through Online Social Networks is an increasingly popular fashion. However, it poses a seriousthreat to end users as private information in the photos maybe inappropriately shared with others without their consent. This paper proposes a design and implementation of a system using a dynamic privacy preserving partial image sharing technique (namely PUPPIES), which allows data owners to stipulate specific private regions (e.g., face, SSN number) in an image and correspondingly set different privacy policies for each user. As a generic technique and system, PUPPIES targets at threats about over-privileged and unauthorized sharing of photos at photo service provider (e.g., Flicker, Facebook, etc) side. To this end, PUPPIES leverages the image perturbation technique to \"encrypt\" the sensitive areas in the original images, and therefore it can naturally support popular image transformations (such as cropping, rotation) and is well compatible with most image processing libraries. The extensive experiments on 19,000 images demonstrate that PUPPIES is very effective for privacy protection and incurs only a small computational overhead. In addition, PUPPIES offers high flexibility for different privacy settings, and is very robust to different types of privacy attacks.","PeriodicalId":102292,"journal":{"name":"2016 46th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129081281","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Salman Yousaf, U. Iqbal, Shehroze Farooqi, Raza Ahmad, M. Shafiq, Fareed Zaffar
Auto-surf and manual-surf traffic exchanges are an increasingly popular way of artificially generating website traffic. Previous research in this area has focused on the makeup, usage, and monetization of underground traffic exchanges. In this paper, we analyze the role of traffic exchanges as a vector for malware propagation. We conduct a measurement study of nine auto-surf and manual-surf traffic exchanges over several months. We present a first of its kind analysis of the different types of malware that are propagated through these traffic exchanges. We find that more than 26% of the URLs surfed on traffic exchanges contain malicious content. We further analyze different categories of malware encountered on traffic exchanges, including blacklisted domains, malicious JavaScript, malicious Flash, and malicious shortened URLs.
{"title":"Malware Slums: Measurement and Analysis of Malware on Traffic Exchanges","authors":"Salman Yousaf, U. Iqbal, Shehroze Farooqi, Raza Ahmad, M. Shafiq, Fareed Zaffar","doi":"10.1109/DSN.2016.58","DOIUrl":"https://doi.org/10.1109/DSN.2016.58","url":null,"abstract":"Auto-surf and manual-surf traffic exchanges are an increasingly popular way of artificially generating website traffic. Previous research in this area has focused on the makeup, usage, and monetization of underground traffic exchanges. In this paper, we analyze the role of traffic exchanges as a vector for malware propagation. We conduct a measurement study of nine auto-surf and manual-surf traffic exchanges over several months. We present a first of its kind analysis of the different types of malware that are propagated through these traffic exchanges. We find that more than 26% of the URLs surfed on traffic exchanges contain malicious content. We further analyze different categories of malware encountered on traffic exchanges, including blacklisted domains, malicious JavaScript, malicious Flash, and malicious shortened URLs.","PeriodicalId":102292,"journal":{"name":"2016 46th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128432736","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Privacy is an important aspect of network communications, but privacy protocols require an investment of network resources. For any such protocol to be of use, we need to understand quantitatively how much privacy to expect, as well as the tradeoff between privacy and other network properties, for any given configuration of networks and parameters. We develop a practical privacy measure and protocol model for multichannel secret sharing protocols which integrates privacy and measurable network properties, deriving optimality results for the overall privacy and performance of these protocols. After proving these results, we evaluate the effectiveness of our model by providing a reference implementation and comparing its behavior to the optimality results derived from the model. In our benchmarks, the behavior of this proof-of-concept protocol matched that which is predicted by our model, furthermore, our results demonstrate the feasibility of implementing secret sharing protocols which transmit at a rate within 3-4% of optimal. This model and its results allow us to understand quantitatively the tradeoffs between privacy and network performance in secret-sharing based protocols.
{"title":"Modeling Privacy and Tradeoffs in Multichannel Secret Sharing Protocols","authors":"Devin J. Pohly, P. Mcdaniel","doi":"10.1109/DSN.2016.41","DOIUrl":"https://doi.org/10.1109/DSN.2016.41","url":null,"abstract":"Privacy is an important aspect of network communications, but privacy protocols require an investment of network resources. For any such protocol to be of use, we need to understand quantitatively how much privacy to expect, as well as the tradeoff between privacy and other network properties, for any given configuration of networks and parameters. We develop a practical privacy measure and protocol model for multichannel secret sharing protocols which integrates privacy and measurable network properties, deriving optimality results for the overall privacy and performance of these protocols. After proving these results, we evaluate the effectiveness of our model by providing a reference implementation and comparing its behavior to the optimality results derived from the model. In our benchmarks, the behavior of this proof-of-concept protocol matched that which is predicted by our model, furthermore, our results demonstrate the feasibility of implementing secret sharing protocols which transmit at a rate within 3-4% of optimal. This model and its results allow us to understand quantitatively the tradeoffs between privacy and network performance in secret-sharing based protocols.","PeriodicalId":102292,"journal":{"name":"2016 46th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN)","volume":"95 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128326184","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Kshiteej S. Mahajan, Rishabh Poddar, Mohan Dhawan, V. Mann
Software-defined networks (SDNs) only logically centralize the control plane. In reality, SDN controllers are distributed entities, which may exhibit different behavior on event triggers. We identify several classes of faults that afflict an SDN controller cluster and demonstrate them on two enterprise SDN controllers, ONOS and OpenDaylight. We present JURY, a system to validate controller activities in a clustered SDN deployment, involving topological and forwarding state, without imposing any restrictions on the controller behavior. Our evaluation shows that JURY requires minimal changes to the SDN controllers for deployment, and is capable of validating controller actions in near real time with low performance overheads.
{"title":"JURY: Validating Controller Actions in Software-Defined Networks","authors":"Kshiteej S. Mahajan, Rishabh Poddar, Mohan Dhawan, V. Mann","doi":"10.1109/DSN.2016.19","DOIUrl":"https://doi.org/10.1109/DSN.2016.19","url":null,"abstract":"Software-defined networks (SDNs) only logically centralize the control plane. In reality, SDN controllers are distributed entities, which may exhibit different behavior on event triggers. We identify several classes of faults that afflict an SDN controller cluster and demonstrate them on two enterprise SDN controllers, ONOS and OpenDaylight. We present JURY, a system to validate controller activities in a clustered SDN deployment, involving topological and forwarding state, without imposing any restrictions on the controller behavior. Our evaluation shows that JURY requires minimal changes to the SDN controllers for deployment, and is capable of validating controller actions in near real time with low performance overheads.","PeriodicalId":102292,"journal":{"name":"2016 46th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133420125","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In recent years, the drive-by malware space has undergone significant consolidation. Today, the most common source of drive-by downloads are so-called exploit kits (EKs). This paper presents Kizzle, the first prevention technique specifically designed for finding exploit kits. Our analysis shows that while the JavaScript delivered by kits varies greatly, the unpacked code varies much less, due to the kits authors' code reuse between versions. Ironically, this well-regarded software engineering practice allows us to build a scalable and precise detector that is able to quickly respond to superficial but frequent changes in EKs. Kizzle is able to generate anti-virus signatures for detecting EKs, which compare favorably to manually created ones. Kizzle is highly responsive and can generate new signatures within hours. Our experiments show that Kizzle produces high-accuracy signatures. When evaluated over a four-week period, false-positive rates for Kizzle are under 0.03%, while the false-negative rates are under 5%.
{"title":"Kizzle: A Signature Compiler for Detecting Exploit Kits","authors":"Ben Stock, B. Livshits, B. Zorn","doi":"10.1109/DSN.2016.48","DOIUrl":"https://doi.org/10.1109/DSN.2016.48","url":null,"abstract":"In recent years, the drive-by malware space has undergone significant consolidation. Today, the most common source of drive-by downloads are so-called exploit kits (EKs). This paper presents Kizzle, the first prevention technique specifically designed for finding exploit kits. Our analysis shows that while the JavaScript delivered by kits varies greatly, the unpacked code varies much less, due to the kits authors' code reuse between versions. Ironically, this well-regarded software engineering practice allows us to build a scalable and precise detector that is able to quickly respond to superficial but frequent changes in EKs. Kizzle is able to generate anti-virus signatures for detecting EKs, which compare favorably to manually created ones. Kizzle is highly responsive and can generate new signatures within hours. Our experiments show that Kizzle produces high-accuracy signatures. When evaluated over a four-week period, false-positive rates for Kizzle are under 0.03%, while the false-negative rates are under 5%.","PeriodicalId":102292,"journal":{"name":"2016 46th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129123396","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
M. Winterrose, K. Carter, Neal Wagner, W. Streilein
In cyber security, achieving the desired balance between system security and system performance in dynamic threat environments is a long-standing open challenge for cyber defenders. Typically an increase in system security comes at the price of decreased system performance, and vice versa, easily resulting in systems that are misaligned to operator specified requirements for system security and performance as the threat environment evolves. We develop an online, reinforcement learning based methodology to automatically discover and maintain desired operating postures in security-performance space even as the threat environment changes. We demonstrate the utility of our approach and discover parameters enabling an agile response to a dynamic adversary in a simulated security game involving prototype cyber moving target defenses.
{"title":"Balancing Security and Performance for Agility in Dynamic Threat Environments","authors":"M. Winterrose, K. Carter, Neal Wagner, W. Streilein","doi":"10.1109/DSN.2016.61","DOIUrl":"https://doi.org/10.1109/DSN.2016.61","url":null,"abstract":"In cyber security, achieving the desired balance between system security and system performance in dynamic threat environments is a long-standing open challenge for cyber defenders. Typically an increase in system security comes at the price of decreased system performance, and vice versa, easily resulting in systems that are misaligned to operator specified requirements for system security and performance as the threat environment evolves. We develop an online, reinforcement learning based methodology to automatically discover and maintain desired operating postures in security-performance space even as the threat environment changes. We demonstrate the utility of our approach and discover parameters enabling an agile response to a dynamic adversary in a simulated security game involving prototype cyber moving target defenses.","PeriodicalId":102292,"journal":{"name":"2016 46th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132153100","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Long Hoang Le, Carlos Eduardo Benevides Bezerra, F. Pedone
State machine replication (SMR) is a well-known technique that guarantees strong consistency (i.e., linearizability) to online services. In SMR, client commands are executed in the same order on all server replicas: after executing each command, every replica reaches the same state. However, SMR lacks scalability: every replica executes all commands, so adding servers does not increase the maximum throughput. Scalable SMR (S-SMR) addresses this problem by partitioning the service state, allowing commands to execute only in some replicas, providing scalability while still ensuring linearizability. One problem is that ssmr quickly saturates when executing multi-partition commands, as partitions must communicate. Dynamic S-SMR (DS-SMR) solves this issue by repartitioning the state dynamically, based on the workload. Variables that are usually accessed together are moved to the same partition, which significantly improves scalability. We evaluate the performance of DS-SMR with a scalable social network application.
{"title":"Dynamic Scalable State Machine Replication","authors":"Long Hoang Le, Carlos Eduardo Benevides Bezerra, F. Pedone","doi":"10.1109/DSN.2016.11","DOIUrl":"https://doi.org/10.1109/DSN.2016.11","url":null,"abstract":"State machine replication (SMR) is a well-known technique that guarantees strong consistency (i.e., linearizability) to online services. In SMR, client commands are executed in the same order on all server replicas: after executing each command, every replica reaches the same state. However, SMR lacks scalability: every replica executes all commands, so adding servers does not increase the maximum throughput. Scalable SMR (S-SMR) addresses this problem by partitioning the service state, allowing commands to execute only in some replicas, providing scalability while still ensuring linearizability. One problem is that ssmr quickly saturates when executing multi-partition commands, as partitions must communicate. Dynamic S-SMR (DS-SMR) solves this issue by repartitioning the state dynamically, based on the workload. Variables that are usually accessed together are moved to the same partition, which significantly improves scalability. We evaluate the performance of DS-SMR with a scalable social network application.","PeriodicalId":102292,"journal":{"name":"2016 46th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129250059","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Kun Tang, Devesh Tiwari, Saurabh Gupta, Ping Huang, Q. Lu, C. Engelmann, Xubin He
Checkpoint and restart mechanisms have been widely used in large scientific simulation applications to make forward progress in case of failures. However, none of the prior works have considered the interaction of power-constraint with temperature, reliability, performance, and checkpointing interval. It is not clear how power-capping may affect optimal checkpointing interval. What are the involved reliability, performance, and energy trade-offs? In this paper, we develop a deep understanding about the interaction between power-capping and scientific applications using checkpoint/restart as resilience mechanism, and propose a new model for the optimal checkpointing interval (OCI) under power-capping. Our study reveals several interesting, and previously unknown, insights about how power-capping affects the reliability, energy consumption, performance.
{"title":"Power-Capping Aware Checkpointing: On the Interplay Among Power-Capping, Temperature, Reliability, Performance, and Energy","authors":"Kun Tang, Devesh Tiwari, Saurabh Gupta, Ping Huang, Q. Lu, C. Engelmann, Xubin He","doi":"10.1109/DSN.2016.36","DOIUrl":"https://doi.org/10.1109/DSN.2016.36","url":null,"abstract":"Checkpoint and restart mechanisms have been widely used in large scientific simulation applications to make forward progress in case of failures. However, none of the prior works have considered the interaction of power-constraint with temperature, reliability, performance, and checkpointing interval. It is not clear how power-capping may affect optimal checkpointing interval. What are the involved reliability, performance, and energy trade-offs? In this paper, we develop a deep understanding about the interaction between power-capping and scientific applications using checkpoint/restart as resilience mechanism, and propose a new model for the optimal checkpointing interval (OCI) under power-capping. Our study reveals several interesting, and previously unknown, insights about how power-capping affects the reliability, energy consumption, performance.","PeriodicalId":102292,"journal":{"name":"2016 46th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134350679","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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