Rethinking Routing and Peering in the era of Vertical Integration of Network Functions

Content providers typically control the digital content consumption services and are getting the most revenue by implementing an all-you-can-eat model via subscription or hyper-targeted advertisements. Revamping the existing Internet architecture and design, a vertical integration where a content provider and access ISP will act as unibody in a sugarcane form seems to be the recent trend. As this vertical integration trend is emerging in the ISP market, it is questionable if existing routing architecture will suffice in terms of sustainable economics, peering, and scalability. It is expected that the current routing will need careful modifications and smart innovations to ensure effective and reliable end-to-end packet delivery. This involves new feature developments for handling traffic with reduced latency to tackle routing scalability issues in a more secure way and to offer new services at cheaper costs. Considering the fact that prices of DRAM or TCAM in legacy routers are not necessarily decreasing at the desired pace, cloud computing can be a great solution to manage the increasing computation and memory complexity of routing functions in a centralized manner with optimized expenses. Focusing on the attributes associated with existing routing cost models and by exploring a hybrid approach to SDN, we also compare recent trends in cloud pricing (for both storage and service) to evaluate whether it would be economically beneficial to integrate cloud services with legacy routing for improved cost-efficiency. In terms of peering, using the US as a case study, we show the overlaps between access ISPs and content providers to explore the viability of a future in terms of peering between the new emerging content-dominated sugarcane ISPs and the healthiness of Internet economics. To this end, we introduce meta-peering, a term that encompasses automation efforts related to peering – from identifying a list of ISPs likely to peer, to injecting control-plane rules, to continuous monitoring and notifying any violation – one of the many outcroppings of vertical integration procedure which could be offered to the ISPs as a standalone service

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

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

A composable approach to design of newer techniques for large-scale denial-of-service attack attribution

Since its early days, the Internet has witnessed not only a phenomenal growth, but also a large number of security attacks, and in recent years, denial-of-service (DoS) attacks have emerged as one of the top threats. The stateless and destination-oriented Internet routing combined with the ability to harness a large number of compromised machines and the relative ease and low costs of launching such attacks has made this a hard problem to address. Additionally, the myriad requirements of scalability, incremental deployment, adequate user privacy protections, and appropriate economic incentives has further complicated the design of DDoS defense mechanisms. While the many research proposals to date have focussed differently on prevention, mitigation, or traceback of DDoS attacks, the lack of a comprehensive approach satisfying the different design criteria for successful attack attribution is indeed disturbing. Our first contribution here has been the design of a composable data model that has helped us represent the various dimensions of the attack attribution problem, particularly the performance attributes of accuracy, effectiveness, speed and overhead, as orthogonal and mutually independent design considerations. We have then designed custom optimizations along each of these dimensions, and have further integrated them into a single composite model, to provide strong performance guarantees. Thus, the proposed model has given us a single framework that can not only address the individual shortcomings of the various known attack attribution techniques, but also provide a more wholesome counter-measure against DDoS attacks. Our second contribution here has been a concrete implementation based on the proposed composable data model, having adopted a graph-theoretic approach to identify and subsequently stitch together individual edge fragments in the Internet graph to reveal the true routing path of any network data packet. The proposed approach has been analyzed through theoretical and experimental evaluation across multiple metrics, including scalability, incremental deployment, speed and efficiency of the distributed algorithm, and finally the total overhead associated with its deployment. We have thereby shown that it is realistically feasible to provide strong performance and scalability guarantees for Internet-wide attack attribution. Our third contribution here has further advanced the state of the art by directly identifying individual path fragments in the Internet graph, having adopted a distributed divide-and-conquer approach employing simple recurrence relations as individual building blocks. A detailed analysis of the proposed approach on real-life Internet topologies with respect to network storage and traffic overhead, has provided a more realistic characterization. Thus, not only does the proposed approach lend well for simplified operations at scale but can also provide robust network-wide performance and security guarantees for Internet-wide attack attribution. Our final contribution here has introduced the notion of anonymity in the overall attack attribution process to significantly broaden its scope. The highly invasive nature of wide-spread data gathering for network traceback continues to violate one of the key principles of Internet use today - the ability to stay anonymous and operate freely without retribution. In this regard, we have successfully reconciled these mutually divergent requirements to make it not only economically feasible and politically viable but also socially acceptable. This work opens up several directions for future research - analysis of existing attack attribution techniques to identify further scope for improvements, incorporation of newer attributes into the design framework of the composable data model abstraction, and finally design of newer attack attribution techniques that comprehensively integrate the various attack prevention, mitigation and traceback techniques in an efficient manner

Effective Wide-Area Network Performance Monitoring and Diagnosis from End Systems.

The quality of all network application services running on today’s Internet heavily depends on the performance assurance offered by the Internet Service Providers (ISPs). Large network providers inside the core of the Internet are instrumental in determining the network properties of their transit services due to their wide-area coverage, especially in the presence of the increasingly deployed real-time sensitive network applications. The end-to-end performance of distributed applications and network services are susceptible to network disruptions in ISP networks. Given the scale and complexity of the Internet, failures and performance problems can occur in different ISP networks. It is important to efficiently identify and proactively respond to potential problems to prevent large damage. Existing work to monitor and diagnose network disruptions are ISP-centric, which relying on each ISP to set up monitors and diagnose within its network. This approach is limited as ISPs are unwilling to revealing such data to the public. My dissertation research developed a light-weight active monitoring system to monitor, diagnose and react to network disruptions by purely using end hosts, which can help customers assess the compliance of their service-level agreements (SLAs). This thesis studies research problems from three indispensable aspects: efficient monitoring, accurate diagnosis, and effective mitigation. This is an essential step towards accountability and fairness on the Internet. To fully understand the limitation of relying on ISP data, this thesis first studies and demonstrates the monitor selection’s great impact on the monitoring quality and the interpretation of the results. Motivated by the limitation of ISP-centric approach, this thesis demonstrates two techniques to diagnose two types of finegrained causes accurately and scalably by exploring information across routing and data planes, as well as sharing information among multiple locations collaboratively. Finally, we demonstrate usefulness of the monitoring and diagnosis results with two mitigation applications. The first application is short-term prevention of avoiding choosing the problematic route by exploring the predictability from history. The second application is to scalably compare multiple ISPs across four important performance metrics, namely reachability, loss rate, latency, and path diversity completely from end systems without any ISP cooperation.Ph.D.Computer Science & EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/64770/1/wingying_1.pd

Reassembler - Towards a Global DDoS Attack Analysis Using Attack Fingerprints

In recent years, the frequency and scale of Distributed Denial-of-Service (DDoS) attacks have increased significantly, yet they remain an unsolved problem. Many intrusion detection systems employ shared attack fingerprints and signatures as a standard practice to detect cyber attacks. For DDoS attacks, a single attack fingerprint typically is not enough to detect other attacks of the same kind. However, attack fingerprints can still be useful, especially when the same attack is observed from multiple locations. Thus, this work proposes Reassembler, a tool that enables global analysis of DDoS attacks based on attack fingerprints recorded at different locations. For this, multiple attack scenarios are specified using a custom-built simulated network. Based on the attack scenarios, the Reassembler solution is implemented, analyzing and aggregating attack fingerprints into a global view. Reassembler is evaluated based on four simulated and one real use case (based on real DDoS network traces), demonstrating that the Reassembler can derive interesting properties such as the number of intermediate nodes or the estimated percentage of spoofed IPs. Based on different experiments, it is shown under which circumstances the Reassembler performs best and where improvements are needed

Survival in the e-conomy: 2nd Australian information warfare & security conference 2001

This is an international conference for academics and industry specialists in information warfare, security, and other related fields. The conference has drawn participants from national and international organisations

Large-Scale Measurement of Real-Time Communication on the Web

Web Real-Time Communication (WebRTC) is getting wide adoptions across the browsers (Chrome, Firefox, Opera, etc.) and platforms (PC, Android, iOS). It enables application developers to add real-time communications features (text chat, audio/video calls) to web applications using W3C standard JavaScript APIs, and the end users can enjoy real-time multimedia communication experience from the browser without the complication of installing special applications or browser plug-ins. As WebRTC based applications are getting deployed on the Internet by thousands of companies across the globe, it is very important to understand the quality of the real-time communication services provided by these applications. Important performance metrics to be considered include: whether the communication session was properly setup, what are the network delays, packet loss rate, throughput, etc. At Callstats.io, we provide a solution to address the above concerns. By integrating an JavaScript API into WebRTC applications, Callstats.io helps application providers to measure the Quality of Experience (QoE) related metrics on the end user side. This thesis illustrates how this WebRTC performance measurement system is designed and built and we show some statistics derived from the collected data to give some insight into the performance of today’s WebRTC based real-time communication services. According to our measurement, real-time communication over the Internet are generally performing well in terms of latency and loss. The throughput are good for about 30% of the communication sessions

Framework for botnet emulation and analysis

Criminals use the anonymity and pervasiveness of the Internet to commit fraud, extortion, and theft. Botnets are used as the primary tool for this criminal activity. Botnets allow criminals to accumulate and covertly control multiple Internet-connected computers. They use this network of controlled computers to flood networks with traffic from multiple sources, send spam, spread infection, spy on users, commit click fraud, run adware, and host phishing sites. This presents serious privacy risks and financial burdens to businesses and individuals. Furthermore, all indicators show that the problem is worsening because the research and development cycle of the criminal industry is faster than that of security research. To enable researchers to measure botnet connection models and counter-measures, a flexible, rapidly augmentable framework for creating test botnets is provided. This botnet framework, written in the Ruby language, enables researchers to run a botnet on a closed network and to rapidly implement new communication, spreading, control, and attack mechanisms for study. This is a significant improvement over augmenting C++ code-bases for the most popular botnets, Agobot and SDBot. Rubot allows researchers to implement new threats and their corresponding defenses before the criminal industry can. The Rubot experiment framework includes models for some of the latest trends in botnet operation such as peer-to-peer based control, fast-flux DNS, and periodic updates. Our approach implements the key network features from existing botnets and provides the required infrastructure to run the botnet in a closed environment.Ph.D.Committee Chair: Copeland, John; Committee Member: Durgin, Gregory; Committee Member: Goodman, Seymour; Committee Member: Owen, Henry; Committee Member: Riley, Georg

Incentive-driven QoS in peer-to-peer overlays

A well known problem in peer-to-peer overlays is that no single entity has control over the software, hardware and configuration of peers. Thus, each peer can selfishly adapt its behaviour to maximise its benefit from the overlay. This thesis is concerned with the modelling and design of incentive mechanisms for QoS-overlays: resource allocation protocols that provide strategic peers with participation incentives, while at the same time optimising the performance of the peer-to-peer distribution overlay. The contributions of this thesis are as follows. First, we present PledgeRoute, a novel contribution accounting system that can be used, along with a set of reciprocity policies, as an incentive mechanism to encourage peers to contribute resources even when users are not actively consuming overlay services. This mechanism uses a decentralised credit network, is resilient to sybil attacks, and allows peers to achieve time and space deferred contribution reciprocity. Then, we present a novel, QoS-aware resource allocation model based on Vickrey auctions that uses PledgeRoute as a substrate. It acts as an incentive mechanism by providing efficient overlay construction, while at the same time allocating increasing service quality to those peers that contribute more to the network. The model is then applied to lagsensitive chunk swarming, and some of its properties are explored for different peer delay distributions. When considering QoS overlays deployed over the best-effort Internet, the quality received by a client cannot be adjudicated completely to either its serving peer or the intervening network between them. By drawing parallels between this situation and well-known hidden action situations in microeconomics, we propose a novel scheme to ensure adherence to advertised QoS levels. We then apply it to delay-sensitive chunk distribution overlays and present the optimal contract payments required, along with a method for QoS contract enforcement through reciprocative strategies. We also present a probabilistic model for application-layer delay as a function of the prevailing network conditions. Finally, we address the incentives of managed overlays, and the prediction of their behaviour. We propose two novel models of multihoming managed overlay incentives in which overlays can freely allocate their traffic flows between different ISPs. One is obtained by optimising an overlay utility function with desired properties, while the other is designed for data-driven least-squares fitting of the cross elasticity of demand. This last model is then used to solve for ISP profit maximisation

IP traceback with deterministic packet marking DPM

In this dissertation, a novel approach to Internet Protocol (IP) Traceback - Deterministic Packet Marking (DPM) is presented. The proposed approach is scalable, simple to implement, and introduces no bandwidth and practically no processing overhead on the network equipment. It is capable of tracing thousands of simultaneous attackers during a Distributed Denial of Service (DDoS) attack. Given sufficient deployment on the Internet, DPM is capable of tracing back to the slaves for DDoS attacks which involve reflectors. Most of the processing is done at the victim. The traceback process can be performed post-mortem, which allows for tracing the attacks that may not have been noticed initially or the attacks which would deny service to the victim, so that traceback is impossible in real time. Deterministic Packet Marking does not introduce the errors for the reassembly errors usually associated with other packet marking schemes. More than 99.99% of fragmented traffic will not be affected by DPM. The involvement of the Internet service providers (ISP) is very limited, and changes to the infrastructure and operation required to deploy DPM are minimal. Deterministic Packet Marking performs the traceback without revealing the internal topology of the provider\u27s network, which is a desirable quality of a traceback scheme