265 research outputs found

    Command & Control: Understanding, Denying and Detecting - A review of malware C2 techniques, detection and defences

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    In this survey, we first briefly review the current state of cyber attacks, highlighting significant recent changes in how and why such attacks are performed. We then investigate the mechanics of malware command and control (C2) establishment: we provide a comprehensive review of the techniques used by attackers to set up such a channel and to hide its presence from the attacked parties and the security tools they use. We then switch to the defensive side of the problem, and review approaches that have been proposed for the detection and disruption of C2 channels. We also map such techniques to widely-adopted security controls, emphasizing gaps or limitations (and success stories) in current best practices.Comment: Work commissioned by CPNI, available at c2report.org. 38 pages. Listing abstract compressed from version appearing in repor

    Designing incentives for peer-to-peer systems

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    Peer-to-peer systems, networks of egalitarian nodes without a central authority, can achieve massive scalability and fault tolerance through the pooling together of individual resources. Unfortunately, most nodes represent self-interested, or rational, parties that will attempt to maximize their consumption of shared resources while minimizing their own contributions. This constitutes a type of attack that can destabilize the system. The first contribution of this thesis is a proposed taxonomy for these rational attacks and the most common solutions used in contemporary designs to thwart them. One approach is to design the P2P system with incentives for cooperation, so that rational nodes voluntarily behave. We broadly classify these incentives as being either genuine or artificial , with the former describing incentives inherent in peer interactions, and the latter describing a secondary enforcement system. We observe that genuine incentives tend to be more robust to rational manipulations than artificial counterparts. Based on this observation, we also propose two extensions to BitTorrent, a P2P file distribution protocol. While this system is popular, accounting for approximately one-third of current Internet traffic, it has known limitations. Our extensions use genuine incentives to address some of these problems. The first extension improves seeding, an altruistic mode wherein nodes that have completed their download continue to provide upload service. We incentivize seeding by giving long-term identifiers to clients enabling seeding clients to be recognized and rewarded in subsequent downloads. Simulations demonstrate that our method is highly effective in protecting swarms from aggressive clients such as BitTyrant. Finally, we introduce The BitTorrent Anonymity Marketplace , wherein each peer simultaneously joins multiple swarms to disguise their true download intentions. Peers then trade one torrent for another, making the cover traffic valuable as a means of obtaining the real target. Thus, when a neighbor receives a request from a peer for blocks of a torrent, it does not know if the peer is really downloading that torrent, or only using it in trade. Using simulation, we demonstrate that nodes cannot determine peer intent from observed interactions

    Measurement and analysis of BitTorrent

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    BitTorrent is assumed and predicted to be the world's largest Peer to Peer (P2P) network. Previous studies of the protocol mainly focus on its file sharing algorithm, and many relevant aspects of the protocol remain untouched. In the thesis, we conduct a number of experiments to explore those untouched aspects. We implement a BitTorrent crawler to collect data from trackers and peers, and statistically analyze it to understand the characteristics and behaviors of the BitTorrent protocol better. We find that the expected lifetime of a peer in the BitTorrent is 56.6 minutes and the activity is diurnal. Peers show strong preference towards a limited number of torrents, and 10% of torrents are responsible for 67% of traffic. The US contributes maximum number of peers to the BitTorrent and µTorrent emerges as the favorite BitTorrent client. We measure the strength of Distributed Denial of Service (DDoS) attack using BitTorrent network and conclude that it is transient and weak. Finally we address and discuss the content locatability problem in BitTorrent and propose two solutions

    A Framework For Efficient Data Distribution In Peer-to-peer Networks.

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    Peer to Peer (P2P) models are based on user altruism, wherein a user shares its content with other users in the pool and it also has an interest in the content of the other nodes. Most P2P systems in their current form are not fair in terms of the content served by a peer and the service obtained from swarm. Most systems suffer from free rider\u27s problem where many high uplink capacity peers contribute much more than they should while many others get a free ride for downloading the content. This leaves high capacity nodes with very little or no motivation to contribute. Many times such resourceful nodes exit the swarm or don\u27t even participate. The whole scenario is unfavorable and disappointing for P2P networks in general, where participation is a must and a very important feature. As the number of users increases in the swarm, the swarm becomes robust and scalable. Other important issues in the present day P2P system are below optimal Quality of Service (QoS) in terms of download time, end-to-end latency and jitter rate, uplink utilization, excessive cross ISP traffic, security and cheating threats etc. These current day problems in P2P networks serve as a motivation for present work. To this end, we present an efficient data distribution framework in Peer-to-Peer (P2P) networks for media streaming and file sharing domain. The experiments with our model, an alliance based peering scheme for media streaming, show that such a scheme distributes data to the swarm members in a near-optimal way. Alliances are small groups of nodes that share data and other vital information for symbiotic association. We show that alliance formation is a loosely coupled and an effective way to organize the peers and our model maps to a small world network, which form efficient overlay structures and are robust to network perturbations such as churn. We present a comparative simulation based study of our model with CoolStreaming/DONet (a popular model) and present a quantitative performance evaluation. Simulation results show that our model scales well under varying workloads and conditions, delivers near optimal levels of QoS, reduces cross ISP traffic considerably and for most cases, performs at par or even better than Cool-Streaming/DONet. In the next phase of our work, we focussed on BitTorrent P2P model as it the most widely used file sharing protocol. Many studies in academia and industry have shown that though BitTorrent scales very well but is far from optimal in terms of fairness to end users, download time and uplink utilization. Furthermore, random peering and data distribution in such model lead to suboptimal performance. Lately, new breed of BitTorrent clients like BitTyrant have shown successful strategic attacks against BitTorrent. Strategic peers configure the BitTorrent client software such that for very less or no contribution, they can obtain good download speeds. Such strategic nodes exploit the altruism in the swarm and consume resources at the expense of other honest nodes and create an unfair swarm. More unfairness is generated in the swarm with the presence of heterogeneous bandwidth nodes. We investigate and propose a new token-based anti-strategic policy that could be used in BitTorrent to minimize the free-riding by strategic clients. We also proposed other policies against strategic attacks that include using a smart tracker that denies the request of strategic clients for peer listmultiple times, and black listing the non-behaving nodes that do not follow the protocol policies. These policies help to stop the strategic behavior of peers to a large extent and improve overall system performance. We also quantify and validate the benefits of using bandwidth peer matching policy. Our simulations results show that with the above proposed changes, uplink utilization and mean download time in BitTorrent network improves considerably. It leaves strategic clients with little or no incentive to behave greedily. This reduces free riding and creates fairer swarm with very little computational overhead. Finally, we show that our model is self healing model where user behavior changes from selfish to altruistic in the presence of the aforementioned policies

    A credit-based approach to scalable video transmission over a peer-to-peer social network

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    PhDThe objective of the research work presented in this thesis is to study scalable video transmission over peer-to-peer networks. In particular, we analyse how a credit-based approach and exploitation of social networking features can play a significant role in the design of such systems. Peer-to-peer systems are nowadays a valid alternative to the traditional client-server architecture for the distribution of multimedia content, as they transfer the workload from the service provider to the final user, with a subsequent reduction of management costs for the former. On the other hand, scalable video coding helps in dealing with network heterogeneity, since the content can be tailored to the characteristics or resources of the peers. First of all, we present a study that evaluates subjective video quality perceived by the final user under different transmission scenarios. We also propose a video chunk selection algorithm that maximises received video quality under different network conditions. Furthermore, challenges in building reliable peer-to-peer systems for multimedia streaming include optimisation of resource allocation and design mechanisms based on rewards and punishments that provide incentives for users to share their own resources. Our solution relies on a credit-based architecture, where peers do not interact with users that have proven to be malicious in the past. Finally, if peers are allowed to build a social network of trusted users, they can share the local information they have about the network and have a more complete understanding of the type of users they are interacting with. Therefore, in addition to a local credit, a social credit or social reputation is introduced. This thesis concludes with an overview of future developments of this research work

    Stochastic analysis of P2P file sharing systems.

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    Lin, Minghong.Thesis (M.Phil.)--Chinese University of Hong Kong, 2008.Includes bibliographical references (p. 49-51).Abstracts in English and Chinese.Abstract --- p.iAcknowledgement --- p.vChapter 1 --- Introduction --- p.1Chapter 2 --- A Stochastic Framework --- p.5Chapter 2.1 --- Model Description --- p.5Chapter 2.2 --- Altruistic File Sharing System with Download Con- straint --- p.7Chapter 2.2.1 --- Model Formulation --- p.8Chapter 2.2.2 --- Steady State Analysis --- p.9Chapter 2.3 --- Altruistic File Sharing System with Download and Upload Constraints --- p.14Chapter 2.3.1 --- Model Formulation --- p.14Chapter 2.3.2 --- Steady State Analysis --- p.15Chapter 2.4 --- Incentive File Sharing via Coordinated Matching --- p.18Chapter 2.4.1 --- Without Incentive Mechanism --- p.18Chapter 2.4.2 --- With Incentive Mechanism --- p.19Chapter 2.5 --- Simulation --- p.23Chapter 3 --- An ISP-friendly Protocol --- p.28Chapter 3.1 --- Simple Mathematical Models --- p.28Chapter 3.1.1 --- Assumptions --- p.29Chapter 3.1.2 --- Homogeneous Case Analysis --- p.30Chapter 3.1.3 --- Heterogeneous Case Analysis --- p.31Chapter 3.1.4 --- Flash Crowd Analysis --- p.32Chapter 3.2 --- An ISP-friendly BitTorrent Protocol --- p.33Chapter 3.3 --- Performance Evaluation & Measurements --- p.36Chapter 3.3.1 --- Choice of the BitTorrent Client --- p.37Chapter 3.3.2 --- Experimental Setup --- p.37Chapter 3.3.3 --- Regular Peer Arrival --- p.38Chapter 3.3.4 --- Flash Crowd --- p.41Chapter 3.4 --- Black Hole Security Attack --- p.42Chapter 4 --- Related Work --- p.46Chapter 5 --- Conclusion --- p.48Bibliography --- p.49Appendix --- p.5
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