This paper presents a simple and robust mechanism, called Change-Point Monitoring (CPM), to detect denial of service (DoS) attacks. The core of CPM is based on the inherent network protocol behaviors, and is an instance of the Sequential Change Point Detection. To make the detection mechanism insensitive to sites and traffic patterns, a non-parametric Cumulative Sum (CUSUM) method is applied, thus making the detection mechanism robust, more generally applicable and its deployment much easier. CPM does not require per-flow state information and only introduces a few variables to record the protocol behaviors. The statelessness and low computation overhead of CPM make itself immune to any flooding attacks. As a case study, the efficacy of CPM is evaluated by detecting a SYN flooding attack — the most common DoS attack. The evaluation results show that CPM has short detection latency and high detection accuracy.

Current intrusion detection and prevention systems seek to detect a wide class of network intrusions (e.g., DoS attacks, worms, port scans) at network vantage points. Unfortunately, even today, many IDS systems we know of keep per-connection or per-flow state to detect malicious TCP flows. Thus, it is hardly surprising that these IDS systems have not scaled to multi-gigabit speeds. By contrast, both router lookups and fair queuing have scaled to high speeds using aggregation via prefix lookups or DiffServ. Thus, in this paper, we initiate research into the question as to whether one can detect attacks without keeping per-flow state. We will show that such aggregation, while making fast implementations possible, immediately causes two problems. First, aggregation can cause behavioral aliasing where, for example, good behaviors can aggregate to look like bad behaviors. Second, aggregated schemes are susceptible to spoofing by which the intruder sends attacks that have appropriate aggregate behavior. We examine a wide variety of DoS and scanning attacks and show that several categories (bandwidth based, claim-and-hold, port-scanning) can be scalably detected. In addition to existing approaches for scalable attack detection, we propose a novel data structure called partial completion filters (PCFs) that can detect claim-and-hold attacks scalably in the network. We analyze PCFs both analytically and using experiments on real network traces to demonstrate how we can tune PCFs to achieve extremely low false positive and false negative probabilities.

As more and more Internet IP prefix hijacking incidents are being reported, the value of hijacking detection services has become evident. Most of the current hijacking detection approaches monitor IP prefixes on the control plane and detect inconsistencies in route advertisements and route qualities. We propose a different approach that utilizes information collected mostly from the data plane. Our method is motivated by two key observations: when a prefix is not hijacked, 1) the hop count of the path from a source to this prefix is generally stable; and 2) the path from a source to this prefix is almost always a super-path of the path from the same source to a reference point along the previous path, as long as the reference point is topologically close to the prefix. By carefully selecting multiple vantage points and monitoring from these vantage points for any departure from these two observations, our method is able to detect prefix hijacking with high accuracy in a light-weight, distributed, and real-time fashion. Through simulations constructed based on real Internet measurement traces, we demonstrate that our scheme is accurate with both false positive and false negative ratios below 0.5%.

Abstract — A new approach for filtering spoofed IP packets, called Spoofing Prevention Method (SPM), is proposed. The method enables routers closer to the destination of a packet to verify the authenticity of the source address of the packet. This stands in contrast to standard ingress filtering which is effective mostly at routers next to the source and is ineffective otherwise. In the proposed method a unique temporal key is associated with each ordered pair of source destination networks (AS’s, autonomous systems). Each packet leaving a source network S is tagged with the key K(S, D), associated with (S, D), where D is the destination network. Upon arrival at the destination network the key is verified and removed. Thus the method verifies the authenticity of packets carrying the address s which belongs to network S. An efficient implementation of the method, ensuring not to overload the routers, is presented. The major benefits of the method are the strong incentive it provides to network operators to implement it, and the fact that the method lends itself to stepwise deployment, since it benefits networks deploying the method even if it is implemented only on parts of the Internet. These two properties, not shared by alternative approaches, make it an attractive and viable solution to the packet spoofing problem.

A key challenge in combating Denial of Service (DoS) attacks is to reliably identify attack sources from packet contents. If a source can be reliably identified, routers can stop an attack by filtering packets from the attack sources without causing collateral damage to legitimate traffic. This task is difficult because attackers may spoof arbitrary packet contents to hide their identities. This paper proposes a packet passport system to address this challenge. A packet passport efficiently and securely authenticates the source of a packet. A packet with a valid passport must have originated from the claimed source. The packet passport system can be incrementally deployed without introducing extra control messages. It also provides incentives for early adoption: a domain that deploys packet passport system can prevent other domains from spoofing its source identifiers. Our preliminary analysis suggests that the packet passport system can be implemented at high-speed routers with today’s technologies. 1

In this paper we analyze a new class of pulsing denialof-service (PDoS) attacks that could seriously degrade the throughput of TCP flows. During a PDoS attack, periodic pulses of attack packets are sent to a victim. The magnitude of each pulse should be significant enough to cause packet losses. We describe two specific attack models according to the timing of the attack pulses with respect to the TCP’s congestion window movement: timeout-based and AIMD (additive-increasemultiplicative-decrease)-based. We show through an analysis that even a small number of attack pulses can cause significant throughput degradation. The second part of this paper is a novel two-stage scheme to detect PDoS attacks on a victim network. The first stage is based on a wavelet transform used to extract the desired frequency components of the data traffic and ACK traffic. The second stage is to detect change points in the extracted components. Through both simulation and testbed experiments, we verify the feasibility and effectiveness of the detection scheme. 1

We present WebSOS, a novel overlay-based architecture that provides guaranteed access to a web server that is targeted by a denial of service (DoS) attack. Our approach exploits two key characteristics of the web environment: its design around a human-centric interface, and the extensibility inherent in many browsers through downloadable “applets. ” We guarantee access to a web server for a large number of previously unknown users, without requiring pre-existing trust relationships between users and the system, by using Reverse Graphic Turing Tests. Furthermore, our system makes it easy for service providers to charge users, providing incentives to a commercial offering of the service. Users can dynamically decide whether to use the WebSOS overlay, based on the prevailing network conditions. Our prototype requires no modifications to either servers or browsers, and makes use of graphical Turing tests, web proxies, and client authentication using the SSL/TLS protocol, all readily supported by modern browsers. We then extend this system with a credentialbased micropayment scheme that combines access control and payment authorization in one operation. Turing Tests ensure that malicious code, such as a worm, cannot abuse a user’s micropayment wallet. We use the WebSOS prototype to conduct a performance evaluation over the Internet using PlanetLab, a testbed for experimentation with network overlays. We determine the end-to-end latency using both a Chord-based approach and our shortcut extension. Our evaluation shows the latency increase by a factor of 7 and 2 respectively, confirming our simulation results.

Most network intrusion tools (e.g., Bro) use per-flow state to reassemble TCP connections and fragments in order to detect network attacks (e.g., SYN Flooding or Connection Hijacking) and preliminary reconnaissance (e.g., Port Scans). On the other hand, if network intrusion detection is to be implemented at high speeds at network vantage points, some form of aggregation is necessary. While many security analysts believe that such per-flow state is required for many of these problems, there is no clear proof that this is the case. In fact, a number of problems (such as detecting large traffic footprints or counting identifiers) have scalable solutions. In this paper, we initiate the study of identifying when and how a security attack detection problem can have a scalable solution. We use tools from Communication Complexity to prove that the common formulations of many well-known intrusion detection problems (detecting SYN Flooding, Port Scans, Connection Hijacking, and content matching across fragments) require per-flow state. Our theory exposes assumptions that need to be changed to provide scalable solutions to these problems; we conclude with some systems techniques to circumvent these lower bounds.

We present the design and evaluation of Passport, a system that allows source addresses to be validated within the network. Passport uses efficient, symmetric-key cryptography to place tokens on packets that allow each autonomous system (AS) along the network path to independently verify that a source address is valid. It leverages the routing system to efficiently distribute the symmetric keys used for verification, and is incrementally deployable without upgrading hosts. We have implemented Passport with Click and XORP and evaluated the design via micro-benchmarking, experiments on the Deterlab, security analysis, and adoptability modeling. We find that Passport is plausible for gigabit links, and can mitigate reflector attacks even without separate denial-of-service defenses. Our adoptability modeling shows that Passport provides stronger security and deployment incentives than alternatives such as ingress filtering. This is because the ISPs that adopt it protect their own addresses from being spoofed at each other’s networks even when the overall deployment is small. 1.

Numerous techniques have been proposed by which an end-system, subjected to a denial-of-service flood, filters the offending traffic. In this paper, we provide an empirical analysis of several such proposals, using traffic recorded at the border of a large network and including real DoS traffic. We focus our analysis on four filtering techniques, two based on the addresses from which the victim server typically receives traffic (static clustering and network-aware clustering), and two based on coarse indications of the path each packet traverses (hop-count filtering and path identifiers). Our analysis reveals challenges facing the proposed techniques in practice, and the implications of these issues for effective filtering. In addition, we compare techniques on equal footing, by evaluating the performance of one scheme under assumptions made by another. We conclude with an interpretation of the results and suggestions for further analysis. 1.