23,761 research outputs found

    Preventing DDoS using Bloom Filter: A Survey

    Full text link
    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

    Defending Against Denial of Service

    Get PDF
    Civil Society currently faces significant cyber threats. At the top of the list of those threats are Denial of Service (DoS) attacks. The websites of many organizations and individuals have already come under such attacks, and the frequency of those attacks are on the rise. Civil Society frequently does not have the kinds of resources or technical know-how that is available to commercial enterprise and government websites, and often have to exist in adverse political environments where every avenue available, both legal and illegal, is used against them. Therefore, the threat of DoS attacks is unlikely to go away any time soon.A Denial of Service (DoS) attack is any attack that overwhelms a website, causing the content normally provided by that website to no longer be available to regular visitors of the website. Distributed Denial of Service (DDoS) attacks are traffic volumebased attacks originating from a large number of computers, which are usually compromised workstations. These workstations, known as 'zombies', form a widely distributed attack network called a 'botnet'. While many modern Denial of Service attacks are Distributed Denial of Service attacks, this is certainly not true for all denials of service experienced by websites. Therefore, when users first start experiencing difficulty in getting to the website content, it should not be assumed that the site is under a DDoS attack. Many forms of DoS are far easier to implement than DDoS, and so these attacks are still used by parties with malicious intent. Many such DoS attacks are easier to defend against once the mechanism used to cause the denial of service is known. Therefore, it is paramount to do proper analysis of attack traffic when a site becomes unable to perform its normal function. There are two parts to this guide. The first part outlines preparatory steps that can be taken by Civil Society organizations to improve their website's resilience, should it come under attack. However, we do understand that most Civil Society organizations' first introduction to DoS attacks comes when they suddenly find themselves the victim of an attack. The second part of this guide provides a step-by-step process to assist the staff of NGOs to efficiently deal with that stressful situation

    An SDN-based Approach For Defending Against Reflective DDoS Attacks

    Full text link
    Distributed Reflective Denial of Service (DRDoS) attacks are an immanent threat to Internet services. The potential scale of such attacks became apparent in March 2018 when a memcached-based attack peaked at 1.7 Tbps. Novel services built upon UDP increase the need for automated mitigation mechanisms that react to attacks without prior knowledge of the actual application protocols used. With the flexibility that software-defined networks offer, we developed a new approach for defending against DRDoS attacks; it not only protects against arbitrary DRDoS attacks but is also transparent for the attack target and can be used without assistance of the target host operator. The approach provides a robust mitigation system which is protocol-agnostic and effective in the defense against DRDoS attacks

    Security and Privacy Issues in Wireless Mesh Networks: A Survey

    Full text link
    This book chapter identifies various security threats in wireless mesh network (WMN). Keeping in mind the critical requirement of security and user privacy in WMNs, this chapter provides a comprehensive overview of various possible attacks on different layers of the communication protocol stack for WMNs and their corresponding defense mechanisms. First, it identifies the security vulnerabilities in the physical, link, network, transport, application layers. Furthermore, various possible attacks on the key management protocols, user authentication and access control protocols, and user privacy preservation protocols are presented. After enumerating various possible attacks, the chapter provides a detailed discussion on various existing security mechanisms and protocols to defend against and wherever possible prevent the possible attacks. Comparative analyses are also presented on the security schemes with regards to the cryptographic schemes used, key management strategies deployed, use of any trusted third party, computation and communication overhead involved etc. The chapter then presents a brief discussion on various trust management approaches for WMNs since trust and reputation-based schemes are increasingly becoming popular for enforcing security in wireless networks. A number of open problems in security and privacy issues for WMNs are subsequently discussed before the chapter is finally concluded.Comment: 62 pages, 12 figures, 6 tables. This chapter is an extension of the author's previous submission in arXiv submission: arXiv:1102.1226. There are some text overlaps with the previous submissio

    AMISEC: Leveraging Redundancy and Adaptability to Secure AmI Applications

    Get PDF
    Security in Ambient Intelligence (AmI) poses too many challenges due to the inherently insecure nature of wireless sensor nodes. However, there are two characteristics of these environments that can be used effectively to prevent, detect, and confine attacks: redundancy and continuous adaptation. In this article we propose a global strategy and a system architecture to cope with security issues in AmI applications at different levels. Unlike in previous approaches, we assume an individual wireless node is vulnerable. We present an agent-based architecture with supporting services that is proven to be adequate to detect and confine common attacks. Decisions at different levels are supported by a trust-based framework with good and bad reputation feedback while maintaining resistance to bad-mouthing attacks. We also propose a set of services that can be used to handle identification, authentication, and authorization in intelligent ambients. The resulting approach takes into account practical issues, such as resource limitation, bandwidth optimization, and scalability
    corecore