319 research outputs found

    Preventing DDoS using Bloom Filter: A Survey

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    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

    Adaptive algorithms for identifying large flows in IP traffic

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    We propose in this paper an on-line algorithm based on Bloom filters for identifying large flows in IP traffic (a.k.a. elephants). Because of the large number of small flows, hash tables of these algorithms have to be regularly refreshed. Recognizing that the periodic erasure scheme usually used in the technical literature turns out to be quite inefficient when using real traffic traces over a long period of time, we introduce a simple adaptive scheme that closely follows the variations of traffic. When tested against real traffic traces, the proposed on-line algorithm performs well in the sense that the detection ratio of long flows by the algorithm over a long time period is quite high. Beyond the identification of elephants, this same class of algorithms is applied to the closely related problem of detection of anomalies in IP traffic, e.g., SYN flood due for instance to attacks. An algorithm for detecting SYN and volume flood anomalies in Internet traffic is designed. Experiments show that an anomaly is detected in less than one minute and the targeted destinations are identified at the same time

    TCP-SYN Flooding Attack in Wireless Networks

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    This paper concerns the TCP (Transmission Control Protocol) vulnerabilities which gives space for a DoS (Denial of Service) attacks called TCP-SYN flooding which is well-known to the community for several years. The paper shows this attack in wireless as well as wired networks using perl synflood script, Wireshark network analyzer server, Windows 2008 server, and OPNET simulation environment. Using these tools an effects of this attack are shown. Finally, some effective practical mitigation techniques against SYN flooding attack for Linux and Windows systems are explained

    Analysis of the SYN Flood DoS Attack

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    The paper analyzes systems vulnerability targeted by TCP (Transmission Control Protocol) segments when SYN flag is ON, which gives space for a DoS (Denial of Service) attack called SYN flooding attack or more often referred as a SYN flood attack. The effects of this type of attack are analyzed and presented in OPNET simulation environment. Furthermore, the paper presents two anomaly detection algorithms as an effective mechanism against this type of attack. Finally, practical approaches against SYN flood attack for Linux and Windows environment are shown

    Locating Network Domain Entry and Exit point/path for DDoS Attack Traffic

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    A method to determine entry and exit points or paths of DDoS attack traffic flows into and out of network domains is proposed. We observe valid source addresses seen by routers from sampled traffic under non-attack conditions. Under attack conditions, we detect route anomalies by determining which routers have been used for unknown source addresses, to construct the attack paths. We consider deployment issues and show results from simulations to prove the feasibility of our scheme. We then implement our Traceback mechanism in C++ and more realistic experiments are conducted. The experiments show that accurate results, with high traceback speed of a few seconds, are achieved. Compared to existing techniques, our approach is non-intrusive, not requiring any changes to the Internet routers and data packets. Precise information regarding the attack is not required allowing a wide variety of DDoS attack detection techniques to be used. The victim is also relieved from the traceback task during an attack. The scheme is simple and efficient, allowing for a fast traceback, and scalable due to the distribution of processing workload. © 2009 IEEE.Accepted versio

    Analysis of the SYN Flood DoS Attack

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    Mitigating Botnet-based DDoS Attacks against Web Servers

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    Distributed denial-of-service (DDoS) attacks have become wide-spread on the Internet. They continuously target retail merchants, financial companies and government institutions, disrupting the availability of their online resources and causing millions of dollars of financial losses. Software vulnerabilities and proliferation of malware have helped create a class of application-level DDoS attacks using networks of compromised hosts (botnets). In a botnet-based DDoS attack, an attacker orders large numbers of bots to send seemingly regular HTTP and HTTPS requests to a web server, so as to deplete the server's CPU, disk, or memory capacity. Researchers have proposed client authentication mechanisms, such as CAPTCHA puzzles, to distinguish bot traffic from legitimate client activity and discard bot-originated packets. However, CAPTCHA authentication is vulnerable to denial-of-service and artificial intelligence attacks. This dissertation proposes that clients instead use hardware tokens to authenticate in a federated authentication environment. The federated authentication solution must resist both man-in-the-middle and denial-of-service attacks. The proposed system architecture uses the Kerberos protocol to satisfy both requirements. This work proposes novel extensions to Kerberos to make it more suitable for generic web authentication. A server could verify client credentials and blacklist repeated offenders. Traffic from blacklisted clients, however, still traverses the server's network stack and consumes server resources. This work proposes Sentinel, a dedicated front-end network device that intercepts server-bound traffic, verifies authentication credentials and filters blacklisted traffic before it reaches the server. Using a front-end device also allows transparently deploying hardware acceleration using network co-processors. Network co-processors can discard blacklisted traffic at the hardware level before it wastes front-end host resources. We implement the proposed system architecture by integrating existing software applications and libraries. We validate the system implementation by evaluating its performance under DDoS attacks consisting of floods of HTTP and HTTPS requests

    Distributed reflection denial of service attack: A critical review

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    As the world becomes increasingly connected and the number of users grows exponentially and “things” go online, the prospect of cyberspace becoming a significant target for cybercriminals is a reality. Any host or device that is exposed on the internet is a prime target for cyberattacks. A denial-of-service (DoS) attack is accountable for the majority of these cyberattacks. Although various solutions have been proposed by researchers to mitigate this issue, cybercriminals always adapt their attack approach to circumvent countermeasures. One of the modified DoS attacks is known as distributed reflection denial-of-service attack (DRDoS). This type of attack is considered to be a more severe variant of the DoS attack and can be conducted in transmission control protocol (TCP) and user datagram protocol (UDP). However, this attack is not effective in the TCP protocol due to the three-way handshake approach that prevents this type of attack from passing through the network layer to the upper layers in the network stack. On the other hand, UDP is a connectionless protocol, so most of these DRDoS attacks pass through UDP. This study aims to examine and identify the differences between TCP-based and UDP-based DRDoS attacks
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