Distributed Denial Of Service Defense Research Articles

An IP-Traceback-based Packet Filtering Scheme for Eliminating DDoS Attacks

Distributed Denial-of-Service (DDoS) is still an important security challenge for computer networks. Filter-based DDoS defense is considered as an effective approach, since it can defend against both victim-resource-consumption attacks and link-congestion attacks. However, the high possibility of false positive and the huge consumption of router resources reduce the practicality of existing filter-based approaches. In order to solve this problem, we propose a new mechanism to efficiently eliminate the impact caused by DDoS attacks. We utilize the IP traceback results to obtain an attack graph that contains the candidate filtering routers. Taking the different filtering performance of the routers in the attack graph into consideration, we propose a filtering scheme to determine a small set of filtering routers that would increase filtering performance and reduce false positive. Simulation results based on real-world network topologies demonstrate that the proposed scheme can reduce the damage caused by DDoS attacks effectively and maintain the loss of normal traffic within an acceptable level.

SShield: small DDoS defense system using RIP-based traffic deflection in autonomous system

DDoS (distributed denial of service) attacks have gradually increased and have become more sophisticated. There have been several methods for defending against these attacks. However, because the types and scales of DDoS attacks have been diversified, it has become important to defend against DDoS attacks not only in main networks, but also in small scale networks such as AS (autonomous system). We have designed a DDoS defense system working inside AS without either changing the network structure or modifying the router. For this purpose, we have applied the Shield mechanism, which deals with the location problem in DDoS defense, and utilizes the routing updates protocol called RIP (routing information protocol), a representative protocol of IGP (interior gateway protocol). Moreover, we have also conducted experiments by using simulations to find the optimal number and locations of deployed systems.

Triple DoS: DDoS defence and traceback

Distributed denial of service (DDoS) attacks occur when a host of compromised systems are used to target a single system. This single system can be either an actual machine or a network resource. These attacks are prevalent and hard to deal with because they are distributed. They come from many machines, making them hard to trace and even harder to counter. There are also a host of tools available which make it easier for an attacker to launch a DDoS attack. This ubiquity is increasing the level of difficulty related to defending against these attacks. This paper proposes a mechanism, DDDoS, or triple DoS, to deal with DDoS attacks on the internet layer. There are registration and authentication protocols to connect clients and servers so that an unregistered client cannot access the network and flood it with traffic. The triple DoS service will be activated only when a DDoS attack is detected (using clustering), and it will ensure that registered clients and servers can always communicate. It includes a tracing mechanism to allow the originator of the DDoS attack to be identified.

Hadoop Based Defense Solution to Handle Distributed Denial of Service (DDoS) Attacks

Distributed denial of service (DDoS) attacks continues to grow as a threat to organizations worldwide. From the first known attack in 1999 to the highly publicized Operation Ababil, the DDoS attacks have a history of flooding the victim network with an enormous number of packets, hence exhausting the resources and preventing the legitimate users to access them. After having standard DDoS defense mechanism, still attackers are able to launch an attack. These inadequate defense mechanisms need to be improved and integrated with other solutions. The purpose of this paper is to study the characteristics of DDoS attacks, various models involved in attacks and to provide a timeline of defense mechanism with their improvements to combat DDoS attacks. In addition to this, a novel scheme is proposed to detect DDoS attack efficiently by using MapReduce programming model.

Geographical Division Traceback for Distributed Denial of Service

Problem statement: Distributed Denial of Service (DDoS) was a serious threat to the internet world that denies the legitimate users from being access the internet by blocking the service. Approach: In this study, we proposed a novel approach, Geographical Division Traceback (GDT) for efficient IP traceback and DDoS defense methodology. DDoS attack was one of the most serious and threatening issue in the modern world web because of its notorious harmfulness and it causes the delay in the availability of services to the intended users. Results: Unless like a traditional traceback methodology, GDT proposes a quick mechanism to identify the attacker with the help of single packet which imposes very less computational overhead on the routers and also victim can avoid receiving data from the same machine in future. This mechanism for IP Traceback utilizes the geographical information for finding out the machine which was responsible for making the delay was proposed. The IP packet consists of the subspaces details in which the path denotes. It helps to make sure whether the packet travels in the network and falls within any one of the subspaces. The division of subspaces leads to the source of attack system. Conclusion/Recommendations: This method possesses several advantageous features such as easy traversing to the attacker and improves the efficiency of tracing the attacker system.

Thwarting DDoS attacks in grid using information divergence

The Grid is an emerging resource intensive environment that aims at utilizing resources efficiently and effectively. Distributed Denial-of-Service (DDoS) attacks on the Grid can have a devastating effect since there are several resource constraints in a Grid environment. A DDoS can cause large-scale damage to resources and availability of the resources to genuine Grid users. This paper proposes a five-fold DDoS Defense Mechanism using an Information Divergence scheme that detects the attacker and discards the adversary’s packets for a fixed amount of time in an organized manner. The trust value is adjusted based on the attack intensity to ensure a trustworthy system. The mitigation is carried out by limiting the bandwidth of the attacking IP instead of completely blocking the attackers IPs. With this, the job success rate is more by the proposed approach compared to completely blocking the attackers IP approach.

DDoS Attack and Defense Scheme in Wireless Ad hoc Networks

The wireless ad hoc networks are highly vulnerable to distributed denial of service(DDoS) attacks because of its unique characteristics such as open network architecture, shared wireless medium and stringent resource constraints. These attacks throttle the tcp throughput heavily and reduce the quality of service(QoS) to end systems gradually rather than refusing the clients from the services completely. In this paper, we discussed the DDoS attacks and proposed a defense scheme to improve the performance of the ad hoc networks. Our proposed defense mechanism uses the medium access control (MAC) layer information to detect the attackers. The status values from MAC layer that can be used for detection are Frequency of receiving RTS/CTS packets, Frequency of sensing a busy channel and the number of RTS/DATA retransmissions. Once the attackers are identified, all the packets from those nodes will be blocked. The network resources are made available to the legitimate users. We perform the simulation with Network Simulator NS2 and we proved that our proposed system improves the network performance.

Defending against Distributed Denial of Service Attacks: Issues and Challenges

ABSTRACT Distributed Denial of Service (DDoS) attacks on user machines, organizations, and infrastructures of the Internet have become highly publicized incidents and call for immediate solution. It is a complex and difficult problem characterized by an explicit attempt of the attackers to prevent access to resources by legitimate users for which they have authorization. Several schemes have been proposed on how to defend against these attacks, yet the problem still lacks a complete solution. The main purpose of this paper is therefore twofold. First is to present a comprehensive study of a wide range of DDoS attacks and defense methods proposed to combat them. This provides better understanding of the problem, current solution space, and future research scope to defend against DDoS attacks. Second is to propose an integrated solution for completely defending against flooding DDoS attacks at the Internet Service Provider (ISP) level.

Differentiating Malicious DDoS Attack Traffic from Normal TCP Flows by Proactive Tests

To defend against distributed denial of service (DDoS) attacks, one critical issue is to effectively isolate the attack traffic from the normal ones. A novel DDoS defense scheme based on TCP is hereby contrived because TCP is the dominant traffic for both the normal and lethal flows in the Internet. Unlike most of the previous DDoS defense schemes that are passive in nature, the proposal uses proactive tests to identify and isolate the malicious traffic. Simulation results validate the effectiveness of our proposed scheme

DDoS defense algorithm based on multi-segment timeout technology

Through the analysis to the DDoS(distributed denial of service) attack, it will conclude that at different time segments, the arrive rate of normal SYN (Synchronization) package are similar, while the abnormal packages are different with the normal ones. Toward this situation a DDoS definse algorithm based on multi-segment timeout technology is presented, more than one timeout segment are set to control the net flow. Experiment results show that in the case of little flow, multi-segment timeout has the ability dynamic defense, so the system performance is improved and the system has high response rate.

An Inline Detection and Prevention Framework for Distributed Denial of Service Attacks

By penetrating into a large number of machines and stealthily installing malicious pieces of code, a distributed denial of service (DDoS) attack constructs a hierarchical network and uses it to launch coordinated assaults. DDoS attacks often exhaust the network bandwidth, processing capacity and information resources of victims, thus, leading to unavailability of computing systems services. Various defense mechanisms for the detection, mitigation and/or prevention of DDoS attacks have been suggested including resource redundancy, traceback of attack origins and identification of programs with suspicious behavior. Contemporary DDoS attacks employ sophisticated techniques including formation of hierarchical networks, one-way communication channels, encrypted messages, dynamic ports allocation and source address spoofing to hide the attackers' identities; such techniques make both detection and tracing of DDoS activities a challenge and render traditional DDoS defense mechanisms ineffective. In this paper, we propose the DDoS Container, a comprehensive framework that uses network-based detection methods to overcome the above complex and evasive types of attacks; the framework operates in 'inline' mode to inspect and manipulate ongoing traffic in real-time. By keeping track of connections established by both potential DDoS attacks and legitimate applications, the suggested DDoS Container carries out stateful inspection on data streams and correlates events among sessions. The framework performs stream re-assembly and dissects the resulting aggregations against protocols followed by various known DDoS attacks facilitating their identification. The traffic pattern analysis and data correlation of the framework further enhance its detection accuracy on DDoS traffic camouflaged with encryption. Actions available on identified DDoS traffic range from simple alerting to message blocking and proactive session termination. Experimentation with the prototype of our DDoS Container shows its effectiveness in classifying DDoS traffic.

ALPi: A DDoS Defense System for High-Speed Networks

Distributed denial-of-service (DDoS) attacks pose a significant threat to the Internet. Most solutions proposed to-date face scalability problems as the size and speed of the network increase, with no widespread DDoS solution deployed in the industry. PacketScore has been proposed as a proactive DDoS defense scheme, which detects DDoS attacks, differentiates attack packets from legitimate ones with the use of packet scoring (where the score of a packet is calculated based on attribute values it possesses), and discards packets whose scores are lower than a dynamic threshold. In this paper, we propose ALPi, a new scheme which extends the packet scoring concept with reduced implementation complexity and enhanced performance. More specifically, a leaky-bucket overflow control scheme simplifies the score computation, and facilitates high-speed implementation. An attribute-value-variation scoring scheme analyzes the deviations of the current traffic attribute values, and increases the accuracy of detecting and differentiating attacks. An enhanced control-theoretic packet discarding method allows both schemes to be more adaptive to challenging attacks such as those with ever-changing signatures and intensities. When combined together, the proposed extensions not only greatly reduce the memory requirement and implementation complexity but also substantially improve the accuracies in attack detection and packet differentiation. This makes ALPi an attractive DDoS defense system amenable for high-speed hardware implementation.

StackPi: New Packet Marking and Filtering Mechanisms for DDoS and IP Spoofing Defense

Today's Internet hosts are threatened by large-scale distributed denial-of-service (DDoS) attacks. The path identification (Pi) DDoS defense scheme has recently been proposed as a deterministic packet marking scheme that allows a DDoS victim to filter out attack packets on a per packet basis with high accuracy after only a few attack packets are received (Yaar , 2003). In this paper, we propose the StackPi marking, a new packet marking scheme based on Pi, and new filtering mechanisms. The StackPi marking scheme consists of two new marking methods that substantially improve Pi's incremental deployment performance: Stack-based marking and write-ahead marking. Our scheme almost completely eliminates the effect of a few legacy routers on a path, and performs 2-4 times better than the original Pi scheme in a sparse deployment of Pi-enabled routers. For the filtering mechanism, we derive an optimal threshold strategy for filtering with the Pi marking. We also develop a new filter, the PiIP filter, which can be used to detect Internet protocol (IP) spoofing attacks with just a single attack packet. Finally, we discuss in detail StackPi's compatibility with IP fragmentation, applicability in an IPv6 environment, and several other important issues relating to potential deployment of StackPi

PacketScore: A Statistics-Based Packet Filtering Scheme against Distributed Denial-of-Service Attacks

Distributed denial-of-service (DDoS) attacks are a critical threat to the Internet. This paper introduces a DDoS defense scheme that supports automated online attack characterizations and accurate attack packet discarding based on statistical processing. The key idea is to prioritize a packet based on a score which estimates its legitimacy given the attribute values it carries. Once the score of a packet is computed, this scheme performs score-based selective packet discarding where the dropping threshold is dynamically adjusted based on the score distribution of recent incoming packets and the current level of system overload. This paper describes the design and evaluation of automated attack characterizations, selective packet discarding, and an overload control process. Special considerations are made to ensure that the scheme is amenable to high-speed hardware implementation through scorebook generation and pipeline processing. A simulation study indicates that packetscore is very effective in blocking several different attack types under many different conditions.

D-WARD: A Source-End Defense against Flooding Denial-of-Service Attacks

Defenses against flooding distributed denial-of-service (DDoS) commonly respond to the attack by dropping the excess traffic, thus reducing the overload at the victim. The major challenge is the differentiation of the legitimate from the attack traffic, so that the dropping policies can be selectively applied. We propose D-WARD, a source-end DDoS defense system that achieves autonomous attack detection and surgically accurate response, thanks to its novel traffic profiling techniques, the adaptive response and the source-end deployment. Moderate traffic volumes seen near the sources, even during the attacks, enable extensive statistics gathering and profiling, facilitating high response selectiveness. D-WARD inflicts an extremely low collateral damage to the legitimate traffic, while quickly detecting and severely rate-limiting outgoing attacks. D-WARD has been extensively evaluated in a controlled testbed environment and in real network operation. Results of selected tests are presented in the paper.

Characterization of defense mechanisms against distributed denial of service attacks

We propose a characterization of distributed denial of service (DDOS) defenses where reaction points are network-based and attack responses are active. The purpose is to provide a framework for comparing the performance and deployment of DDOS defenses. We identify the characteristics in attack detection algorithms and attack responses by reviewing defenses that have appeared in the literature. We expect that this characterization will provide practitioners and academia insights into deploying DDOS defense as network services.

A taxonomy of DDoS attack and DDoS defense mechanisms

Distributed denial-of-service (DDoS) is a rapidly growing problem. The multitude and variety of both the attacks and the defense approaches is overwhelming. This paper presents two taxonomies for classifying attacks and defenses, and thus provides researchers with a better understanding of the problem and the current solution space. The attack classification criteria was selected to highlight commonalities and important features of attack strategies, that define challenges and dictate the design of countermeasures. The defense taxonomy classifies the body of existing DDoS defenses based on their design decisions; it then shows how these decisions dictate the advantages and deficiencies of proposed solutions.

DDoS attacks and defense mechanisms: classification and state-of-the-art

Denial of Service (DoS) attacks constitute one of the major threats and among the hardest security problems in today’s Internet. Of particular concern are Distributed Denial of Service (DDoS) attacks, whose impact can be proportionally severe. With little or no advance warning, a DDoS attack can easily exhaust the computing and communication resources of its victim within a short period of time. Because of the seriousness of the problem many defense mechanisms have been proposed to combat these attacks. This paper presents a structural approach to the DDoS problem by developing a classification of DDoS attacks and DDoS defense mechanisms. Furthermore, important features of each attack and defense system category are described and advantages and disadvantages of each proposed scheme are outlined. The goal of the paper is to place some order into the existing attack and defense mechanisms, so that a better understanding of DDoS attacks can be achieved and subsequently more efficient and effective algorithms, techniques and procedures to combat these attacks may be developed.

Sustaining availability of web services under distributed denial of service attacks

The recent tide of Distributed Denial of Service (DDoS) attacks against high-profile web sites demonstrate how devastating DDoS attacks are and how defenseless the Internet is under such attacks. We design a practical DDoS defense system that can protect the availability of web services during severe DDoS attacks. The basic idea behind our system is to isolate and protect legitimate traffic from a huge volume of DDoS traffic when an attack occurs. Traffic that needs to be protected can be recognized and protected using efficient cryptographic techniques. Therefore, by provisioning adequate resource (e.g., bandwidth) to legitimate traffic separated by this process, we are able to provide adequate service to a large percentage of clients during DDoS attacks. The worst-case performance (effectiveness) of the system is evaluated based on a novel game theoretical framework, which characterizes the natural adversarial relationship between a DDoS adversary and the proposed system. We also conduct a simulation study to verify a key assumption used in the game-theoretical analysis and to demonstrate the system dynamics during an attack.