Daiping Liu, Xing Gao, Mingwei Zhang, Haining Wang, A. Stavrou
As the most commonly used bots in first-person shooter (FPS) online games, aimbots are notoriously difficult to detect because they are completely passive and resemble excellent honest players in many aspects. In this paper, we conduct the first field measurement study to understand the status quo of aimbots and how they play in the wild. For data collection purpose, we devise a novel and generic technique called baittarget to accurately capture existing aimbots from the two most popular FPS games. Our measurement reveals that cheaters who use aimbots cannot play as skillful as excellent honest players in all aspects even though aimbots can help them to achieve very high shooting performance. To characterize the unskillful and blatant nature of cheaters, we identify seven features, of which six are novel, and these features cannot be easily mimicked by aimbots. Leveraging this set of features, we propose an accurate and robust server-side aimbot detector called AimDetect. The core of AimDetect is a cascaded classifier that detects the inconsistency between performance and skillfulness of aimbots. We evaluate the efficacy and generality of AimDetect using the real game traces. Our results show that AimDetect can capture almost all of the aimbots with very few false positives and minor overhead.
{"title":"Detecting Passive Cheats in Online Games via Performance-Skillfulness Inconsistency","authors":"Daiping Liu, Xing Gao, Mingwei Zhang, Haining Wang, A. Stavrou","doi":"10.1109/DSN.2017.20","DOIUrl":"https://doi.org/10.1109/DSN.2017.20","url":null,"abstract":"As the most commonly used bots in first-person shooter (FPS) online games, aimbots are notoriously difficult to detect because they are completely passive and resemble excellent honest players in many aspects. In this paper, we conduct the first field measurement study to understand the status quo of aimbots and how they play in the wild. For data collection purpose, we devise a novel and generic technique called baittarget to accurately capture existing aimbots from the two most popular FPS games. Our measurement reveals that cheaters who use aimbots cannot play as skillful as excellent honest players in all aspects even though aimbots can help them to achieve very high shooting performance. To characterize the unskillful and blatant nature of cheaters, we identify seven features, of which six are novel, and these features cannot be easily mimicked by aimbots. Leveraging this set of features, we propose an accurate and robust server-side aimbot detector called AimDetect. The core of AimDetect is a cascaded classifier that detects the inconsistency between performance and skillfulness of aimbots. We evaluate the efficacy and generality of AimDetect using the real game traces. Our results show that AimDetect can capture almost all of the aimbots with very few false positives and minor overhead.","PeriodicalId":426928,"journal":{"name":"2017 47th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130562407","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}
Hardware failures have a big impact on the dependability of large-scale data centers. We present studies on over 290,000 hardware failure reports collected over the past four years from dozens of data centers with hundreds of thousands of servers. We examine the dataset statistically to discover failure characteristics along the temporal, spatial, product line and component dimensions. We specifically focus on the correlations among different failures, including batch and repeating failures, as well as the human operators' response to the failures. We reconfirm or extend findings from previous studies. We also find many new failure and recovery patterns that are the undesirable by-product of the state-of-the-art data center hardware and software design.
{"title":"What Can We Learn from Four Years of Data Center Hardware Failures?","authors":"Guosai Wang, Lifei Zhang, W. Xu","doi":"10.1109/DSN.2017.26","DOIUrl":"https://doi.org/10.1109/DSN.2017.26","url":null,"abstract":"Hardware failures have a big impact on the dependability of large-scale data centers. We present studies on over 290,000 hardware failure reports collected over the past four years from dozens of data centers with hundreds of thousands of servers. We examine the dataset statistically to discover failure characteristics along the temporal, spatial, product line and component dimensions. We specifically focus on the correlations among different failures, including batch and repeating failures, as well as the human operators' response to the failures. We reconfirm or extend findings from previous studies. We also find many new failure and recovery patterns that are the undesirable by-product of the state-of-the-art data center hardware and software design.","PeriodicalId":426928,"journal":{"name":"2017 47th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116540689","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}
Third-party IME (Input Method Editor) apps are often the preference means of interaction for Android users' input. In this paper, we first discuss the insecurity of IME apps, including the Potentially Harmful Apps (PHA) and malicious IME apps, which may leak users' sensitive keystrokes. The current defense system, such as I-BOX, is vulnerable to the prefix-substitution attack and the colluding attack due to the post-IME nature. We provide a deeper understanding that all the designs with the post-IME nature are subject to the prefix-substitution and colluding attacks. To remedy the above post-IME system's flaws, we propose a new idea, pre-IME, which guarantees that "Is this touch event a sensitive keystroke?" analysis will always access user touch events prior to the execution of any IME app code. We designed an innovative TrustZone-based framework named IM-Visor which has the pre-IME nature. Specifically, IM-Visor creates the isolation environment named STIE as soon as a user intends to type on a soft keyboard, then the STIE intercepts, translates and analyzes the user's touch input. If the input is sensitive, the translation of keystrokes will be delivered to user apps through a trusted path. Otherwise, IM-Visor replays non-sensitive keystroke touch events for IME apps or replays non-keystroke touch events for other apps. A prototype of IM-Visor has been implemented and tested with several most popular IMEs. The experimental results show that IM-Visor has small runtime overheads.
{"title":"IM-Visor: A Pre-IME Guard to Prevent IME Apps from Stealing Sensitive Keystrokes Using TrustZone","authors":"Chen Tian, Yazhe Wang, Peng Liu, Qihui Zhou, Cheng Zhang, Zhen Xu","doi":"10.1109/DSN.2017.12","DOIUrl":"https://doi.org/10.1109/DSN.2017.12","url":null,"abstract":"Third-party IME (Input Method Editor) apps are often the preference means of interaction for Android users' input. In this paper, we first discuss the insecurity of IME apps, including the Potentially Harmful Apps (PHA) and malicious IME apps, which may leak users' sensitive keystrokes. The current defense system, such as I-BOX, is vulnerable to the prefix-substitution attack and the colluding attack due to the post-IME nature. We provide a deeper understanding that all the designs with the post-IME nature are subject to the prefix-substitution and colluding attacks. To remedy the above post-IME system's flaws, we propose a new idea, pre-IME, which guarantees that \"Is this touch event a sensitive keystroke?\" analysis will always access user touch events prior to the execution of any IME app code. We designed an innovative TrustZone-based framework named IM-Visor which has the pre-IME nature. Specifically, IM-Visor creates the isolation environment named STIE as soon as a user intends to type on a soft keyboard, then the STIE intercepts, translates and analyzes the user's touch input. If the input is sensitive, the translation of keystrokes will be delivered to user apps through a trusted path. Otherwise, IM-Visor replays non-sensitive keystroke touch events for IME apps or replays non-keystroke touch events for other apps. A prototype of IM-Visor has been implemented and tested with several most popular IMEs. The experimental results show that IM-Visor has small runtime overheads.","PeriodicalId":426928,"journal":{"name":"2017 47th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127992629","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}
An emerging solution to privacy issues in smart grids is battery-based load hiding (BLH) that uses a rechargeable battery to decouple the meter readings from user activities. However, existing BLH algorithms have two significant limitations: (1) Most of them focus on flattening high-frequency variation of usage profile only, thereby still revealing a low-frequency shape, (2) Otherwise, they assume to know a statistical model of usage pattern. To overcome these limitations, we propose a new BLH algorithm, named RL-BLH. The RL-BLH hides both low-frequency and high-frequency usage patterns by shaping the meter readings to rectangular pulses. The RL-BLH learns a decision policy for choosing pulse magnitudes on the fly without prior knowledge of usage pattern. The decision policy is designed to charge and discharge the battery in the optimal way to maximize cost savings. We also provide heuristics to shorten learning time and improve cost savings.
{"title":"RL-BLH: Learning-Based Battery Control for Cost Savings and Privacy Preservation for Smart Meters","authors":"Jinkyu Koo, Xiaojun Lin, S. Bagchi","doi":"10.1109/DSN.2017.16","DOIUrl":"https://doi.org/10.1109/DSN.2017.16","url":null,"abstract":"An emerging solution to privacy issues in smart grids is battery-based load hiding (BLH) that uses a rechargeable battery to decouple the meter readings from user activities. However, existing BLH algorithms have two significant limitations: (1) Most of them focus on flattening high-frequency variation of usage profile only, thereby still revealing a low-frequency shape, (2) Otherwise, they assume to know a statistical model of usage pattern. To overcome these limitations, we propose a new BLH algorithm, named RL-BLH. The RL-BLH hides both low-frequency and high-frequency usage patterns by shaping the meter readings to rectangular pulses. The RL-BLH learns a decision policy for choosing pulse magnitudes on the fly without prior knowledge of usage pattern. The decision policy is designed to charge and discharge the battery in the optimal way to maximize cost savings. We also provide heuristics to shorten learning time and improve cost savings.","PeriodicalId":426928,"journal":{"name":"2017 47th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130174480","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}
V. Krishna, Michael J. Rausch, Benjamin E. Ujcich, Indranil Gupta, W. Sanders
Wireless sensor networks (WSNs) should collect accurate readings to reliably capture an environment's state. However, readings may become erroneous because of sensor hardware failures or degradation. In remote deployments, centrally detecting those reading errors can result in many message transmissions, which in turn dramatically decreases sensor battery life. In this paper, we address this issue through three main contributions. First, we propose REMAX, a peer-to-peer (P2P) error detection protocol that extends the WSN's life by minimizing message transmissions. Second, we propose a low-overhead error detection approach that helps minimize communication complexity. Third, we evaluate our approach via a trace-driven, discrete-event simulator, using two datasets from real WSN deployments that measure indoor air temperature and seismic wave amplitude. Our results show that REMAX can accurately detect errors and extend the WSN's reachability (effective lifetime) compared to the centralized approach.
{"title":"REMAX: Reachability-Maximizing P2P Detection of Erroneous Readings in Wireless Sensor Networks","authors":"V. Krishna, Michael J. Rausch, Benjamin E. Ujcich, Indranil Gupta, W. Sanders","doi":"10.1109/DSN.2017.52","DOIUrl":"https://doi.org/10.1109/DSN.2017.52","url":null,"abstract":"Wireless sensor networks (WSNs) should collect accurate readings to reliably capture an environment's state. However, readings may become erroneous because of sensor hardware failures or degradation. In remote deployments, centrally detecting those reading errors can result in many message transmissions, which in turn dramatically decreases sensor battery life. In this paper, we address this issue through three main contributions. First, we propose REMAX, a peer-to-peer (P2P) error detection protocol that extends the WSN's life by minimizing message transmissions. Second, we propose a low-overhead error detection approach that helps minimize communication complexity. Third, we evaluate our approach via a trace-driven, discrete-event simulator, using two datasets from real WSN deployments that measure indoor air temperature and seismic wave amplitude. Our results show that REMAX can accurately detect errors and extend the WSN's reachability (effective lifetime) compared to the centralized approach.","PeriodicalId":426928,"journal":{"name":"2017 47th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124212486","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}
Guido Lena Cota, Sonia Ben Mokhtar, G. Gianini, E. Damiani, J. Lawall, Gilles Muller, L. Brunie
Selfishness is one of the key problems that confronts developers of cooperative distributed systems (e.g., file-sharing networks, voluntary computing). It has the potential to severely degrade system performance and to lead to instability and failures. Current techniques for understanding the impact of selfish behaviours and designing effective countermeasures remain manual and time-consuming, requiring multi-domain expertise. To overcome these difficulties, we propose SEINE, a simulation framework for rapid modelling and evaluation of selfish behaviours in a cooperative system. SEINE relies on a domain-specific language (SEINE-L) for specifying selfishness scenarios, and provides semi-automatic support for their implementation and study in a state-of-the-art simulator. We show in this paper that (1) SEINE-L is expressive enough to specify fifteen selfishness scenarios taken from the literature, (2) SEINE is accurate in predicting the impact of selfishness compared to real experiments, and (3) SEINE substantially reduces the development effort compared to traditional manual approaches.
{"title":"Analysing Selfishness Flooding with SEINE","authors":"Guido Lena Cota, Sonia Ben Mokhtar, G. Gianini, E. Damiani, J. Lawall, Gilles Muller, L. Brunie","doi":"10.1109/DSN.2017.51","DOIUrl":"https://doi.org/10.1109/DSN.2017.51","url":null,"abstract":"Selfishness is one of the key problems that confronts developers of cooperative distributed systems (e.g., file-sharing networks, voluntary computing). It has the potential to severely degrade system performance and to lead to instability and failures. Current techniques for understanding the impact of selfish behaviours and designing effective countermeasures remain manual and time-consuming, requiring multi-domain expertise. To overcome these difficulties, we propose SEINE, a simulation framework for rapid modelling and evaluation of selfish behaviours in a cooperative system. SEINE relies on a domain-specific language (SEINE-L) for specifying selfishness scenarios, and provides semi-automatic support for their implementation and study in a state-of-the-art simulator. We show in this paper that (1) SEINE-L is expressive enough to specify fifteen selfishness scenarios taken from the literature, (2) SEINE is accurate in predicting the impact of selfishness compared to real experiments, and (3) SEINE substantially reduces the development effort compared to traditional manual approaches.","PeriodicalId":426928,"journal":{"name":"2017 47th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114688735","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}
Ping Chen, Jun Xu, Zhi-hao Hu, Xinyu Xing, Minghui Zhu, Bing Mao, Peng Liu
Address space randomization has long been used for counteracting code reuse attacks, ranging from conventional ROP to sophisticated Just-in-Time ROP. At the high level, it shuffles program code in memory and thus prevents malicious ROP payload from performing arbitrary operations. While effective in mitigating attacks, existing randomization mechanisms are impractical for real-world applications and systems, especially considering the significant performance overhead and potential program corruption incurred by their implementation. In this paper, we introduce CHAMELEON, a practical defense mechanism that hinders code reuse attacks, particularly Just-in-Time ROP attacks. Technically speaking, CHAMELEON instruments program code, randomly shuffles code page addresses and minimizes the attack surface exposed to adversaries. While this defense mechanism follows in the footprints of address space randomization, our design principle focuses on using randomization to obstruct code page disclosure, making the ensuing attacks infeasible. We implemented a prototype of CHAMELEON on Linux operating system and extensively experimented it in different settings. Our theoretical and empirical evaluation indicates the effectiveness and efficiency of CHAMELEON in thwarting Just-in-Time ROP attacks.
{"title":"What You See is Not What You Get! Thwarting Just-in-Time ROP with Chameleon","authors":"Ping Chen, Jun Xu, Zhi-hao Hu, Xinyu Xing, Minghui Zhu, Bing Mao, Peng Liu","doi":"10.1109/DSN.2017.47","DOIUrl":"https://doi.org/10.1109/DSN.2017.47","url":null,"abstract":"Address space randomization has long been used for counteracting code reuse attacks, ranging from conventional ROP to sophisticated Just-in-Time ROP. At the high level, it shuffles program code in memory and thus prevents malicious ROP payload from performing arbitrary operations. While effective in mitigating attacks, existing randomization mechanisms are impractical for real-world applications and systems, especially considering the significant performance overhead and potential program corruption incurred by their implementation. In this paper, we introduce CHAMELEON, a practical defense mechanism that hinders code reuse attacks, particularly Just-in-Time ROP attacks. Technically speaking, CHAMELEON instruments program code, randomly shuffles code page addresses and minimizes the attack surface exposed to adversaries. While this defense mechanism follows in the footprints of address space randomization, our design principle focuses on using randomization to obstruct code page disclosure, making the ensuing attacks infeasible. We implemented a prototype of CHAMELEON on Linux operating system and extensively experimented it in different settings. Our theoretical and empirical evaluation indicates the effectiveness and efficiency of CHAMELEON in thwarting Just-in-Time ROP attacks.","PeriodicalId":426928,"journal":{"name":"2017 47th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133273985","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}
Web-borne malware continues to be a major threat on the Web. At the core of malware infection are for-crime toolkits that exploit vulnerabilities in browsers and their extensions. When a victim host gets infected, the infection dynamics is often buried in benign traffic, which makes the task of inferring malicious behavior a non-trivial exercise. In this paper, we leverage web conversation graph analytics to tap into the rich dynamics of the interaction between a victim and malicious host(s) without the need for analyzing exploit payload. Based on insights derived from infection graph analytics, we formulate the malware detection challenge as a graph-analytics based learning problem. The key insight of our approach is the payload-agnostic abstraction and comprehensive analytics of malware infection dynamics pre-, during-, and post-infection. Our technique leverages 3 years of infection intelligence spanning 9 popular exploit kit families. Our approach is implemented in a tool called DynaMiner and evaluated on infection and benign HTTP traffic. DynaMiner achieves a 97.3% true positive rate with false positive rate of 1.5%. Our forensic and live case studies suggest the effectiveness of comprehensive graph abstraction malware infection. In some instances, DynaMiner detected unknown malware 11 days earlier than existing AV engines.
{"title":"DynaMiner: Leveraging Offline Infection Analytics for On-the-Wire Malware Detection","authors":"Birhanu Eshete, V. Venkatakrishnan","doi":"10.1109/DSN.2017.54","DOIUrl":"https://doi.org/10.1109/DSN.2017.54","url":null,"abstract":"Web-borne malware continues to be a major threat on the Web. At the core of malware infection are for-crime toolkits that exploit vulnerabilities in browsers and their extensions. When a victim host gets infected, the infection dynamics is often buried in benign traffic, which makes the task of inferring malicious behavior a non-trivial exercise. In this paper, we leverage web conversation graph analytics to tap into the rich dynamics of the interaction between a victim and malicious host(s) without the need for analyzing exploit payload. Based on insights derived from infection graph analytics, we formulate the malware detection challenge as a graph-analytics based learning problem. The key insight of our approach is the payload-agnostic abstraction and comprehensive analytics of malware infection dynamics pre-, during-, and post-infection. Our technique leverages 3 years of infection intelligence spanning 9 popular exploit kit families. Our approach is implemented in a tool called DynaMiner and evaluated on infection and benign HTTP traffic. DynaMiner achieves a 97.3% true positive rate with false positive rate of 1.5%. Our forensic and live case studies suggest the effectiveness of comprehensive graph abstraction malware infection. In some instances, DynaMiner detected unknown malware 11 days earlier than existing AV engines.","PeriodicalId":426928,"journal":{"name":"2017 47th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114080667","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}
Domain Name System (DNS) is a fundamental element of the Internet providing lookup services for end users as well as for a multitude of applications, systems and security mechanisms that depend on DNS, such as antispam defences, routing security, firewalls, certificates and more. Caches constitute a critical component of DNS, allowing to improve efficiency and reduce latency and traffic in the Internet. Understanding the behaviour, configurations and topologies of caches in the DNS platforms in the Internet is important for efficiency and security of Internet users and services. In this work we present methodologies for efficiently discovering and enumerating the caches of the DNS resolution platforms in the Internet. We apply our techniques and methodologies for studying caches in popular DNS resolution platforms in the Internet. Our study includes networks of major ISPs, enterprises and professionally managed open DNS resolvers. The results of our Internet measurements shed light on architectures and configurations of the caches in DNS resolution platforms.
{"title":"Counting in the Dark: DNS Caches Discovery and Enumeration in the Internet","authors":"Amit Klein, Haya Schulmann, M. Waidner","doi":"10.1109/DSN.2017.63","DOIUrl":"https://doi.org/10.1109/DSN.2017.63","url":null,"abstract":"Domain Name System (DNS) is a fundamental element of the Internet providing lookup services for end users as well as for a multitude of applications, systems and security mechanisms that depend on DNS, such as antispam defences, routing security, firewalls, certificates and more. Caches constitute a critical component of DNS, allowing to improve efficiency and reduce latency and traffic in the Internet. Understanding the behaviour, configurations and topologies of caches in the DNS platforms in the Internet is important for efficiency and security of Internet users and services. In this work we present methodologies for efficiently discovering and enumerating the caches of the DNS resolution platforms in the Internet. We apply our techniques and methodologies for studying caches in popular DNS resolution platforms in the Internet. Our study includes networks of major ISPs, enterprises and professionally managed open DNS resolvers. The results of our Internet measurements shed light on architectures and configurations of the caches in DNS resolution platforms.","PeriodicalId":426928,"journal":{"name":"2017 47th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN)","volume":"164 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122852984","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}
Atomic multicast is a communication building block of scalable and highly available applications. With atomic multicast, messages can be ordered and reliably propagated to one or more groups of server processes. Because each message can be multicast to a different set of destinations, distributed message ordering is challenging. Some atomic multicast protocols address this challenge by ordering all messages using a fixed group of processes, regardless of the destination of the messages. To be efficient, however, an atomic multicast protocol must be genuine: only the message sender and destination groups should communicate to order a message. In this paper, we present FastCast, a genuine atomic multicast algorithm that offers unprecedented low time complexity, measured in communication delays. FastCast can order messages addressed to multiple groups in four communication delays, messages addressed to a single group take three communication delays. In addition to proposing a novel atomic multicast protocol, we extensively assess its performance experimentally.
{"title":"Fast Atomic Multicast","authors":"Paulo R. Coelho, Nicolas Schiper, F. Pedone","doi":"10.1109/DSN.2017.15","DOIUrl":"https://doi.org/10.1109/DSN.2017.15","url":null,"abstract":"Atomic multicast is a communication building block of scalable and highly available applications. With atomic multicast, messages can be ordered and reliably propagated to one or more groups of server processes. Because each message can be multicast to a different set of destinations, distributed message ordering is challenging. Some atomic multicast protocols address this challenge by ordering all messages using a fixed group of processes, regardless of the destination of the messages. To be efficient, however, an atomic multicast protocol must be genuine: only the message sender and destination groups should communicate to order a message. In this paper, we present FastCast, a genuine atomic multicast algorithm that offers unprecedented low time complexity, measured in communication delays. FastCast can order messages addressed to multiple groups in four communication delays, messages addressed to a single group take three communication delays. In addition to proposing a novel atomic multicast protocol, we extensively assess its performance experimentally.","PeriodicalId":426928,"journal":{"name":"2017 47th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121293055","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：