Social network spam increases explosively with the rapid development and wide usage of various social networks on the Internet. To timely detect spam in large social network sites, it is desirable to discover unsupervised schemes that can save the training cost of supervised schemes. In this work, we first show several limitations of existing unsupervised detection schemes. The main reason behind the limitations is that existing schemes heavily rely on spamming patterns that are constantly changing to avoid detection. Motivated by our observations, we first propose a sybil defense based spam detection scheme SD2 that remarkably outperforms existing schemes by taking the social network relationship into consideration. In order to make it highly robust in facing an increased level of spam attacks, we further design an unsupervised spam detection scheme, called UNIK. Instead of detecting spammers directly, UNIK works by deliberately removing non-spammers from the network, leveraging both the social graph and the user-link graph. The underpinning of UNIK is that while spammers constantly change their patterns to evade detection, non-spammers do not have to do so and thus have a relatively non-volatile pattern. UNIK has comparable performance to SD2 when it is applied to a large social network site, and outperforms SD2 significantly when the level of spam attacks increases. Based on detection results of UNIK, we further analyze several identified spam campaigns in this social network site. The result shows that different spammer clusters demonstrate distinct characteristics, implying the volatility of spamming patterns and the ability of UNIK to automatically extract spam signatures.

Spam content is surging with an explosive increase of user generated content (UGC) on the Internet. Spammers often insert popular keywords or simply copy and paste recent articles from the Web with spam links inserted, attempting to disable content-based detection. In order to effectively detect spam in user generated content, we first conduct a comprehensive analysis of spamming activities on a large commercial UGC site in 325 days covering over 6 million posts and nearly 400 thousand users. Our analysis shows that UGC spammers exhibit unique non-textual patterns, such as posting activities, advertised spam link metrics, and spam hosting behaviors. Based on these non-textual features, we show via several classification methods that a high detection rate could be achieved offline. These results further motivate us to develop a runtime scheme, BARS, to detect spam posts based on these spamming patterns. The experimental results demonstrate the effectiveness and robustness of BARS.

BitTorrent (BT) has carried out a significant and continuously increasing portion of Internet traffic. While several designs have been recently proposed and implemented to improve the resource utilization by bridging the application layer (overlay) and the network layer (underlay), these designs are largely dependent on Internet infrastructures, such as ISPs and CDNs. In addition, they also demand large-scale deployments of their systems to work effectively. Consequently, they require multiefforts far beyond individual users' ability to be widely used in the Internet. In this paper, aiming at building an infrastructure-independent user-level facility, we present our design, implementation, and evaluation of a topology-aware BT system, called TopBT, to significantly improve the overall Internet resource utilization without degrading user downloading performance. The unique feature of TopBT client lies in that a TopBT client actively discovers network proximities (to connected peers), and uses both proximities and transmission rates to maintain fast downloading while reducing the transmitting distance of the BT traffic and thus the Internet traffic. As a result, a TopBT client neither requires feeds from major Internet infrastructures, such as ISPs or CDNs, nor requires large-scale deployment of other TopBT clients on the Internet to work effectively. We have implemented TopBT based on widely used open-source BT client code base, and made the software publicly available. By deploying TopBT and other BitTorrent clients on hundreds of Internet hosts, we show that on average TopBT can reduce about 25% download traffic while achieving a 15% faster download speed compared to several prevalent BT clients. TopBT has been widely used in the Internet by many users all over the world.

Millions of residential users are widely served by cable or DSL connections with modest upload bandwidth and relatively high download bandwidth. For the increasingly important and demanding P2P applications such as VoIP, BitTorrent, and Internet streaming, stable or high upload bandwidth is required. Inadequate upload bandwidth degrades the performance of these applications among residential users. On the other hand, our Internet measurements show that plenty of idle upload bandwidth (from 50% to 80%) is always available in a local residential network. Based on this observation, we propose a system prototype to Coordinate Upload Bandwidth Sharing (CUBS) among neighboring residential users. Specifically, the idle upload bandwidth of neighbors can be used upon a request from a demanding user. Since it has become a common practice to deploy wireless access points in a residential user's home, we have built CUBS by leveraging the support from the wireless networks. In CUBS, to discover and manage idle bandwidth, a localized overlay is constructed by the cooperative users. CUBS is application independent as the bandwidth sharing is implemented at the network layer. CUBS is also ISP transparent because the sharing of neighbors' bandwidth does not demand any additional bandwidth supplies. We have evaluated the CUBS system prototype with experiments on Internet. The experimental results demonstrate that CUBS can effectively improve the performance of upload intensive applications by more than 30%.

Various online social networks (OSNs) have been developed rapidly on the Internet. Researchers have analyzed different properties of such OSNs, mainly focusing on the formation and evolution of the networks as well as the information propagation over the networks. In knowledge-sharing OSNs, such as blogs and question answering systems, issues on how users participate in the network and how users "generate/contribute" knowledge are vital to the sustained and healthy growth of the networks. However, related discussions have not been reported in the research literature.

The commonly agreed Zipf-like access pattern of Web workloads is mainly based on Internet measurements when text-based content dominated the Web traffic. However, with dramatic increase of media traffic on the Internet, the inconsistency between the access patterns of media objects and the Zipf model has been observed in a number of studies. An insightful understanding of media access patterns is essential to guide Internet system design and management, including resource provisioning and performance optimizations.

The increasing number of wireless users in Internet P2P applications causes two new performance problems due to the requirement of uploading the downloaded traffic for other peers, limited bandwidth of wireless communications, and resource competition between the access point and wireless stations. First, an active P2P wireless user can significantly reduce the downloading throughput of other wireless users in the WLAN. Second, the slowdown of a P2P wireless user communication can also delay its relay and data sharing service for other dependent wired/wireless peers. In order to address these problems, in this paper, we propose an efficient caching mechanism called SCAP (Smart Caching in Access Points). Conducting intensive Internet measurements on representative P2P streaming applications, we observe a high percentage of duplicated data packets in successive downloading and uploading data streams. Through duplication detection and caching at the access point, these duplicated packets can be compressed so that the uploading traffic in the WLAN is significantly reduced. Our prototype-based experimental evaluation demonstrates that by effectively reducing the redundant P2P traffic in the WLAN, SCAP improves the throughput of the WLAN by up to 88% and reduces the response delay to other Internet users meanwhile.

While the 802.11 power saving mode (PSM) and its enhancements can reduce power consumption by putting the wireless network interface (WNI) into sleep as much as possible, they either require additional infrastructure support, or may degrade the transmission throughput and cause additional transmission delay. These schemes are not suitable for long and bulk data transmissions with strict QoS requirements on wireless devices. With increasingly abundant bandwidth available on the Internet, we have observed that TCP congestion control is often not a constraint of bulk data transmissions as bandwidth throttling is widely used in practice. In this paper, instead of further manipulating the trade-off between the power saving and the incurred delay, we effectively explore the power saving potential by considering the bandwidth throttling on streaming/downloading servers. We propose an application-independent protocol, called PSM-throttling. With a quick detection on the TCP flow throughput, a client can identify bandwidth throttling connections with a low cost Since the throttling enables us to reshape the TCP traffic into periodic bursts with the same average throughput as the server transmission rate, the client can accurately predict the arriving time of packets and turn on/off the WNI accordingly. PSM-throttling can minimize power consumption on TCP-based bulk traffic by effectively utilizing available Internet bandwidth without degrading the application's performance perceived by the user. Furthermore, PSM-throttling is client-centric, and does not need any additional infrastructure support. Our lab-environment and Internet-based evaluation results show that PSM-throttling can effectively improve energy savings (by up to 75%) and/or the QoS for a broad types of TCP-based applications, including streaming, pseudo streaming, and large file downloading, over existing PSM-like methods.

No abstract available.

This paper presents a performance study of BitTorrent-like P2P systems by modeling, based on extensive measurements and trace analysis. Existing studies on BitTorrent systems are single-torrent based and usually assume the process of request arrivals to a torrent is Poisson-like. However, in reality, most BitTorrent peers participate in multiple torrents and file popularity changes over time. Our study of representative BitTorrent traffic provides insights into the evolution of single-torrent systems and several new findings regarding the limitations of BitTorrent systems: (1) Due to the exponentially decreasing peer arrival rate in a torrent, the service availability of the corresponding file becomes poor quickly, and eventually it is hard to locate and download this file. (2) Client performance in the BitTorrent-like system is unstable, and fluctuates significantly with the changes of the number of online peers. (3) Existing systems could provide unfair services to peers, where a peer with a higher downloading speed tends to download more and upload less. Motivated by the analysis and modeling results, we have further proposed a graph based model to study interactions among multiple torrents. Our model quantitatively demonstrates that inter-torrent collaboration is much more effective than stimulating seeds to serve longer for addressing the service unavailability in BitTorrent systems. An architecture for inter-torrent collaboration under an exchange based instant incentive mechanism is also discussed and evaluated by simulations.

Modern Internet streaming services have utilized various techniques to improve the quality of streaming media delivery. Despite the characterization of media access patterns and user behaviors in many measurement studies, few studies have focused on the streaming techniques themselves, particularly on the quality of streaming experiences they offer end users and on the resources of the media systems that they consume. In order to gain insights into current streaming services techniques and thus provide guidance on designing resource-efficient and high quality streaming media systems, we have collected a large streaming media workload from thousands of broadband home users and business users hosted by a major ISP, and analyzed the most commonly used streaming techniques such as automatic protocol switch, Fast Streaming, MBR encoding and rate adaptation. Our measurement and analysis results show that with these techniques, current streaming systems these techniques tend to over-utilize CPU and bandwidth resources to provide better services to end users, which may not be a desirable and effective is not necessary the best way to improve the quality of streaming media delivery. Motivated by these results, we propose and evaluate a coordination mechanism that effectively takes advantage of both Fast Streaming and rate adaptation to better utilize the server and Internet resources for streaming quality improvement.