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DDoS attack diagram. In, a denial-of-service attack ( DoS attack) is a where the perpetrator seeks to make a machine or network resource unavailable to its intended by temporarily or indefinitely disrupting of a connected to the. 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. In a distributed denial-of-service attack ( DDoS attack), the incoming traffic flooding the victim originates from many different sources. This effectively makes it impossible to stop the attack simply by blocking a single source. A DoS or DDoS attack is analogous to a group of people crowding the entry door or gate to a shop or business, and not letting legitimate parties enter into the shop or business, disrupting normal operations.

Criminal perpetrators of DoS attacks often target sites or services hosted on high-profile such as banks or., and can motivate these attacks. This section needs expansion. You can help.

(July 2017) Court testimony shows that the first demonstration of DoS attack was made by Khan C. Smith in 1997 during a event disrupting Internet access to the for over an hour. The release of sample code during the event led to the online attack of,,, and other major corporations in the year to follow.

Types [ ] Denial-of-service attacks are characterized by an explicit attempt by attackers to prevent legitimate users of a service from using that service. There are two general forms of DoS attacks: those that crash services and those that flood services. The most serious attacks are distributed.

Distributed DoS [ ] A distributed denial-of-service ( DDoS) is a cyber-attack where the perpetrator uses more than one unique, often thousands of them. The incoming traffic flooding the victim originates from many different sources. This effectively makes it impossible to stop the attack simply by using. It also makes it very difficult to distinguish legitimate user traffic from attack traffic when spread across so many points of origin.

As an alternative or augmentation of a DDoS, many attacks involve forging of IP sender addresses () also so that the location of the attacking machines cannot easily be identified and defeated. The scale of DDoS attacks has continued to rise over recent years, by 2016 exceeding a per second. Application layer attacks [ ] An application layer DDoS attack (sometimes referred to as layer 7 DDoS attack) is a form of DDoS attack where attackers target the of the. The attack over-exercises specific functions or features of a website with the intention to disable those functions or features. This application-layer attack is different from an entire network attack, and is often used against financial institutions to distract IT and security personnel from security breaches. As of 2013, application layer DDoS attacks represent 20% of all DDoS attacks.

According to research by the company Akamai, there have been '51 percent more application layer attacks' from Q4 2013 to Q4 2014 and '16 percent more' from Q3 2014 over Q4 2014. Application layer [ ]. Main article: The Open Systems Interconnection (OSI) model (ISO/IEC 7498-1) is a conceptual model that characterizes and standardizes the internal functions of a communication system by partitioning it into abstraction layers. The model is a product of the Open Systems Interconnection project at the International Organization for Standardization (ISO). The model groups similar communication functions into one of seven logical layers. A layer serves the layer above it and is served by the layer below it. For example, a layer that provides error-free communications across a network provides the path needed by applications above it, while it calls the next lower layer to send and receive packets that make up the contents of that path.

Two instances at one layer are connected by a horizontal connection on that layer. Main article: In the, the definition of its application layer is narrower in scope. The OSI model defines the application layer as being the user interface. The OSI application layer is responsible for displaying data and images to the user in a human-recognizable format and to interface with the below it. Method of attack [ ] An application layer DDoS attack is done mainly for specific targeted purposes, including disrupting transactions and access to databases.

It requires less resources and often accompanies network layer attacks. An attack is disguised to look like legitimate traffic, except it targets specific application packets. The attack on the application layer can disrupt services such as the retrieval of information or search function as well as web browser function, email services and photo applications. In order to be deemed a distributed denial of service attack, more than around 3–5 nodes on different networks should be used; using fewer than 3–5 nodes qualifies as a and not a DDoS. Advanced persistent DoS [ ] An advanced persistent DoS (APDoS) is more likely to be perpetrated by an (APT): actors who are well-resourced, exceptionally skilled and have access to substantial commercial grade computer resources and capacity. APDoS attacks represent a clear and emerging threat needing specialised monitoring and incident response services and the defensive capabilities of specialised service providers.

This type of attack involves massive network layer DDoS attacks through to focused application layer (HTTP) floods, followed by repeated (at varying intervals) SQLi and XSS attacks. [ ] Typically, the perpetrators can simultaneously use from 2 to 5 attack vectors involving up to several tens of millions of requests per second, often accompanied by large SYN floods that can not only attack the victim but also any service provider implementing any sort of managed DDoS mitigation capability. These attacks can persist for several weeks- the longest continuous period noted so far lasted 38 days.

This APDoS attack involved approximately 50+ petabits (50,000+ terabits) of malicious traffic. Attackers in this scenario may (or often will) tactically switch between several targets to create a diversion to evade defensive DDoS countermeasures but all the while eventually concentrating the main thrust of the attack onto a single victim. In this scenario, threat actors with continuous access to several very powerful network resources are capable of sustaining a prolonged campaign generating enormous levels of un-amplified DDoS traffic. This section does not any. Unsourced material may be challenged and.

(October 2017) () A Nuke is an old denial-of-service attack against consisting of fragmented or otherwise invalid packets sent to the target, achieved by using a modified utility to repeatedly send this corrupt data, thus slowing down the affected computer until it comes to a complete stop. A specific example of a nuke attack that gained some prominence is the, which exploited the vulnerability in the handler in. A string of out-of-band data was sent to port 139 of the victim's machine, causing it to lock up and display a (BSOD).

Peer-to-peer attacks [ ]. Main article: Attackers have found a way to exploit a number of bugs in servers to initiate DDoS attacks. The most aggressive of these peer-to-peer-DDoS attacks exploits. With peer-to-peer there is no botnet and the attacker does not have to communicate with the clients it subverts. Instead, the attacker acts as a 'puppet master,' instructing clients of large hubs to disconnect from their peer-to-peer network and to connect to the victim's website instead. Permanent denial-of-service attacks [ ] Permanent denial-of-service (PDoS), also known loosely as phlashing, is an attack that damages a system so badly that it requires replacement or reinstallation of hardware. Unlike the distributed denial-of-service attack, a PDoS attack exploits security flaws which allow remote administration on the management interfaces of the victim's hardware, such as routers, printers, or other.

The attacker uses these vulnerabilities to replace a device's with a modified, corrupt, or defective firmware image—a process which when done legitimately is known as flashing. This therefore ' the device, rendering it unusable for its original purpose until it can be repaired or replaced. The PDoS is a pure hardware targeted attack which can be much faster and requires fewer resources than using a botnet or a root/vserver in a DDoS attack. Because of these features, and the potential and high probability of security exploits on Network Enabled Embedded Devices (NEEDs), this technique has come to the attention of numerous hacking communities. PhlashDance is a tool created by Rich Smith (an employee of Hewlett-Packard's Systems Security Lab) used to detect and demonstrate PDoS vulnerabilities at the 2008 in London. Reflected / spoofed attack [ ] A distributed denial-of-service attack may involve sending forged requests of some type to a very large number of computers that will reply to the requests. Using, the source address is set to that of the targeted victim, which means all the replies will go to (and flood) the target.

(This reflected attack form is sometimes called a 'DRDOS'. ) attacks () can be considered one form of reflected attack, as the flooding host(s) send Echo Requests to the broadcast addresses of mis-configured networks, thereby enticing hosts to send Echo Reply packets to the victim. Some early DDoS programs implemented a distributed form of this attack. Amplification [ ] Amplification attacks are used to magnify the bandwidth that is sent to a victim. This is typically done through publicly accessible DNS servers that are used to cause congestion on the target system using DNS response traffic.

Many services can be exploited to act as reflectors, some harder to block than others. US-CERT have observed that different services implies in different amplification factors, as you can see below: UDP-based Amplification Attacks Protocol Bandwidth Amplification Factor NTP 556.9 CharGen 358.8 DNS up to 179 QOTD 140.3 Quake Network Protocol 63.9 BitTorrent 4.0 - 54.3 SSDP 30.8 Kad 16.3 SNMPv2 6.3 Steam Protocol 5.5 NetBIOS 3.8 DNS amplification attacks involve a new mechanism that increased the amplification effect, using a much larger list of DNS servers than seen earlier. The process typically involves an attacker sending a DNS name look up request to a public DNS server, spoofing the source IP address of the targeted victim. The attacker tries to request as much zone information as possible, thus amplifying the DNS record response that is sent to the targeted victim. Since the size of the request is significantly smaller than the response, the attacker is easily able to increase the amount of traffic directed at the target. SNMP and can also be exploited as reflector in an amplification attack. An example of an amplified DDoS attack through NTP is through a command called monlist, which sends the details of the last 600 people who have requested the time from that computer back to the requester.

A small request to this time server can be sent using a spoofed source IP address of some victim, which results in 556.9 times the amount of data that was requested back to the victim. This becomes amplified when using botnets that all send requests with the same spoofed IP source, which will send a massive amount of data back to the victim.

It is very difficult to defend against these types of attacks because the response data is coming from legitimate servers. These attack requests are also sent through UDP, which does not require a connection to the server. This means that the source IP is not verified when a request is received by the server. In order to bring awareness of these vulnerabilities, campaigns have been started that are dedicated to finding amplification vectors which has led to people fixing their resolvers or having the resolvers shut down completely. (RUDY) [ ] attack targets web applications by starvation of available sessions on the web server.

Much like, RUDY keeps sessions at halt using never-ending POST transmissions and sending an arbitrarily large content-length header value. Shrew attack [ ] The shrew attack is a denial-of-service attack on the. It uses short synchronized bursts of traffic to disrupt TCP connections on the same link, by exploiting a weakness in TCP's retransmission timeout mechanism. Slow Read attack [ ] A slow read attack sends legitimate application layer requests, but reads responses very slowly, thus trying to exhaust the server's connection pool. It is achieved by advertising a very small number for the TCP Receive Window size, and at the same time emptying clients' TCP receive buffer slowly, which causes a very low data flow rate.

Sophisticated low-bandwidth Distributed Denial-of-Service Attack [ ] A sophisticated low-bandwidth DDoS attack is a form of DoS that uses less traffic and increases their effectiveness by aiming at a weak point in the victim's system design, i.e., the attacker sends traffic consisting of complicated requests to the system. Essentially, a sophisticated DDoS attack is lower in cost due to its use of less traffic, is smaller in size making it more difficult to identify, and it has the ability to hurt systems which are protected by flow control mechanisms. (S)SYN flood [ ]. See also: A occurs when a host sends a flood of TCP/SYN packets, often with a forged sender address. Each of these packets are handled like a connection request, causing the server to spawn a, by sending back a TCP/SYN-ACK packet (Acknowledge), and waiting for a packet in response from the sender address (response to the ACK Packet). However, because the sender address is forged, the response never comes. These half-open connections saturate the number of available connections the server can make, keeping it from responding to legitimate requests until after the attack ends.

Teardrop attacks [ ] A teardrop attack involves sending fragments with overlapping, oversized payloads to the target machine. This can crash various operating systems because of a bug in their code., and operating systems, as well as versions of prior to versions 2.0.32 and 2.1.63 are vulnerable to this attack.

(Although in September 2009, a vulnerability in was referred to as a 'teardrop attack', this targeted which is a higher layer than the TCP packets that teardrop used). One of the fields in an IP header is the “fragment offset” field, indicating the starting position, or offset, of the data contained in a fragmented packet relative to the data in the original packet. If the sum of the offset and size of one fragmented packet differs from that of the next fragmented packet, the packets overlap. When this happens, a server vulnerable to teardrop attacks is unable to reassemble the packets - resulting in a denial-of-service condition. Telephony denial-of-service (TDoS) [ ] has made abusive origination of large numbers of voice calls inexpensive and readily automated while permitting call origins to be misrepresented through. According to the US, telephony denial-of-service (TDoS) has appeared as part of various fraudulent schemes: • A scammer contacts the victim's banker or broker, impersonating the victim to request a funds transfer. The banker's attempt to contact the victim for verification of the transfer fails as the victim's telephone lines are being flooded with thousands of bogus calls, rendering the victim unreachable.

• A scammer contacts consumers with a bogus claim to collect an outstanding for thousands of dollars. When the consumer objects, the scammer retaliates by flooding the victim's employer with thousands of automated calls. In some cases, displayed caller ID is spoofed to impersonate police or law enforcement agencies. • A scammer contacts consumers with a bogus debt collection demand and threatens to send police; when the victim balks, the scammer floods local police numbers with calls on which caller ID is spoofed to display the victims number.

Police soon arrive at the victim's residence attempting to find the origin of the calls. Telephony denial-of-service can exist even without.

In the, were used to flood political opponents with spurious calls to jam phone banks on election day. Widespread publication of a number can also flood it with enough calls to render it unusable, as happened by accident in 1981 with multiple +1--867-5309 subscribers inundated by hundreds of misdialed calls daily in response to the song. TDoS differs from other (such as and ) by the number of calls originated; by occupying lines continuously with repeated automated calls, the victim is prevented from making or receiving both routine and emergency telephone calls. Related exploits include attacks and or fax loop transmission. Defense techniques [ ] Defensive responses to denial-of-service attacks typically involve the use of a combination of attack detection, traffic classification and response tools, aiming to block traffic that they identify as illegitimate and allow traffic that they identify as legitimate.

A list of prevention and response tools is provided below: Application front end hardware [ ] Application front-end hardware is intelligent hardware placed on the network before traffic reaches the servers. It can be used on networks in conjunction with routers and switches. Application front end hardware analyzes data packets as they enter the system, and then identifies them as priority, regular, or dangerous.

There are more than 25 vendors. Application level Key Completion Indicators [ ] In order to meet the case of application level DDoS attacks against cloud-based applications, approaches may be based on an application layer analysis, to indicate whether an incoming traffic bulk is legitimate or not and thus enable the triggering of elasticity decisions without the economical implications of a DDoS attack. These approaches mainly rely on an identified path of value inside the application and monitor the macroscopic progress of the requests in this path, towards the final generation of profit, through markers denoted as Key Completion Indicators. In essence, this technique is a statistical method of assessing the behavior of incoming requests to detect if something unusual or abnormal is going on. Imagine if you were to observe the behavior of normal, paying customers at a brick-and-mortar department store. On average, they would spend in aggregate a known percentage of time on different activities such as picking up items and examining them, putting them back on shelves, trying on clothes, filling a basket, waiting in line, paying for their purchases, and leaving.

These high-level activities correspond to the Key Completion Indicators in a service or site, and once normal behavior is determined, abnormal behavior can be identified. For example, if a huge number of customers arrive and spend all their time picking up items and setting them down, but never making any purchases, this can be flagged as unusual behavior. In the case of elastic cloud services where a huge and abnormal additional workload may incur significant charges from the cloud service provider, this technique can be used to stop or even scale back the elastic expansion of server availability in order to protect from economic loss. In the example analogy, imagine that the department store had the ability to bring in additional employees on a few minutes' notice and routinely did this during 'rushes' of unusual customer volume. If a mob shows up that never does any buying, after a relatively short time of paying for the additional employee costs, the store can scale back the number of employees, understanding that the non-buying customers provide no profit for the store and thus should not be serviced.

While this may prevent the store from making sales to legitimate customers during the period of attack, it saves the potentially ruinous cost of calling up huge numbers of employees to service an illegitimate load. De Delftse Methode Netherlands Voor Buitenlanders Pdf File. Blackholing and sinkholing [ ] With, all the traffic to the attacked DNS or IP address is sent to a 'black hole' (null interface or a non-existent server). To be more efficient and avoid affecting network connectivity, it can be managed by the ISP. A routes traffic to a valid IP address which analyzes traffic and rejects bad packets. Sinkholing is not efficient for most severe attacks. IPS based prevention [ ] (IPS) are effective if the attacks have signatures associated with them. However, the trend among the attacks is to have legitimate content but bad intent.

Intrusion-prevention systems which work on content recognition cannot block behavior-based DoS attacks. [ ] An based IPS may detect and block denial-of-service attacks because they have the and the granularity to analyze the attacks and act like a in an automated way. [ ] A (RBIPS) must analyze traffic granularly and continuously monitor the traffic pattern and determine if there is traffic anomaly. It must let the legitimate traffic flow while blocking the DoS attack traffic. DDS based defense [ ] More focused on the problem than IPS, a DoS defense system (DDS) can block connection-based DoS attacks and those with legitimate content but bad intent. A DDS can also address both protocol attacks (such as teardrop and ping of death) and rate-based attacks (such as ICMP floods and SYN floods).

Firewalls [ ] In the case of a simple attack, a could have a simple rule added to deny all incoming traffic from the attackers, based on protocols, ports or the originating IP addresses. More complex attacks will however be hard to block with simple rules: for example, if there is an ongoing attack on port 80 (web service), it is not possible to drop all incoming traffic on this port because doing so will prevent the server from serving legitimate traffic. Additionally, firewalls may be too deep in the network hierarchy, with routers being adversely affected before the traffic gets to the firewall.

Routers [ ] Similar to switches, routers have some rate-limiting and capability. They, too, are manually set. Most routers can be easily overwhelmed under a DoS attack. Has optional features that can reduce the impact of flooding.

Switches [ ] Most switches have some rate-limiting and capability. Some switches provide automatic and/or system-wide,, (), and (bogus IP filtering) to detect and remediate DoS attacks through automatic rate filtering and WAN Link failover and balancing. [ ] These schemes will work as long as the DoS attacks can be prevented by using them. For example, SYN flood can be prevented using delayed binding or TCP splicing. Similarly content based DoS may be prevented using deep packet inspection. Attacks originating from or going to dark addresses can be prevented using.

Automatic rate filtering can work as long as set rate-thresholds have been set correctly. Wan-link failover will work as long as both links have DoS/DDoS prevention mechanism. [ ] Upstream filtering [ ] All traffic is passed through a 'cleaning center' or a 'scrubbing center' via various methods such as proxies, tunnels, digital cross connects, or even direct circuits, which separates 'bad' traffic (DDoS and also other common internet attacks) and only sends good traffic beyond to the server.

The provider needs central connectivity to the Internet to manage this kind of service unless they happen to be located within the same facility as the 'cleaning center' or 'scrubbing center'. Examples of providers of this service. • • • • • • • • • • • • Unintentional denial-of-service [ ] An unintentional denial-of-service can occur when a system ends up denied, not due to a deliberate attack by a single individual or group of individuals, but simply due to a sudden enormous spike in popularity. This can happen when an extremely popular website posts a prominent link to a second, less well-prepared site, for example, as part of a news story. The result is that a significant proportion of the primary site's regular users – potentially hundreds of thousands of people – click that link in the space of a few hours, having the same effect on the target website as a DDoS attack.

A VIPDoS is the same, but specifically when the link was posted by a celebrity. When in 2009, websites such as Google and Twitter slowed down or even crashed. Many sites' servers thought the requests were from a virus or spyware trying to cause a denial-of-service attack, warning users that their queries looked like 'automated requests from a or spyware application'. News sites and link sites – sites whose primary function is to provide links to interesting content elsewhere on the Internet – are most likely to cause this phenomenon. The canonical example is the when receiving traffic from. It is also known as 'the hug of death' and 'the effect'. Routers have also been known to create unintentional DoS attacks, as both and routers have overloaded NTP servers by flooding NTP servers without respecting the restrictions of client types or geographical limitations.

Similar unintentional denials-of-service can also occur via other media, e.g. When a URL is mentioned on television. If a server is being indexed by or another during peak periods of activity, or does not have a lot of available bandwidth while being indexed, it can also experience the effects of a DoS attack. [ ] Legal action has been taken in at least one such case. In 2006, sued: massive numbers of would-be youtube.com users accidentally typed the tube company's URL, utube.com. As a result, the tube company ended up having to spend large amounts of money on upgrading their bandwidth. The company appears to have taken advantage of the situation, with utube.com now containing ads for advertisement revenue.

In March 2014, after went missing, launched a service on which users could help search for the missing jet in satellite images. The response overwhelmed the company's servers. An unintentional denial-of-service may also result from a prescheduled event created by the website itself, as was the case of the in 2016.

[ ] This could be caused when a server provides some service at a specific time. This might be a university website setting the grades to be available where it will result in many more login requests at that time than any other. Side effects of attacks [ ] Backscatter [ ]. See also: and In computer network security, backscatter is a side-effect of a spoofed denial-of-service attack. In this kind of attack, the attacker spoofs (or forges) the source address in sent to the victim.

In general, the victim machine cannot distinguish between the spoofed packets and legitimate packets, so the victim responds to the spoofed packets as it normally would. These response packets are known as backscatter. If the attacker is spoofing source addresses randomly, the backscatter response packets from the victim will be sent back to random destinations.

This effect can be used by as indirect evidence of such attacks. The term 'backscatter analysis' refers to observing backscatter packets arriving at a statistically significant portion of the space to determine characteristics of DoS attacks and victims.

Casmate Pro Windows 7 Download more. Legality [ ]. See also: Many jurisdictions have laws under which denial-of-service attacks are illegal.

• In the US, denial-of-service attacks may be considered a federal crime under the with penalties that include years of imprisonment. The of the US handles cases of (D)DoS. • In countries, committing criminal denial-of-service attacks may, as a minimum, lead to arrest. The is unusual in that it specifically outlawed denial-of-service attacks and set a maximum penalty of 10 years in prison with the, which amended Section 3 of the. On January 7, 2013, on the site asking that DDoS be recognized as a legal form of protest similar to the, the claim being that the similarity in purpose of both are same. See also [ ]. • Ethan Zuckerman; Hal Roberts; Ryan McGrady; Jillian York; John Palfrey (December 2011).

The Berkman Center for Internet & Society at Harvard University. Archived from (PDF) on 2011-03-02. Retrieved 2011-03-02. Archived from on 2011-03-02. • External links [ ] • Internet Denial-of-Service Considerations • - Quarterly Security and Internet trend statistics • • CERT's Guide to DoS attacks. (historic document) • – Real-time global report of DDoS attacks. • - The Well Known Network Stress Testing Tool • - A Simple HTTP Flooder • An Attempt to Bring SlowLoris and Slow Network Tools on LOIC.

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