Preventing DDoS using Bloom Filter: A Survey

Distributed Denial-of-Service (DDoS) is a menace for service provider and prominent issue in network security. Defeating or defending the DDoS is a prime challenge. DDoS make a service unavailable for a certain time. This phenomenon harms the service providers, and hence, loss of business revenue. Therefore, DDoS is a grand challenge to defeat. There are numerous mechanism to defend DDoS, however, this paper surveys the deployment of Bloom Filter in defending a DDoS attack. The Bloom Filter is a probabilistic data structure for membership query that returns either true or false. Bloom Filter uses tiny memory to store information of large data. Therefore, packet information is stored in Bloom Filter to defend and defeat DDoS. This paper presents a survey on DDoS defending technique using Bloom Filter.Comment: 9 pages, 1 figure. This article is accepted for publication in EAI Endorsed Transactions on Scalable Information System

An Approach for Mitigating Denial of Service Attack

Distributed Denial of Service (DDoS) attacks are the most common types of cyber-attack on the internet and are rapidly increasing. Denial of service/distributed denial of service attack is an explicit attempt to make a machine or a network resource unavailable to its intended users. Attackers interrupt/suspend services of the host connected to internet temporarily or indefinitely.It involves saturating the target machine with external communication requests such that it cannot either respond to legitimate traffic or responds so slowly as to be rendered effectively unavailable. Two general form of Dos attacks are - those attacks that crashes services (computer attack) and those that flood services (network attack). Flooding DDoS attacks produce adverse effects for critical infrastructure availability, integrity and confidentiality. Current defense approaches cannot efficiently detect and filter out the attack traffic in real time. Based on the assumption that the attacker flows are very aggressive than the legitimate users the proposed work provides sufficient bandwidth to genuine users during flooding DDoS attack.The aim of the project is to implement an approach for mitigating DDoS based on “The Interface Based Rate Limiting (IBRL) algorithm”, used to mitigate the identified DDoS attacks. The implementation is carried out on a simulation tool Omnett++ installed on linux machine. The results are the plots that show that there is considerable increase in the two important and significant measures, response time and packet drop metrics for legitimate users even under DoS and DDoS attacks

DoS and DDoS Attacks: Defense, Detection and Traceback Mechanisms - A Survey

Denial of Service (DoS) or Distributed Denial of Service (DDoS) attacks are typically explicit attempts to exhaust victim2019;s bandwidth or disrupt legitimate users2019; access to services. Traditional architecture of internet is vulnerable to DDoS attacks and it provides an opportunity to an attacker to gain access to a large number of compromised computers by exploiting their vulnerabilities to set up attack networks or Botnets. Once attack network or Botnet has been set up, an attacker invokes a large-scale, coordinated attack against one or more targets. Asa result of the continuous evolution of new attacks and ever-increasing range of vulnerable hosts on the internet, many DDoS attack Detection, Prevention and Traceback mechanisms have been proposed, In this paper, we tend to surveyed different types of attacks and techniques of DDoS attacks and their countermeasures. The significance of this paper is that the coverage of many aspects of countering DDoS attacks including detection, defence and mitigation, traceback approaches, open issues and research challenges

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

IP spoofing attack and its countermeasures

IP spoofing is a technique used to gain unauthorized access to computers, whereby the intruder sends messages to a computer with an IP address indicating that the message is coming from a trusted host. It causes serious security problem in the cyber world, and is currently exploited widely in the information warfare. This paper at first introduces the IP spoofing attack through examples, technical issues and attacking types. Later its countermeasures are analysed in detail, which include authentication and encription, filtering and IP traceback. In particular, an IP traceback mechanism, Flexible Deterministic Packet Marking (FDPM) is presented. Since the IP spoofing problem can not be solved only by technology, but it also needs social regulation, the legal issues and economic impact are discussed in the later part.<br /

TDDA- Traceback-based Defence against DDoS Attack

Look In today's fast growing of internet use, security of the data and information, resources and other useful files are more important viewpoints. Distributed Denial-of-Service (DDoS) attacks are responsible for making a machine or network resource unavailable to its appropriate users. Also a DDoS attack reduces the efficiency or capability of the server to doing its job. That’s why they are very challenging issues for us. The problem is rises when spoofed IP addresses are present in the attack packets. In order to solve this critical situation of problem, that’s why we proposed a new mechanism to efficiently reduce the impact or outcome caused by DDoS attacks. In some cases, even if the attacking traffic can be filtered by the victim side, here also the attacker may blocks the access of the victim by consuming the computing resources or by consuming a large amount portion of the bandwidth of the victim. This paper is proposes a Traceback-based Defense against DDoS Attacks (TDDA) approach to resolve this problem very goodly. In this paper, we present and design one technique that can be impressively filter out the majority of DDoS attack traffic. Our primary objective or intention for this work is to improving the overall throughput and performance of the appropriate traffic and also reduce the attack traffic to maintain the quality of service for that user