Robust random early detection (RRED) is a queueing discipline for a network scheduler. The existing random early detection (RED) algorithm and its variants are found vulnerable to emerging attacks, especially the Low-rate Denial-of-Service attacks (LDoS). Experiments have confirmed that the existing RED-like algorithms are notably vulnerable under LDoS attacks due to the oscillating TCP queue size caused by the attacks. [1]
The Robust RED (RRED) algorithm was proposed to improve the TCP throughput against LDoS attacks. The basic idea behind the RRED is to detect and filter out attack packets before a normal RED algorithm is applied to incoming flows. RRED algorithm can significantly improve the performance of TCP under Low-rate denial-of-service attacks. [1]
A detection and filter block is added in front of a regular RED block on a router. The basic idea behind the RRED is to detect and filter out LDoS attack packets from incoming flows before they feed to the RED algorithm. How to distinguish an attacking packet from normal TCP packets is critical in the RRED design.
Within a benign TCP flow, the sender will delay sending new packets if loss is detected (e.g., a packet is dropped). Consequently, a packet is suspected to be an attacking packet if it is sent within a short-range after a packet is dropped. This is the basic idea of the detection algorithm of Robust RED (RRED). [1]
algorithm RRED-ENQUE(pkt) 01 f ← RRED-FLOWHASH(pkt) 02 Tmax ← MAX(Flow[f].T1, T2) 03 if pkt.arrivaltime is within [Tmax, Tmax+T*] then 04 reduce local indicator by 1 for each bin corresponding to f 05 else 06 increase local indicator by 1 for each bin of f 07 Flow[f].I ← maximum of local indicators from bins of f 08 if Flow[f].I ≥ 0 then 09 RED-ENQUE(pkt) // pass pkt to the RED block 10 if RED drops pkt then 11 T2 ← pkt.arrivaltime 12 else 13 Flow[f].T1 ← pkt.arrivaltime 14 drop(pkt) 15 return
The simulation code of the RRED algorithm is published as an active queue management and denial-of-service attack (AQM&DoS) simulation platform. The AQM&DoS Simulation Platform is able to simulate a variety of DoS attacks (Distributed DoS, Spoofing DoS, Low-rate DoS, etc.) and active queue management (AQM) algorithms (RED, RRED, SFB, etc.). It automatically calculates and records the average throughput of normal TCP flows before and after DoS attacks to facilitate the analysis of the impact of DoS attacks on normal TCP flows and AQM algorithms.
The Transmission Control Protocol (TCP) is one of the main protocols of the Internet protocol suite. It originated in the initial network implementation in which it complemented the Internet Protocol (IP). Therefore, the entire suite is commonly referred to as TCP/IP. TCP provides reliable, ordered, and error-checked delivery of a stream of octets (bytes) between applications running on hosts communicating via an IP network. Major internet applications such as the World Wide Web, email, remote administration, and file transfer rely on TCP, which is part of the Transport Layer of the TCP/IP suite. SSL/TLS often runs on top of TCP.
In computing, a denial-of-service attack is a cyber-attack in which the perpetrator seeks to make a machine or network resource unavailable to its intended users by temporarily or indefinitely disrupting services of a host connected to a network. Denial of service is typically accomplished by flooding the targeted machine or resource with superfluous requests in an attempt to overload systems and prevent some or all legitimate requests from being fulfilled.
Explicit Congestion Notification (ECN) is an extension to the Internet Protocol and to the Transmission Control Protocol and is defined in RFC 3168 (2001). ECN allows end-to-end notification of network congestion without dropping packets. ECN is an optional feature that may be used between two ECN-enabled endpoints when the underlying network infrastructure also supports it.
Network congestion in data networking and queueing theory is the reduced quality of service that occurs when a network node or link is carrying more data than it can handle. Typical effects include queueing delay, packet loss or the blocking of new connections. A consequence of congestion is that an incremental increase in offered load leads either only to a small increase or even a decrease in network throughput.
FAST TCP is a TCP congestion avoidance algorithm especially targeted at long-distance, high latency links, developed at the Netlab, California Institute of Technology and now being commercialized by FastSoft. FastSoft was acquired by Akamai Technologies in 2012.
Random early detection (RED), also known as random early discard or random early drop, is a queuing discipline for a network scheduler suited for congestion avoidance.
A traffic generation model is a stochastic model of the traffic flows or data sources in a communication network, for example a cellular network or a computer network. A packet generation model is a traffic generation model of the packet flows or data sources in a packet-switched network. For example, a web traffic model is a model of the data that is sent or received by a user's web-browser. These models are useful during the development of telecommunication technologies, in view to analyse the performance and capacity of various protocols, algorithms and network topologies.
TCP global synchronization in computer networks can happen to TCP/IP flows during periods of congestion because each sender will reduce their transmission rate at the same time when packet loss occurs.
Packet loss occurs when one or more packets of data travelling across a computer network fail to reach their destination. Packet loss is either caused by errors in data transmission, typically across wireless networks, or network congestion. Packet loss is measured as a percentage of packets lost with respect to packets sent.
Weighted random early detection (WRED) is a queueing discipline for a network scheduler suited for congestion avoidance. It is an extension to random early detection (RED) where a single queue may have several different sets of queue thresholds. Each threshold set is associated to a particular traffic class.
Bandwidth management is the process of measuring and controlling the communications on a network link, to avoid filling the link to capacity or overfilling the link, which would result in network congestion and poor performance of the network. Bandwidth is described by bit rate and measured in units of bits per second (bit/s) or bytes per second (B/s).
In routers and switches, active queue management (AQM) is the policy of dropping packets inside a buffer associated with a network interface controller (NIC) before that buffer becomes full, often with the goal of reducing network congestion or improving end-to-end latency. This task is performed by the network scheduler, which for this purpose uses various algorithms such as random early detection (RED), Explicit Congestion Notification (ECN), or controlled delay (CoDel). RFC 7567 recommends active queue management as a best practice.
Tail drop is a simple queue management algorithm used by network schedulers in network equipment to decide when to drop packets. With tail drop, when the queue is filled to its maximum capacity, the newly arriving packets are dropped until the queue has enough room to accept incoming traffic.
Intrusion detection system evasion techniques are modifications made to attacks in order to prevent detection by an intrusion detection system (IDS). Almost all published evasion techniques modify network attacks. The 1998 paper Insertion, Evasion, and Denial of Service: Eluding Network Intrusion Detection popularized IDS evasion, and discussed both evasion techniques and areas where the correct interpretation was ambiguous depending on the targeted computer system. The 'fragroute' and 'fragrouter' programs implement evasion techniques discussed in the paper. Many web vulnerability scanners, such as 'Nikto', 'whisker' and 'Sandcat', also incorporate IDS evasion techniques.
Blue is a scheduling discipline for the network scheduler developed by graduate student Wu-chang Feng for Professor Kang G. Shin at the University of Michigan and others at the Thomas J. Watson Research Center of IBM in 1999.
Bufferbloat is a cause of high latency and jitter in packet-switched networks caused by excess buffering of packets. Bufferbloat can also cause packet delay variation, as well as reduce the overall network throughput. When a router or switch is configured to use excessively large buffers, even very high-speed networks can become practically unusable for many interactive applications like voice over IP (VoIP), audio streaming, online gaming, and even ordinary web browsing.
Zeta-TCP refers to a set of proprietary Transmission Control Protocol (TCP) algorithms aiming at improving the end-to-end performance of TCP, regardless of whether the peer is Zeta-TCP or any other TCP protocol stack, in other words, to be compatible with the existing TCP algorithms. It was designed and implemented by AppEx Networks Corporation.
CoDel is an active queue management (AQM) algorithm in network routing, developed by Van Jacobson and Kathleen Nichols and published as RFC8289. It is designed to overcome bufferbloat in networking hardware, such as routers, by setting limits on the delay network packets experience as they pass through buffers in this equipment. CoDel aims to improve on the overall performance of the random early detection (RED) algorithm by addressing some of its fundamental misconceptions, as perceived by Jacobson, and by being easier to manage.
A network scheduler, also called packet scheduler, queueing discipline (qdisc) or queueing algorithm, is an arbiter on a node in a packet switching communication network. It manages the sequence of network packets in the transmit and receive queues of the protocol stack and network interface controller. There are several network schedulers available for the different operating systems, that implement many of the existing network scheduling algorithms.
The Fast Adaptive and Secure Protocol (FASP) is a proprietary data transfer protocol. FASP is a network-optimized network protocol created by Michelle C. Munson and Serban Simu, productized by Aspera, and now owned by IBM subsequent to its acquisition of Aspera. The associated client/server software packages are also commonly called Aspera. The technology is patented under US Patent #8085781, Bulk Data Transfer, #20090063698, Method and system for aggregate bandwidth control. and others.