scholarly journals Survey of Countering DoS/DDoS Attacks on SIP Based VoIP Networks

Electronics ◽  
2020 ◽  
Vol 9 (11) ◽  
pp. 1827
Author(s):  
Waleed Nazih ◽  
Wail S. Elkilani ◽  
Habib Dhahri ◽  
Tamer Abdelkader
Keyword(s):  
Low Cost ◽  
Denial Of Service ◽  
Voice Over Ip ◽  
Session Initiation Protocol ◽  
Future Research ◽  
Distributed Denial Of Service ◽  
Ddos Attacks ◽  
Voip Services

Voice over IP (VoIP) services hold promise because of their offered features and low cost. Most VoIP networks depend on the Session Initiation Protocol (SIP) to handle signaling functions. The SIP is a text-based protocol that is vulnerable to many attacks. Denial of Service (DoS) and distributed denial of service (DDoS) attacks are the most harmful types of attacks, because they drain VoIP resources and render SIP service unavailable to legitimate users. In this paper, we present recently introduced approaches to detect DoS and DDoS attacks, and classify them based on various factors. We then analyze these approaches according to various characteristics; furthermore, we investigate the main strengths and weaknesses of these approaches. Finally, we provide some remarks for enhancing the surveyed approaches and highlight directions for future research to build effective detection solutions.

Towards Utilizing Blockchain for Countering Distributed Denial-of-Service (DDoS)

2021 ◽  
pp. 35-58
Author(s):  
Rochak Swami ◽  
Mayank Dave ◽  
Virender Ranga ◽  
Nikhil Tripathi ◽  
Abhijith Kalayil Shaji ◽  
...  
Keyword(s):  
Cyber Security ◽  
Defense Mechanisms ◽  
Denial Of Service ◽  
Future Research ◽  
Distributed Denial Of Service ◽  
Ddos Attacks ◽  
Research Directions ◽  
Network Bandwidth ◽  
Future Research Directions ◽  
Network Administrators

Distributed denial of service (DDoS) attacks have been a matter of serious concern for network administrators in the last two decades. These attacks target the resources such as memory, CPU cycles, and network bandwidth in order to make them unavailable for the benign users, thereby violating availability, one of the components of cyber security. With the existence of DDoS-as-a-service on internet, DDoS attacks have now become more lucrative for the adversaries to target a potential victim. In this work, the authors focus on countering DDoS attacks using one of the latest technologies called blockchain. In inception phase, utilizing blockchain for countering DDoS attacks has proved to be quite promising. The authors also compare existing blockchain-based defense mechanisms to counter DDoS attacks and analyze them. Towards the end of the work, they also discuss possible future research directions in this domain.

scholarly journals DDoS Flood and Destination Service Changing Sensor

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 1980
Author(s):  
Fu-Hau Hsu ◽  
Chia-Hao Lee ◽  
Chun-Yi Wang ◽  
Rui-Yi Hung ◽  
YungYu Zhuang
Keyword(s):  
Operating System ◽  
Network Architecture ◽  
Transmission Control Protocol ◽  
Low Cost ◽  
Denial Of Service ◽  
Attack Detection ◽  
System Call ◽  
Distributed Denial Of Service ◽  
Ddos Attacks ◽  
Detection Mechanism

In this paper, we aim to detect distributed denial of service (DDoS) attacks, and receive a notification of destination service, changing immediately, without the additional efforts of other modules. We designed a kernel-based mechanism to build a new Transmission Control Protocol/Internet Protocol (TCP/IP) connection smartly by the host while the users or clients not knowing the location of the next host. Moreover, we built a lightweight flooding attack detection mechanism in the user mode of an operating system. Given that reinstalling a modified operating system on each client is not realistic, we managed to replace the entry of the system call table with a customized sys_connect. An effective defense depends on fine detection and defensive procedures. In according with our experiments, this novel mechanism can detect flooding DDoS successfully, including SYN flood and ICMP flood. Furthermore, through cooperating with a specific low cost network architecture, the mechanism can help to defend DDoS attacks effectively.

HULK and DDoS Attacks in Web Applications with Detection Mechanism

2018 ◽  
Vol 6 (6) ◽  
pp. 192
Author(s):  
Amit Sharma
Keyword(s):  
Web Applications ◽  
Denial Of Service ◽  
Single Server ◽  
Distributed Denial Of Service ◽  
Ddos Attacks ◽  
Application Layer ◽  
Detection Mechanism ◽  
Plan Execution ◽  
Social Affair ◽  
Server Application

Distributed Denial of Service attacks are significant dangers these days over web applications and web administrations. These assaults pushing ahead towards application layer to procure furthermore, squander most extreme CPU cycles. By asking for assets from web benefits in gigantic sum utilizing quick fire of solicitations, assailant robotized programs use all the capacity of handling of single server application or circulated environment application. The periods of the plan execution is client conduct checking and identification. In to beginning with stage by social affair the data of client conduct and computing individual user’s trust score will happen and Entropy of a similar client will be ascertained. HTTP Unbearable Load King (HULK) attacks are also evaluated. In light of first stage, in recognition stage, variety in entropy will be watched and malevolent clients will be recognized. Rate limiter is additionally acquainted with stop or downsize serving the noxious clients. This paper introduces the FAÇADE layer for discovery also, hindering the unapproved client from assaulting the framework.

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 Reducing distributed denial of service (DDoS) attacks using client puzzle mechanism

2017 ◽  
Vol 7 (1.1) ◽  
pp. 230
Author(s):  
C. Vasan Sai Krishna ◽  
Y. Bhuvana ◽  
P. Pavan Kumar ◽  
R. Murugan
Keyword(s):  
Denial Of Service ◽  
Distributed Denial Of Service ◽  
Ddos Attacks ◽  
Dos Attack ◽  
Computing Power ◽  
Server Side ◽  
Ddos Attack ◽  
Client Machine ◽  
Client Side

In a typical DoS attack, the attacker tries to bring the server down. In this case, the attacker sends a lot of bogus queries to the server to consume its computing power and bandwidth. As the server’s bandwidth and computing power are always greater than attacker’s client machine, He seeks help from a group of connected computers. DDoS attack involves a lot of client machines which are hijacked by the attacker (together called as botnet). As the server handles all these requests sent by the attacker, all its resources get consumed and it cannot provide services. In this project, we are more concerned about reducing the computing power on the server side by giving the client a puzzle to solve. To prevent such attacks, we use client puzzle mechanism. In this mechanism, we introduce a client-side puzzle which demands the machine to perform tasks that require more resources (computation power). The client’s request is not directly sent to the server. Moreover, there will be an Intermediate Server to monitor all the requests that are being sent to the main server. Before the client’s request is sent to the server, it must solve a puzzle and send the answer. Intermediate Server is used to validate the answer and give access to the client or block the client from accessing the server.

scholarly journals Towards Effective Detection of Recent DDoS Attacks: A Deep Learning Approach

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Ivandro Ortet Lopes ◽  
Deqing Zou ◽  
Francis A Ruambo ◽  
Saeed Akbar ◽  
Bin Yuan
Keyword(s):  
Deep Learning ◽  
Intrusion Detection System ◽  
State Of The Art ◽  
Detection System ◽  
Denial Of Service ◽  
Model Performance ◽  
Distributed Denial Of Service ◽  
Ddos Attacks ◽  
Validation Metrics ◽  
High Processing

Distributed Denial of Service (DDoS) is a predominant threat to the availability of online services due to their size and frequency. However, developing an effective security mechanism to protect a network from this threat is a big challenge because DDoS uses various attack approaches coupled with several possible combinations. Furthermore, most of the existing deep learning- (DL-) based models pose a high processing overhead or may not perform well to detect the recently reported DDoS attacks as these models use outdated datasets for training and evaluation. To address the issues mentioned earlier, we propose CyDDoS, an integrated intrusion detection system (IDS) framework, which combines an ensemble of feature engineering algorithms with the deep neural network. The ensemble feature selection is based on five machine learning classifiers used to identify and extract the most relevant features used by the predictive model. This approach improves the model performance by processing only a subset of relevant features while reducing the computation requirement. We evaluate the model performance based on CICDDoS2019, a modern and realistic dataset consisting of normal and DDoS attack traffic. The evaluation considers different validation metrics such as accuracy, precision, F1-Score, and recall to argue the effectiveness of the proposed framework against state-of-the-art IDSs.

Security of the Cloud

2015 ◽  
pp. 363-404 ◽  
Author(s):  
Khalid Al-Begain ◽  
Michal Zak ◽  
Wael Alosaimi ◽  
Charles Turyagyenda
Keyword(s):  
Service Providers ◽  
Denial Of Service ◽  
Cloud Service ◽  
Future Research ◽  
Cloud Environment ◽  
Ddos Attacks ◽  
Security Attacks ◽  
Edos Attacks ◽  
Future Research Directions ◽  
Cloud Users

The chapter presents current security concerns in the Cloud Computing Environment. The cloud concept and operation raise many concerns for cloud users since they have no control of the arrangements made to protect the services and resources offered. Additionally, it is obvious that many of the cloud service providers will be subject to significant security attacks. Some traditional security attacks such as the Denial of Service attacks (DoS) and distributed DDoS attacks are well known, and there are several proposed solutions to mitigate their impact. However, in the cloud environment, DDoS becomes more severe and can be coupled with Economical Denial of Sustainability (EDoS) attacks. The chapter presents a general overview of cloud security, the types of vulnerabilities, and potential attacks. The chapter further presents a more detailed analysis of DDoS attacks' launch mechanisms and well-known DDoS defence mechanisms. Finally, the chapter presents a DDoS-Mitigation system and potential future research directions.

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