DDOS Attack

Since the last decade, Internet users increased rapidly and most of them are depending on the World Wide Web (WWW) service for achieving daily routine. Having Internet access and especially WWW sometimes users face difficulties because of various security problems. The most dangerous and serious threats that make Internet services impossible is Denial of Service (DoS) and its severe type ‘Distributed Denial of Service (DDoS)’. In this paper, the performance of different web servers in Network Load Balancing (NLB), cluster-based and none clustered are analyzed. Furthermore, we evaluate the impact of TCP SYN flood attack with massive concurrent HTTP load traffic on web server’s average response time, throughput and average CPU usage. The results show that Internet Information Service 10.0 (IIS10.0) on Windows server 2016 is more vulnerable to attacks compared to Apache2 on Ubuntu 16.04. The results also show that the IIS10.0 NLB clustered web servers is the most suitable mechanism for...

The essential services such as banking, transportation, medicine, education and defense are being progressively replaced by cheaper and more efficient Internet-based web applications. Therefore, the availability of Web services is very critical for the socio-economic growth of the society. Distributed denial-of-service (DDoS) attacks pose an immense threat to the availability of these services. The services are severely degraded and hence lot of business loses are incurred due to these attacks. To objectively evaluate DDoS attack's impact, its severity and the effectiveness of a potential defense, we need precise, quantitative and comprehensive DDoS impact metrics that are applicable to web services. In this paper an attempt has been made to analyze impact of DDoS attacks on the Web services. The experiments are conducted in NS-2. The attack traffic is mixed with legitimate traffic at different strengths and impact of DDoS attacks are measured in terms of throughput, response time, ratio of average serve to request rate, percentage link utilization, and normal packet survival ratio (NPSR). electronic document is a "live" template. The various components of your paper [title, text, heads, etc.] are already defined on the style sheet, as illustrated by the portions given in this document.

Nowadays, continuously accessing Internet services is vital for the most of people. However, due to Denial of Service (DoS) and its severe type ‘Distributed Denial of Service (DDoS), online services becomes unavailable to users in sometimes. Rather than DDoS is dangerous and has serious impact on the Internet consumers, there are multiple types of that attack such Slowrise, ping of death and UDP, ICMP, SYN flood, etc. In this paper, the effect of HTTP and SYN flood attack on the most recent and widely used web servers is studied and evaluated. Systematic performance analysis is performed on Internet Information Service 10.0 (IIS 10.0) on Windows server 2016 and Apache 2 on Linux Ubuntu 16.04 Long Term Support (LTS) server. Furthermore, the key metrics of the performance are average response time, average CPU usage and standard deviation as a responsiveness, efficiency and stability of the web servers. The results show that the IIS10.0 outperformed Apache2 web server in efficiency and responsiveness during HTTP flood attack. However, Apache2 web server achievement was more responsive and performed more stability with SYN flood attack.

Distributed Denial of Service (DDoS) attacks on the Internet are used by attackers to be a nuisance, make a political statement (e.g. the 2009 attack against Estonia), or as a weapon of an Internet extortionist. Effective defense against these is a crucial study area, where advanced simulation techniques play a critical role, because of the enormous number of events involved. This paper considers a methodology for evaluating a game-theoretic defense against DDoS. We first describe a basic form of the defense, note the performance limitations suffered by a naive implementation, and then consider methodologies in which a parallelized approach may accelerate performance.

Data security is an integral requirement of any modern information system as attackers are gaining chances due to the prompt improvement in digital technology. However, in the current decade, the use of cloud computing is rising steeply, and so is network traffic. As the cloud computing model is based on the distributed computing, cloud servers are widely distributed and cloud users can access the service from anywhere and at any time. This makes the cloud servers, a target for the adversaries. The most common attack in a cloud environment is the DDoS attack that causes bulky and abnormal traffic to the cloud server. The cloud server is incapable to manage such unusual traffic and stops momentarily by making the server down with excessive traffic. DDoS attacks can be avoided by diligent traffic control prior to the DDoS attack. This paper proposes a novel three-layer filtering mechanism to prevent various forms of DDoS attacks. The first layer of the proposed DDoS attack prevention mechanism uses two-level authentication processes. Second layer filtering verifies whether the user accesses the resources within the pre-defined limits and the third layer filtering sieves out the spoofed packets. The proposed model has been analyzed for evaluating the performance in terms of CPU overhead and load, the throughput of the victim, the reduction in connection delay. The result analysis shows that the proposed model has improved performance with a higher detection rate of 0.92 and a lower dropout rate of 0.10.

This paper gives the idea of Vulnerabilities present in protocols, Also detail study of DoS attacks and the scenario of how DoS attacks can happen on internet its defence mechanisms. There are many solutions proposed by many author to avoid DoS and DDoS attacks and that are discussed in this paper. This paper provides classification of attacks, and the defence mechanisms that can be used to detect the DDoS and DoS attack.

A denial-of-service attack (DDoS) is one that seeks to prevent computer machines from executing their functions properly; for example, a distributed denial of service assault involves rogue nodes flooding a network with unrelated data. As a result, the host or server will deny the access. We will conduct a study of certain studies that covered issues related to the detection of denial-of-service attacks in this paper. Although many papers have been produced in this subject, we will concentrate our efforts on the most recent ones. After analyzing several articles and the detection strategies employed in those publications, as well as how they work, we classify those techniques into groups and provide a table of comparisons for each category.
    Distributed denial-of-service (DDoS) is a rapidly growing problem. The multitude and variety of both the attacks and the defense approaches is overwhelming. This paper presents two taxonomies for classifying attacks and defenses, and thus provides researchers with a better understanding of the problem and the current solution space. The attack classification criteria was selected to highlight common and important features of attack strategies, that define challenges and dictate the design of countermeasures. The defense taxonomy classifies the body of existing DDoS defenses based on their design decisions; it then shows how these decisions dictate the advantages and deficiencies of proposed solutions. The main contributions are the process of combining appropriate measures and cyber safety protection causes and understanding which technology details of this.
    Keywords:  Denial-of-service; Types of DDoS attack; Distributed denial-of-service; Risk Assessment; Internet of Things botnet.

Several IP Traceback schemes employing packet marking have been proposed to trace DoS/DDoS attacks that use source address spoofing. The major challenges in the design of an efficient traceback technique are to minimize the number of packets required for successful traceback, and also to reduce the number of bits marked per packet by any router along the attack path. We propose a graph-coloring approach here that specifically addresses these issues. We propose to view the deployment of the traceback-enabled routers as an Internet Traceback Overlay Network, which not only provides easy scalability and incremental deployment, but also allows for the spatial reuse of the router labels used for packet marking, directly resulting in a reduced bit-space, and hence in fewer packets required for successful traceback. We additionally propose an enhanced (logical) partitioned coloring technique to achieve an order of magnitude improvement over the best known schemes today. We also propose a 2-tier architecture that provides greater incentives for deployment to different ISP networks worldwide. We analyze the proposed techniques using real Internet AS-level topologies obtained from various sources.

The entire network is doing paradigm shift towards the software-defined networks by separating forwarding plane from control plane. This gives a clear call to researchers for joining the ocean of software-defined networks for doing research considering its security aspects. The biggest advantage of SDN is programmability of the forwarding plane. By making the switches programmable, it can take live instructions from controllers. The versions of OpenFlow protocol and the compatibility of programmable switches with OpenFlow were the stepping stone making software-defined networks thrashed towards reality. The control plane has come up with multiple options of controllers such as NOX [2], Ryu [3], Floodlight [4], OpenDayLight [6], ONOS [7] and the list is big. The major players are Java based which keeps the doors open for enhancement of features by the contributors. However, more is expected from the practicality of P4Lang programmed switches by bringing skilled people to the industry...

DDoS threats have been around ever since the Internet took over half of global communications, posing the real problem of denial of access to online service providers. Recently, a new trend has emerged in non-Windows DDoS attacks that has been induced by code availability, lack of security and an abundance of resources. The attack infrastructure has undergone signifi cant changes in structure, function and complexity. Malware has evolved into complex and relatively sophisticated pieces of code, employing compression, advanced encryption and even rootkit capabilities. Targeted machines are those running systems supporting the ELF format-anything from desktops and servers to IoT devices such as routers or digital video recorders (DVRs) could be at risk. In this paper, we will look at the current state of DDoS trojans forming covert botnets on unsuspecting systems. A technical analysis of the most important malware families will be provided, with a specific focus on infection methods, dynamic behaviour, C&C communication, obfuscation techniques, advanced methods of persistence and stealth, and elimination of rivals. We will study cybercriminals' behaviour and introduce their operation tools, including vulnerability scanners, brute-forcers, bot builders and C&C panels. In many cases, it's unnecessary to apply reverse engineering within the analysis-the original source codes are indexed in public search engines and their customisation is a subject of monetisation. Finally, we will discuss tracking methods and techniques and reveal the targets of these attacks.

Internet was designed for network services without any intention for secure communication. Exponential growth of internet and its users have developed an era of global competition and rivalry. Denial of service attack by multiple nodes is capable of disturbing the services of rival servers. The attack can be for multiple reasons e. g. extortion or to beat the rivals. Peer

In recent years, the rise of software-defined networks (SDN) have made network control more flexible, easier to set up and manage, and have provided a stronger ability to adapt to the changing demands of application development and network conditions. The network becomes easier to maintain, but also achieves improved security as a result of SDN. The architecture of SDN is designed for Control Plane and Forwarding Plane separation and uses open APIs to realize programmable control. SDN allows for the importing of third-party applications to improve network service, or even provide a new network service. In this paper, we present a defense mechanism, which can find attack packets previously identified through the Sniffer function, and once the abnormal flow is found, the protection mechanism of the Firewall function will be activated. For the capture of the packets, available libraries will be used to determine the properties and contents of the malicious packet, and to anticipate any possible attacks. Through the prediction of all latent malicious behaviors, our new defense algorithm can prevent potential losses like system failures or crashes and reduce the risk of being attacked.

In today's world of computer security, internei attacks such as DodDDos, worms, and spyware continue to cvolve as detection techniques improve. It is not easy, however, to disfinguish such new attacks using on/y knowledge of preexisling attacks. I n this puper we concentrate on machine learning techniques for delecling affacks from internet anomalies. Our machine ieqrning framework consists of two major components: Genetic Algorithm (GA) for feature selection and Support Vector Machine (SVM} for packet classi/icaiioion. By experiment we also demonstrate that our proposed framework oui performs currently employed realworld M D S .

Denial of Service (DoS) attacks constitute one of the major threats and among the hardest security problems in todayÕs Internet. Of particular concern are Distributed Denial of Service (DDoS) attacks, whose impact can be proportionally severe. With little or no advance warning, a DDoS attack can easily exhaust the computing and communication resources of its victim within a short period of time. Because of the seriousness of the problem many defense mechanisms have been proposed to combat these attacks. This paper presents a structural approach to the DDoS problem by developing a classification of DDoS attacks and DDoS defense mechanisms. Furthermore, important features of each attack and defense system category are described and advantages and disadvantages of each proposed scheme are outlined. The goal of the paper is to place some order into the existing attack and defense mechanisms, so that a better understanding of DDoS attacks can be achieved and subsequently more efficient and effective algorithms, techniques and procedures to combat these attacks may be developed.

Internet has become an important part of our everyday life. We use services like Netflix, Skype, online banking and Scopus etc. daily. We even use Internet for filing our tax returns and communicating with municipalities. This dependency on network-based technologies provides an opportunity to malicious actors in our society to remotely attack IT infrastructure. One type of cyberattack that may lead to unavailability of network resources is known as distributed denial of service (DDoS) attack. A DDoS attack leverages many computers to launch a coordinated Denial of Service attack against one or more targets.

These attacks cause damages to victim businesses. According to reports published by several consultancies and security companies these attacks lead to millions of dollars in losses every year. One might ponder: are the damages caused by temporary unavailability of network services really this large? One of the points of criticism for these reports has been that they often base their findings on victim surveys and expert opinions. Now, as cost accounting/book keeping methods are not focused on measuring the impact of cyber security incidents, it is highly likely that surveys are unable to capture the true impact of an attack. A troubling fact is that most C-level managers make budgetary decisions for security based on the losses reported in these surveys. Several inputs for security investment decision models such as return on security investment (ROSI) also depend on these figures. This makes the situation very similar to the parable of the blind men and the elephant, in which several blind men try to conceptualise how the elephant looks like by touching it. Hence, it is important to develop methodologies that capture the true impact of DDoS attacks. In this thesis, we study the economic impact of DDoS attacks on public/private organisations by using an empirical approach.

In Chapter 1 we explain the motivation for our work and illustrate the problems associated with measuring the economic impacts of DDoS attacks. We then formulate our main research question and break it down into sub-questions that we investigate in later chapters. We state our main research question as follows:

What are the economic impacts of DDoS attacks on public/private organisations?

Our first contribution is identifying the main stakeholders in a DDoS attack. In Chapter 2, we discuss the evolution of DDoS attacks in the last decade and briefly describe the strategies adopted by attackers and defenders. By studying the business model of a botnet, we also analyse how DDoS attacks can be used by attackers for monetary gains.

Our second contribution is to develop methodologies to capture the direct impact of DDoS attacks. In Chapters 3 and 4 we measure the direct consequences of DDoS attacks on large managed domain name service (DNS) providers and a cryptocurrency exchange respectively. We find that a successful DDoS attack on a managed DNS service provider, changes the security behaviour of its customers. In the case of cryptocurrency exchange we find that the losses are recovered very quickly, on most instances even within a single day. We show how longitudinal datasets can be used to asses the impacts.

The third contribution of this thesis is to develop methodologies to measure the indirect consequences of DDoS attacks. In Chapter 5, we propose a more robust event study approach and use it to analyse the impact of DDoS attack announcements on victims' stock prices. We find that in most cases this impact is short lived (5-10 days). In Chapter 6, we introduce a dataset based on web articles on DDoS attacks which captures the social context of an attack. We show how machine learning algorithms can be used to filter news articles that are reporting a DDoS attack from the dataset.

We recognise that it is not possible to measure the true impact of DDoS attacks on the victim without learning about the aims of attackers. In Chapter 7, we propose a model based on Routine Activity Theory (RAT) to study attacker's aims by using the information about the attack reported in the news articles. Later in Chapter 8, we show how postulates of RAT may be used to explain DDoS attack trends on educational institutions.

Our results show that DDoS attacks are not a random phenomenon and attackers are instigated by the circumstances surrounding them. We observe that measuring the true economic impact of these attacks is complex and requires us to consider the context of an attack. Some of the consequences of short duration IT unavailability are temporary and they are recovered rather quickly. Hence, to take this work forward we propose to give economic meaning to the empirical data that is presently available and collect more data at employee level to measure the resilience of firms towards IT unavailability.

Security network systems have been an increasingly important discipline since the implementation of preliminary stages of Internet Protocol version 6 (IPv6) for exploiting by attackers. IPv6 has an improved protocol in terms of security as it brought new functionalities, procedures, i.e., Internet Control Message Protocol version 6 (ICMPv6). The ICMPv6 protocol is considered to be very important and represents the backbone of the IPv6, which is also responsible to send and receive messages in IPv6. However, IPv6 Inherited many attacks from the previous internet protocol version 4 (IPv4) such as distributed denial of service (DDoS) attacks. DDoS is a thorny problem on the internet, being one of the most prominent attacks affecting a network result in tremendous economic damage to individuals as well as organizations. In this paper, an exhaustive evaluation and analysis are conducted anomaly detection DDoS attacks against ICMPv6 messages, in addition, explained anomaly detection types to ICMPv6 DDoS flooding attacks in IPv6 networks. Proposed using feature selection technique based on bio-inspired algorithms for selecting an optimal solution which selects subset to have a positive impact of the detection accuracy ICMPv6 DDoS attack. The review outlines the features and protection constraints of IPv6 intrusion detection systems focusing mainly on DDoS attacks.

This is analysis of China’s “Great Cannon,” our term for an attack tool that we identify as separate from, but co-located with, the Great Firewall of China. The first known usage of the Great Cannon is in the recent large-scale novel DDoS attack on both GitHub and servers used by GreatFire.org.

Distributed Denial of Service (DDoS) attacks in the networks needs to be prevented or handled if it occurs, as early as possible and before reaching the victim. Dealing with DDoS attacks is difficult due to their properties such as dynamic attack rates, various kinds of targets, big scale of botnet, etc. Distributed Denial of Service (DDoS) attack is hard to deal with because it is difficult to distinguish legitimate traffic from malicious traffic, especially when the traffic is coming at a different rate from distributed sources. DDoS attack becomes more difficult to handle if it occurs in wireless network because of the properties of ad hoc network such as dynamic topologies, low battery life, multicast routing, frequency of updates or network overhead, scalability, mobile agent based routing, and power aware routing, etc. Therefore, it is better to prevent the distributed denial of service attack rather than allowing it to occur and then taking the necessary steps to handle it. This paper discusses various the attack mechanisms and problems due to DDoS attack, also how MANET can be affected by these attacks. In addition to this, a novel solution is proposed to handle DDoS attacks in mobile ad hoc networks (MANETs).

 Abstract-The term denial of Service (DOS) refers to form an attacking computers over a network. The denial of service attack is an explicit attempt by an attacker to prevent the legitimate users not to access the services. When this attack is made at a larger amount that is by using multiple computers than it's known as Distributed Denial of Service Attack (DDoS) [1]. An attacker can use many techniques for denial of service like flooding technique is to flood a network and reduce the legitimate user bandwidths to disrupt the services of the users. In DDoS attack, the attacker try to interrupt the services of a server and utilizes its CPU and Network. Flooding DDOS attack is based on a huge volume of attack traffic which is termed as a Flooding based DDOS attack. Flooding-based DDOS attack attempts to congest the victim's network bandwidth with real-looking but unwanted IP data. Due to which Legitimate IP packets cannot reach the victim because of lack of bandwidth resource [5]. ICMP FLOOD initiated by sending a large number of ICMP packets to a remote host. As a result, the victimized system's resources will be consumed with handling the attacking packets, which eventually causes the system to be unreachable by other clients. In this reserach firstly, we detect the ICMP Flood by using various methods and tools and then find out the prevention techniques for DDOS attack using ICMP Protocol.

With the increased dependence of organizations on technological solutions, the cyber threats have become some of the major concerns for the very existence of the businesses. Thus, the security measures to be implemented need to go beyond a simple presence of a firewall and anti-malware. In this work, an overview of two Intrusion Detection and Prevention systems (IDPS) was performed. Namely, the architecture of Snort and Suricata IDPS engines was discussed.

Pushback is a mechanism for defending against Distributed Denial-of-Service (DDoS) attacks. DDoS attacks are treated as a congestion-control problem, but because most such congestion is caused by malicious hosts not obeying traditional end-to-end congestion control, the problem must be handled by the routers. Functionality is added to each router to detect and preferentially drop packets that probably belong to an attack. Upstream routers are also notified to drop such packets in order that the router's resources be used to route legitimate traffic hence term pushback. Client puzzles have been advocated as a promising countermeasure to DoS attacks in the recent years. In order to identify the attackers, the victim server issues a puzzle to the client that sent the traffic. When the client is able to solve the puzzle, it is assumed to be authentic and the traffic from it is allowed into the server. If the victim suspects that the puzzles are solved by most of the clients, it increases the complexity of the puzzles. This puzzle solving technique allows the traversal of the attack traffic throughout the intermediate routers before reaching the destination. In order to attain the advantages of both pushback and puzzle solving techniques, a hybrid scheme called Router based Pushback technique, which involves both the techniques to solve the problem of DDoS attacks is proposed. In this proposal, the puzzle solving mechanism is pushed back to the core routers rather than having at the victim. The router based client puzzle mechanism checks the host system whether it is legitimate or not by providing a puzzle to be solved by the suspected host.

Abstract—We investigate the stability properties of a novel agent-based system for the detection of network bandwidth-based distributed denial of service (DDoS) attacks. The pro-posed system provides a description of the structure of flows which comprise the DDoS attack. In doing ...

The Internet is developing dangerously, as is the number of crimes committed against or utilizing computers. Hence, there arises the need for Cyber security. Cyber security is one of the most important parts in the field of information technology. As we think about Cyber security, first thing which comes to our minds is the increasing number of cyber-crimes. Governments around the world are taking steps to prevent these cyber-crimes. This paper focuses mainly on the problems and obstacles created by cyber-crimes. It also points out the ongoing trends about cyber security.

In order to control the request flow in Computer Networks, a proxy server is used. Proxy Server is a server which acts as an intermediary server between server and clients. The more adaptable and converted attack is Web proxy-based HTTP attack in the existing DDoS attacks. In most of the large-scale official proxies which are usually configured to have high security sometimes cannot avoid being abused for the proxy base attacks. This type of attacks introduces new challenges to the existing security systems of the network. Web application is a set of technologies which serves for the web service. It is a good security practice to implement additional precautions to every mitigation level including the web application level for bringing the HTTP flood attack awareness for the web application. Here we introduce the detection and prevention of these flood attacks and DDoS attacks by using their frequency of request sequence arrival.

... like attacks like Smurf and TCP-SYN uses Rahul Chowdary Bobba(B.Tech), Raghunath. ... San Diego, Jan 2004. [9] HR Nagesh, Chandra Sekaran K. Department of Computer Engineering, PA College of Engineering, Mangalore, Karnataka, INDIA Department of Computer ...

Clouds are distributed Internet-based platforms that provide highly resilient and scalable environments to be used by enterprises in a multitude of ways. Cloud computing offers enterprises technology innovation that business leaders and IT infrastructure managers can choose to apply based on how and to what extent it helps them fulfil their business requirements. It is crucial that all technical consultants have a rigorous understanding of the ramifications of cloud computing as its influence is likely to spread the complete IT landscape. Security is one of the major concerns that is of practical interest to decision makers when they are making critical strategic operational decisions. Distributed Denial of Service (DDoS) attacks are becoming more frequent and effective over the past few years, since the widely publicised DDoS attacks on the financial services industry that came to light in September and October 2012 and resurfaced in the past two years. In this paper, we introduce advanced cloud security technologies and practices as a series of concepts and technology architectures, from an industry-centric point of view. This is followed by classification of intrusion detection and prevention mechanisms that can be part of an overall strategy to help understand identify and mitigate potential DDoS attacks on business networks. The paper establishes solid coverage of security issues related to DDoS and virtualisation with a focus on structure, clarity, and well-defined blocks for mainstream cloud computing security solutions and platforms. In doing so, we aim to provide industry technologists, who may not be necessarily cloud or security experts, with an effective tool to help them understand the security implications associated with cloud adoption in their transition towards more knowledge-based systems.

Numerous attacks are performed on network infrastructures. These include attacks on network availability, confidentiality and integrity. Distributed denial-of-service (DDoS) attack is a persistent attack which affects the availability of the network. Command and Control (C & C) mechanism is used to perform such kind of attack. Various researchers have proposed different methods based on machine learning technique to detect these attacks. In this paper, DDoS attack was performed using ping of death technique and detected using machine learning technique by using WEKA tool. NSL-KDD dataset was used in this experiment. Random forest algorithm was used to perform classification of the normal and attack samples. 99.76% of the samples were correctly classified.

One of the most serious threat to network security is Denial of service (DOS) attacks. When this attack is performed in distributed manner it can create more disaster. Lot of research has been carried for the detection of this attack. In this various techniques has been studied and discussed. Primary focus was given to machine learning and deep learning techniques.

Abstract: Most of people across the world accesses Internet-based applications and web services in their daily activities. Distributed Denial of Service (DDoS) attack is one of the well-known attacks that crush the computing and communication resources of a web server hosting these applications and services. It often leads to huge financial losses, and thus, involves timely actions. This paper presents a case study of the WEKA tool that can be used to analyze the different types of networks to differentiate legitimate traffic from attack traffic. WEKA is based on machine learning and is an effective tool used for data mining.

Nowadays, continuously accessing Internet services is vital for the most of people. However, due to Denial of Service (DoS) and its severe type 'Distributed Denial of Service (DDoS), online services becomes unavailable to users in sometimes. Rather than DDoS is dangerous and has serious impact on the Internet consumers, there are multiple types of that attack such Slowrise, ping of death and UDP, ICMP, SYN flood, etc. In this paper, the effect of HTTP and SYN flood attack on the most recent and widely used web servers is studied and evaluated. Systematic performance analysis is performed on Internet Information Service 10.0 (IIS 10.0) on Windows server 2016 and Apache 2 on Linux Ubuntu 16.04 Long Term Support (LTS) server. Furthermore, the key metrics of the performance are average response time, average CPU usage and standard deviation as a responsiveness, efficiency and stability of the web servers. The results show that the IIS10.0 outperformed Apache2 web server in efficiency and responsiveness during HTTP flood attack. However, Apache2 web server achievement was more responsive and performed more stability with SYN flood attack. Keywords-DoS, DDoS, HTTP flood attack, SYN flood attack and Web server performance analysis

Denial of Service (DoS) attacks constitute one of the major threats and among the hardest security problems in todayÕs Internet. Of particular concern are Distributed Denial of Service (DDoS) attacks, whose impact can be proportionally severe. With little or no advance warning, a DDoS attack can easily exhaust the computing and communication resources of its victim within a short period of time. Because of the seriousness of the problem many defense mechanisms have been proposed to combat these attacks. This paper presents a structural approach to the DDoS problem by developing a classification of DDoS attacks and DDoS defense mechanisms. Furthermore, important features of each attack and defense system category are described and advantages and disadvantages of each proposed scheme are outlined. The goal of the paper is to place some order into the existing attack and defense mechanisms, so that a better understanding of DDoS attacks can be achieved and subsequently more efficient and effective algorithms, techniques and procedures to combat these attacks may be developed.

Distributed Denial of Service attack is a coordinated attack, generally performed on a massive scale on the availability of services of a target system or network resources. Due to the continuous evolution of new attacks and ever-increasing number of vulnerable hosts on the Internet, many DDoS attack detection or prevention mechanisms have been proposed.

This paper describes an approach to detecting distributed denial of service (DDoS) attacks that is based on fundamentals of Information Theory, specifically Kolmogorov Complexity. A theorem derived using principles of Kolmogorov Complexity states that the joint complexity measure of random strings is lower than the sum of the complexities of the individual strings when the strings exhibit some correlation. Furthermore, the joint complexity measure varies inversely with the amount of correlation. We propose a distributed active network-based algorithm that exploits this property to correlate arbitrary traffic flows in the network to detect possible denial-of-service attacks. One of the strengths of this algorithm is that it does not require special filtering rules and hence it can be used to detect any type of DDoS attack. We implement and investigate the performance of the algorithm in an active network. Our results show that DDoS attacks can be detected in a manner that is not sensitive to legitimate background traffic.

Many Cloud Service Providers (CSP) offer access to scalable, reliable computing resources following a pay- as-you-go model. Research into security of the Cloud focusses mainly on protecting legitimate users of Cloud services from attacks by external, malicious users. Little attention is given to prohibit malicious users from using the Cloud to launch attacks, such as those currently done by botnets.

This article provides an analysis of the problematic of foresight in traditional Chinese thought, articulating it with current developments in the epistemology of futures studies, planning theory, and strategic management. It is argued that in Chinese thought the answer to the question " Can the future be predicted? " depends on the forecasting horizon: whereas the immediate future can be sensed and taken advantage of by immersing oneself in the evolving situation, the remote future is fundamentally unpredictable. These dual answers are entrenched in discussions of what constitutes wisdom, opening up productive spaces of encounter between the problematic of foresight and the problematic of wisdom. https://doi.org/10.6531/JFS.2018.22(3).00A35

Modbus is the de facto standard communication protocol for the industrial world. It was initially designed to be used in serial communications (Modbus RTU/ASCII). However, not long ago, it was adapted to TCP due to the increasing popularity of the TCP/IP stack. Since it was originally designed for controlled serial lines, Modbus does not have any security features. In this paper, we wrote several benchmarks to evaluate the performance of networking devices that run Modbus TCP. Parameters reported by our benchmarks include: (1) response time for Modbus requests, (2) maximum number of requests successfully handled by Modbus devices in a specific amount of time, and (3) monitoring of Modbus devices when suffering a Distributed Denial of Service attack. Due to the growing adoption of IoT technologies, we also selected two widely known and inexpensive development boards (ESP8266 and Raspberry Pi 3 B+/OpenPLC) to realize a performance evaluation of Modbus TCP.

The increasing popularity of web-based applications has led to several critical services being provided over the Internet. This has made it imperative to monitor the network traffic so as to prevent malicious attackers from depleting the resources of the network and denying services to legitimate users. This paper has presented a mechanism for protecting a web-server against a distributed denial of service (DDoS) attack. Incoming traffic to the server is continuously monitored and any abnormal rise in the inbound traffic is immediately detected. The detection algorithm is based on a statistical analysis of the inbound traffic on the server and a robust hypothesis testing framework. While the detection process is on, the sessions from the legitimate sources are not disrupted and the load on the server is restored to the normal level by blocking the traffic from the attacking sources. To cater to different scenarios, the detection algorithm has various modules with varying level of co...

The main issues of the Intrusion Detection Systems (IDS) are in the sensitivity of these systems toward the errors, the inconsistent and inequitable ways in which the evaluation processes of these systems were often performed. Most of the previous efforts concerned with improving the overall accuracy of these models via increasing the detection rate and decreasing the false alarm which is an important issue. Machine Learning (ML) algorithms can classify all or most of the records of the minor classes to one of the main classes with negligible impact on performance. The riskiness of the threats caused by the small classes and the shortcoming of the previous efforts were used to address this issue, in addition to the need for improving the performance of the IDSs were the motivations for this work. In this paper, stratified sampling method and different cost-function schemes were consolidated with Extreme Learning Machine (ELM) method with Kernels, Activation Functions to build competitive ID solutions that improved the performance of these systems and reduced the occurrence of the accuracy paradox problem. The main experiments were performed using the UNB ISCX2012 dataset. The experimental results of the UNB ISCX2012 dataset showed that ELM models with polynomial function outperform other models in overall accuracy, recall, and F-score. Also, it competed with traditional model in Normal, DoS and SSH classes.

Botnets have evolved to become one of the most serious threats to the Internet and there is substantial research on both botnets and botnet detection techniques.  This analysis reviewed the history of botnets and botnet detection techniques. The analysis showed traditional botnet detection techniques rely on passive techniques, primarily honeypots, and that honeypots are not effective at detecting peer-to-peer and other decentralized botnets. Furthermore, the detection techniques aimed at decentralized and peer-to-peer botnets focus on detecting communications between the infected bots.  However, the increased use of obfuscation and encryption has significantly impacted the ability to detect botnet communications.

Wireless Mobile ad-hoc network (MANET) is an emerging technology and have great strength to be applied in critical situations like battlefields and commercial applications such as building, traffic surveillance, MANET is infrastructure less, with no any centralized controller exist and also each node contain routing capability, Each device in a MANET is independently free to move in any direction, and will therefore change its connections to other devices frequently. So one of the major challenges wireless mobile ad-hoc networks face today is security, because no central controller exists. MANETs are a kind of wireless ad hoc networks that usually has a routable networking environment on top of a link layer ad hoc network. Ad hoc also contains wireless sensor network so the problems is facing by sensor network is also faced by MANET. While developing the sensor nodes in unattended environment increases the chances of various attacks. There are many security attacks in MANET and DDoS (Distributed denial of service) is one of them. Our main aim is seeing the effect of DDoS in routing load, packet drop rate, end to end delay, i.e. maximizing due to attack on network. And with these parameters and many more also we build secure IDS to detect this kind of attack and block it. In this paper we discussed some attacks on MANET and DDOS also and provide the security against the DDOS attack.

Citation/Export MLA Sagar D. Pande, Prof. Ajay B. Gadicha, “Prevention Mechanism on DDOS Attacks by using Multilevel Filtering of Distributed Firewalls”, March 15 Volume 3 Issue 3 , International Journal on Recent and Innovation Trends in Computing and Communication (IJRITCC), ISSN: 2321-8169, PP: 1005 - 1008, DOI: 10.17762/ijritcc2321-8169.150323 APA Sagar D. Pande, Prof. Ajay B. Gadicha, March 15 Volume 3 Issue 3, “Prevention Mechanism on DDOS Attacks by using Multilevel Filtering of Distributed Firewalls”, International Journal on Recent and Innovation Trends in Computing and Communication (IJRITCC), ISSN: 2321-8169, PP: 1005 - 1008, DOI: 10.17762/ijritcc2321-8169.150323

Network. At the same time, its commercial nature is causing increase vulnerability to enhance cyber crimes and there has been an enormous increase in the number of DDOS (distributed denial of service attack) attacks on the internet over the past decade. Network resources such as network bandwidth, web servers and network switches are mostly the victims of DDoS attacks.

Distributed denial-of-service (DDoS) is a rapidly growing problem. The multitude and variety of both the attacks and the defense approaches is overwhelming. This paper presents two taxonomies for classifying attacks and defenses, and thus provides researchers with a better understanding of the problem and the current solution space. The attack classification criteria was selected to highlight commonalities and important features of attack strategies, that define challenges and dictate the design of countermeasures. The defense taxonomy classifies the body of existing DDoS defenses based on their design decisions; it then shows how these decisions dictate the advantages and deficiencies of proposed solutions.