A Novel Approach to Develop and Deploy Preventive Measures for Different Types of DDoS Attacks

2020 ◽  
Vol 14 (2) ◽  
pp. 1-19
Author(s):  
Khundrakpam Johnson Singh ◽  
Janggunlun Haokip ◽  
Usham Sanjota Chanu
Keyword(s):  
Preventive Measures ◽  
Denial Of Service ◽  
External Environment ◽  
Distributed Denial Of Service ◽  
Ddos Attacks ◽  
New Era ◽  
Denial Of Service Attack ◽  
Novel Approach ◽  
Different Types ◽  
Service Attack

In the new era of computers, everyone relies on the internet for basic day-to-day activities to sophisticated and secret tasks. The cyber threats are increasing, not only theft and manipulation of someone's information, but also forcing the victim to deny other requests. A DDoS (Distributed Denial of Service) attack, which is one of the serious issues in today's cyber world needs to be detected and their advance towards the server should be blocked. In the article, the authors are focusing mainly on preventive measures of different types of DDoS attacks using multiple IPtables rules and Windows firewall advance security settings configuration, which would be feasibly free on any PC. The IPtables when appropriately selected and implemented can establish a relatively secure barrier for the system and the external environment.

scholarly journals Mathematical model on distributed denial of service attack through Internet of things in a network

2019 ◽  
Vol 8 (1) ◽  
pp. 486-495 ◽  
Author(s):  
Bimal Kumar Mishra ◽  
Ajit Kumar Keshri ◽  
Dheeresh Kumar Mallick ◽  
Binay Kumar Mishra
Keyword(s):  
Mathematical Model ◽  
Internet Of Things ◽  
Equilibrium Points ◽  
Denial Of Service ◽  
Distributed Denial Of Service ◽  
Ddos Attacks ◽  
Denial Of Service Attack ◽  
Different Types ◽  
Service Attack ◽  
Iot Devices

Abstract Internet of Things (IoT) opens up the possibility of agglomerations of different types of devices, Internet and human elements to provide extreme interconnectivity among them towards achieving a completely connected world of things. The mainstream adaptation of IoT technology and its widespread use has also opened up a whole new platform for cyber perpetrators mostly used for distributed denial of service (DDoS) attacks. In this paper, under the influence of internal and external nodes, a two - fold epidemic model is developed where attack on IoT devices is first achieved and then IoT based distributed attack of malicious objects on targeted resources in a network has been established. This model is mainly based on Mirai botnet made of IoT devices which came into the limelight with three major DDoS attacks in 2016. The model is analyzed at equilibrium points to find the conditions for their local and global stability. Impact of external nodes on the over-all model is critically analyzed. Numerical simulations are performed to validate the vitality of the model developed.

scholarly journals Shield Advanced Mitigation System of Distributed Denial of Service Attack in Integration of Internet of Things and Cloud Computing Environment

2019 ◽  
Vol 9 (2) ◽  
pp. 1300-1306
Keyword(s):  
Cloud Computing ◽  
Internet Of Things ◽  
Denial Of Service ◽  
Cloud Services ◽  
Distributed Denial Of Service ◽  
Ddos Attacks ◽  
Denial Of Service Attack ◽  
Ddos Attack ◽  
Service Attack ◽  
Verification Process

Cloud services among public and business companies have become popular in recent years. For production activities, many companies rely on cloud technology. Distributed Denial of Services (DDoS) attack is an extremely damaging general and critical type of cloud attacks. Several efforts have been made in recent years to identify numerous types of DDoS attacks. This paper discusses the different types of DDoS attacks and their cloud computing consequences. Distributed Denial of Service attack (DDoS) is a malicious attempt to disrupt the normal movement of a targeted server, service or network through influx of internet traffic overwhelming the target or its infrastructure. The use of multiple affected computer systems as a source of attacks makes DDoS attacks effective. Computers and other networked tools, including IoT phones, may be included on exploited machines. A DDoS attack from a high level resembles a traffic jam that is caused by roads that prevents normal travel at their desired destination. So DDoS Attack is a major challenging problem in integrated Cloud and IoT. Hence, this paper proposes Shield Advanced Mitigation System of Distributed Denial of Service Attack in the integration of Internet of Things and Cloud Computing Environment. This secure architecture use two verification process to identify whether user is legitimate or malicious. Dynamic Captcha Testing with Equal Probability test for first verification process, moreover Zigsaw Image Puzzle Test is used for second verification process, and Intrusion Detection Prevention System is used to identify and prevent malicious user, moreover reverse proxy is used to hide server location. These functional components and flow could strengthen security in Client side network to provide cloud services furthermore to overcome distributed denial of service attack in the integration of Internet of Things and Cloud Environment.

scholarly journals Multilevel Modeling of Distributed Denial of Service Attacks in Wireless Sensor Networks

2016 ◽  
Vol 2016 ◽  
pp. 1-13 ◽  
Author(s):  
Katarzyna Mazur ◽  
Bogdan Ksiezopolski ◽  
Radoslaw Nielek
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Denial Of Service ◽  
Monitoring Network ◽  
Wireless Sensor ◽  
Distributed Denial Of Service ◽  
Ddos Attacks ◽  
Denial Of Service Attack ◽  
Ddos Attack ◽  
Service Attack

The growing popularity of wireless sensor networks increases the risk of security attacks. One of the most common and dangerous types of attack that takes place these days in any electronic society is a distributed denial of service attack. Due to the resource constraint nature of mobile sensors, DDoS attacks have become a major threat to its stability. In this paper, we established a model of a structural health monitoring network, being disturbed by one of the most common types of DDoS attacks, the flooding attack. Through a set of simulations, we explore the scope of flood-based DDoS attack problem, assessing the performance and the lifetime of the network under the attack condition. To conduct our research, we utilized the Quality of Protection Modeling Language. With the proposed approach, it was possible to examine numerous network configurations, parameters, attack options, and scenarios. The results of the carefully performed multilevel analysis allowed us to identify a new kind of DDoS attack, the delayed distributed denial of service, by the authors, referred to as DDDoS attack. Multilevel approach to DDoS attack analysis confirmed that, examining endangered environments, it is significant to take into account many characteristics at once, just to not overlook any important aspect.

scholarly journals An New Efficient Cluster Based Detection Mechanisms for Distributed Denial of Services (DDoS) Attacks

2021 ◽  
Vol 15 ◽  
pp. 147-152
Author(s):  
K. Saravanan ◽  
R. Asokan
Keyword(s):  
Denial Of Service ◽  
Distributed Denial Of Service ◽  
Ddos Attacks ◽  
Host System ◽  
Denial Of Service Attack ◽  
Cluster Aggregation ◽  
The Core ◽  
Service Attack ◽  
Detection Mechanisms ◽  
Statistical Anomaly Detection

Cluster aggregation of statistical anomaly detection is a mechanism for defending against denial of service attack (dos) and distributed denial-of-service (DDoS) attacks. DDoS attacks are treated as a congestioncontrol problem; because most of the congestion is occurred in the malicious hosts not follow the normal endto- end congestion control. Upstream routers are also notified to drop such packets in order that the router’s resources are used to route legitimate traffic hence term cluster aggregation. If the victim suspects that the cluster aggregations are solved by most of the clients, it increases the complexity of the cluster aggregation. This aggregation solving technique allows the traversal of the attack traffic throughout the intermediate routers before reaching the destination. In this proposal, the aggregation solving mechanism is cluster aggregation to the core routers rather than having at the victim. The router based cluster aggregation mechanism checks the host system whether it is legitimate or not by providing a aggregation to be solved by the suspected host.

scholarly journals Optimal software-defined network topology for distributed denial of service attack mitigation

2020 ◽  
Vol 9 (6) ◽  
pp. 2588-2594
Author(s):  
Branislav Mladenov ◽  
Georgi Iliev
Keyword(s):  
Network Topology ◽  
Network Architecture ◽  
Denial Of Service ◽  
Distributed Denial Of Service ◽  
Ddos Attacks ◽  
Denial Of Service Attack ◽  
Optimal Network ◽  
Service Attack ◽  
Network Topologies ◽  
Sdn Controller

Distributed denial of service (DDoS) attacks are a major threat to all internet services. The main goal is to disrupt normal traffic and overwhelms the target. Software-defined networking (SDN) is a new type of network architecture where control and data plane are separated. A successful attack may block the SDN controller which may stop processing the new request and will lead to a total disruption of the whole network. The main goal of this paper is to find the optimal network topology and size which can handle Distributed denial of service attack without management channel bandwidth exhaustion or run out of SDN controller CPU and memory. Through simulations, it is shown that mesh topologies with more connections between switches are more resistant to DDoS attacks than liner type network topologies. 

scholarly journals The Slow HTTP Distributed Denial of Service Attack Detection in Cloud

2019 ◽  
Vol 20 (2) ◽  
pp. 285-298 ◽  
Author(s):  
A. Dhanapal ◽  
P. Nithyanandam
Keyword(s):  
Cloud Computing ◽  
Financial Services ◽  
Denial Of Service ◽  
Attack Detection ◽  
Distributed Denial Of Service ◽  
Ddos Attacks ◽  
Denial Of Service Attack ◽  
Ddos Attack ◽  
Service Attack ◽  
The Cost

Cloud computing became popular due to nature as it provides the flexibility to add or remove the resources on-demand basis. This also reduces the cost of investments for the enterprises significantly. The adoption of cloud computing is very high for enterprises running their online applications. The availability of online services is critical for businesses like financial services, e-commerce applications, etc. Though cloud provides availability, still these applications are having potential threats of going down due to the slow HTTP Distributed Denial of Service (DDoS) attack in the cloud. The slow HTTP attacks intention is to consume all the available server resources and make it unavailable to the real users. The slow HTTP DDoS attack comes with different formats such as slow HTTP headers attacks, slow HTTP body attacks and slow HTTP read attacks. Detecting the slow HTTP DDoS attacks in the cloud is very crucial to safeguard online cloud applications. This is a very interesting and challenging topic in DDoS as it mimics the slow network. This paper proposed a novel method to detect slow HTTP DDoS attacks in the cloud. The solution is implemented using the OpenStack cloud platform. The experiments conducted exhibits the accurate results on detecting the attacks at the early stages. The slowHTTPTest open source tool is used in this experiment to originate slow HTTP DDoS attacks.

scholarly journals Protection From Distributed Denial of Service Attack Using Fuzzy Logic

2021 ◽  
Author(s):  
Hemalatha S ◽  
Vasantha Gowri N ◽  
vani A ◽  
Sana Qaiyum ◽  
vijayakumar P ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Denial Of Service ◽  
Cloud Service ◽  
Detection Accuracy ◽  
Distributed Denial Of Service ◽  
Ddos Attacks ◽  
Denial Of Service Attack ◽  
Service Attack ◽  
Important Challenge ◽  
Set Up

Abstract Distributed Denial of Service (DDoS) attacks represent an important challenge for public cloud as they invade the offender and completely delete Cloud service in order to serve the correct user and at the same time against the targets that cause system and service lack of access on infected devices. DDoS (Distributed Denial of Service) attacks are usually specific efforts to drain the resources of the victim or interrupt connections to networks by legitimate users. Traditional internet infrastructure is susceptible to DDoS assaults, and through leveraging their flaws to set up assault networks or Botnets, it offers an opening for an intruder to reach a wide number of infected machines. In order to identify and sustain improved detection accuracy, this work focuses on evaluating the different works and recommending a better solution to accommodate the cloud environment. A fuzzy logic for the detection and safety of DDOS attacks is proposed in this paper. The Fuzzy logic is used to dynamically select an algorithm from a collection of defined supervised learning that distinguish various DDoS variations and ultimately choose the relevant traffic algorithm.

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