Comparing Single Tier and Three Tier Infrastructure Designs against DDoS Attacks

2021 ◽  
pp. 541-558
Author(s):  
Akashdeep Bhardwaj ◽  
Sam Goundar
Keyword(s):  
Data Center ◽  
Denial Of Service ◽  
Cyber Attacks ◽  
Cyber Attack ◽  
Ddos Attacks ◽  
Design Data ◽  
Application Performance ◽  
Server Virtualization ◽  
Security Officers ◽  
Cloud Environments

With the rise in cyber-attacks on cloud environments like Brute Force, Malware or Distributed Denial of Service attacks, information security officers and data center administrators have a monumental task on hand. Organizations design data center and service delivery with the aim of catering to maximize device provisioning & availability, improve application performance, ensure better server virtualization and end up securing data centers using security solutions at internet edge protection level. These security solutions prove to be largely inadequate in times of a DDoS cyber-attack. In this paper, traditional data center design is reviewed and compared to the proposed three tier data center. The resilience to withstand against DDoS attacks is measured for Real User Monitoring parameters, compared for the two infrastructure designs and the data is validated using T-Test.

Comparing Single Tier and Three Tier Infrastructure Designs against DDoS Attacks

2017 ◽  
Vol 7 (3) ◽  
pp. 59-75 ◽  
Author(s):  
Akashdeep Bhardwaj ◽  
Sam Goundar
Keyword(s):  
Data Center ◽  
Denial Of Service ◽  
Cyber Attacks ◽  
Cyber Attack ◽  
Ddos Attacks ◽  
Design Data ◽  
Application Performance ◽  
Server Virtualization ◽  
Security Officers ◽  
Cloud Environments

With the rise in cyber-attacks on cloud environments like Brute Force, Malware or Distributed Denial of Service attacks, information security officers and data center administrators have a monumental task on hand. Organizations design data center and service delivery with the aim of catering to maximize device provisioning & availability, improve application performance, ensure better server virtualization and end up securing data centers using security solutions at internet edge protection level. These security solutions prove to be largely inadequate in times of a DDoS cyber-attack. In this paper, traditional data center design is reviewed and compared to the proposed three tier data center. The resilience to withstand against DDoS attacks is measured for Real User Monitoring parameters, compared for the two infrastructure designs and the data is validated using T-Test.

scholarly journals Blockchain Technology towards the Mitigation of Distributed Denial of Service Attacks

2020 ◽  
Vol 8 (6) ◽  
pp. 961-965
Keyword(s):  
Denial Of Service ◽  
Distributed Database ◽  
Cyber Attacks ◽  
Distributed Denial Of Service ◽  
Cyber Attack ◽  
Ddos Attacks ◽  
Denial Of Service Attack ◽  
Blockchain Technology ◽  
Main Challenge ◽  
Communication Devices

The Distributed Denial of Service attack become one of the most adverse effects among all Cyber-attack due to the high availability of the internet and unprotected internetconnected communication devices. There are many mitigation solutions available to reduce the risk of DDoS attacks, and the researcher represents many techniques to get rid of the DDoS attacks. The main challenge to identify and mitigate the attack is that attack traffic mixes with the legitimate system user traffic so it becomes very important to block the attack traffic because it costs in terms of money and system reputation. Blockchain technology presents the ideology of decentralized distributed database and transaction without the need of any central authority. But utilization of blockchain is not only limited to the financial sector but supply chain, IoT, hospitality sector used blockchain most. The most attractive features of the blockchain like immutability, distributed makes the use of blockchain for mitigation of various Cyber-attacks, and one of them is DDoS Attacks. The solution of DDoS attacks that utilize the blockchain is still in the infancy phase. In this paper, we propose the review or survey of DDoS attacks solutions based on blockchain. And also present the comparative study of Blockchain-based DDoS mitigation solutions for non-IOT domain or system. This paper also gives brief about the features of this interconnection of two emerging domain named DDoS Attacks and Blockchain Technology.

scholarly journals A HMM-R Approach to Detect L-DDoS Attack Adaptively on SDN Controller

2018 ◽  
Vol 10 (9) ◽  
pp. 83 ◽  
Author(s):  
Wentao Wang ◽  
Xuan Ke ◽  
Lingxia Wang
Keyword(s):  
Data Center ◽  
False Positive ◽  
Data Flow ◽  
Denial Of Service ◽  
True Positive ◽  
Ddos Attacks ◽  
Data Center Network ◽  
Data Packets ◽  
Positive Rate ◽  
Sdn Controller

A data center network is vulnerable to suffer from concealed low-rate distributed denial of service (L-DDoS) attacks because its data flow has the characteristics of data flow delay, diversity, and synchronization. Several studies have proposed addressing the detection of L-DDoS attacks, most of them are only detect L-DDoS attacks at a fixed rate. These methods cause low true positive and high false positive in detecting multi-rate L-DDoS attacks. Software defined network (SDN) is a new network architecture that can centrally control the network. We use an SDN controller to collect and analyze data packets entering the data center network and calculate the Renyi entropies base on IP of data packets, and then combine them with the hidden Markov model to get a probability model HMM-R to detect L-DDoS attacks at different rates. Compared with the four common attack detection algorithms (KNN, SVM, SOM, BP), HMM-R is superior to them in terms of the true positive rate, the false positive rate, and the adaptivity.

RESEARCH OF THE ISSUES OF IMPROVEMENT OF PROTECTION SYSTEMS AGAINST DDOS-ATTACKS BASED ON THE COMPREHENSIVE ANALYSIS OF MODERN INTERACTION MECHANISMS

2021 ◽  
Vol 53 (1) ◽  
pp. 63-74
Author(s):  
DMITRIY A. BACHMANOV ◽  
◽  
ANDREY R. OCHEREDKO ◽  
MICHAEL M. PUTYATO ◽  
ALEXANDER S. MAKARYAN ◽  
...  
Keyword(s):  
Denial Of Service ◽  
Comprehensive Analysis ◽  
Cyber Attacks ◽  
Ddos Attacks ◽  
Network Resources ◽  
Combined Use ◽  
Service Type ◽  
Protection Systems ◽  
Comparison Criteria

The article presents the results of an analysis of the growth in the development of botnet networks and new cyber threats when they are used by cybercriminals. A review and comparison of the models for the implementation of botnet networks is carried out, as a result of which there are two main types. The main types of attacks carried out using the infrastructure of distributed computer networks are identified and classified, formed into 7 main groups, taking into account the relevance, prevalence and amount of damage. Based on the results of the analysis, it was determined that the most widespread and relevant type of attack is “Denial of Service”. The article presents a classification of services that provide services to ensure the protection of network resources from distributed attacks by the "Denial of Service" type, by the type of deployment, the level of security and the types of services provided. The comparison criteria are given taking into account their infrastructure, availability of technical support and a test period, available types of protection, capabilities, additional options, notification and reporting, as well as licensing. Practically implemented and shown a way to integrate the DDoS-Guard Protection service with an additional module at the application level, which made it possible to expand the methods of protection against DDoS attacks. Various modifications of the combined use of the module and the modified system make it possible to increase the expected level of detection and prevention of cyber - attacks.

scholarly journals Optimasi Keamanan Informasi Pendaftaran Event Menggunakan Teknologi Blockchain

2020 ◽  
Vol 12 (1) ◽  
pp. 74
Author(s):  
Iqbal Busthomi ◽  
Imam Riadi ◽  
Rusydi Umar
Keyword(s):  
Web Application ◽  
Denial Of Service ◽  
Cyber Attacks ◽  
Data Consistency ◽  
Distributed Denial Of Service ◽  
Ddos Attacks ◽  
Registration Data ◽  
Event System ◽  
Start Up ◽  
Cpu Usage

Abstract CV. Nyebar is an IT-based start-up that deals with event data management using a web-based application. The Event system provides account registration services as a Member and Organizer. Members of the Event System must first have an account and log-in to be able to register for the event. The process of registering events so far has not been properly secured. The event registration process will send registrant information, but the information sent has not been secured and validated first, so the Event System is still vulnerable to cyber-attacks including the registration data sniffing attack and Distributed Denial of Service (DDoS) attacks. DDoS attacks are carried out by sending messages and packet requests continuously to the business sector, hosting, social sites originating from bot at one time, resulting in overloaded network servers because of the resources (bandwidth, memory, and CPU usage) they have. the network server is used up. Blockchain which has three techniques/mechanisms including the use of hashes and proof-of-work mechanisms which can be an alternative security for event registration information because it can maintain information security, data consistency, and DDoS attacks.Keyword: Web Application, Distributed Denial of Service (DDoS), BlockchainAbstrak CV. Nyebar merupakan start-up berbasis IT yang bergelut dibidang pengelolaan data event menggunakan sebuah aplikasi berbasis web. Sistem Event menyediakan layanan pendaftaran akun sebagai Member dan Organizer. Member dari Sistem Event harus memiliki akun dan log-in terlebih dahulu untuk mendaftar sebuah event. Proses pendaftaran event sejauh ini belum diamankan dengan baik. Proses pendaftaran event akan mengirimkan informasi pendaftar, namun informasi yang dikirimkan belum diamanakan dan divalidasi terlebih dahulu, sehingga Sistem Event masih rentan akan serangan siber diantaranya adalah serangan sniffing data pendaftaran dan serangan Distributed Denial of Service (DDoS). Serangan DDoS dilakukan dengan mengirimkan pesan dan permintaan paket secara terus menerus kepada sektor bisnis, hosting, situs sosial yang berasal dari bot dalam satu waktu, sehingga mengakibatkan server jaringan menjadi overload karena sumber daya (bandwith, memory, dan CPU usage) yang dimiliki server jaringan habis terpakai. Blockchain yang memiliki dua teknik/mekanisme antara lain adalah penggunaan hash dan mekanisme proof-of-work, yang dapat menjadi alternatif pengamanan informasi pemdaftaran event karena dapat menjaga keamanan informasi, kekonsistenan data, dan serangan dari DDoS.Keyword: Aplikasi Web, Distributed Denial of Service (DDoS), Teknologi Blockchain

Algorithm for Secure Hybrid Cloud Design Against DDoS Attacks

2018 ◽  
Vol 13 (4) ◽  
pp. 61-77 ◽  
Author(s):  
Akashdeep Bhardwaj ◽  
Sam Goundar
Keyword(s):  
Service Industry ◽  
Denial Of Service ◽  
Hybrid Cloud ◽  
Ddos Attacks ◽  
Cloud Infrastructure ◽  
Dos Attacks ◽  
Cloud Application ◽  
Government Education ◽  
Cloud Environments ◽  
Cloud Applications

This article describes how cloud computing has become a significant IT infrastructure in business, government, education, research, and service industry domains. Security of cloud-based applications, especially for those applications with constant inbound and outbound user traffic is important. It becomes of the utmost importance to secure the data flowing between the cloud application and user systems against cyber criminals who launch Denial of Service (DoS) attacks. Existing research related to cloud security focuses on securing the flow of information on servers or between networks but there is a lack of research to mitigate Distributed Denial of Service attacks on cloud environments as presented by Buyya et al. and Fachkha, et al. In this article, the authors propose an algorithm and a Hybrid Cloud-based Secure Architecture to mitigate DDoS attacks. By proposing a three-tier cloud infrastructure with a two-tier defense system for separate Network and Application layers, the authors show that DDoS attacks can be detected and blocked before reaching the infrastructure hosting the Cloud applications.

scholarly journals SDN-Based Intrusion Detection System for Early Detection and Mitigation of DDoS Attacks

Information ◽  
2019 ◽  
Vol 10 (3) ◽  
pp. 106 ◽  
Author(s):  
Pedro Manso ◽  
José Moura ◽  
Carlos Serrão
Keyword(s):  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Network Performance ◽  
Detection System ◽  
Denial Of Service ◽  
Cyber Attacks ◽  
Normal Operation ◽  
Ddos Attacks ◽  
Network Infrastructure ◽  
Sdn Controller

The current paper addresses relevant network security vulnerabilities introduced by network devices within the emerging paradigm of Internet of Things (IoT) as well as the urgent need to mitigate the negative effects of some types of Distributed Denial of Service (DDoS) attacks that try to explore those security weaknesses. We design and implement a Software-Defined Intrusion Detection System (IDS) that reactively impairs the attacks at its origin, ensuring the “normal operation” of the network infrastructure. Our proposal includes an IDS that automatically detects several DDoS attacks, and then as an attack is detected, it notifies a Software Defined Networking (SDN) controller. The current proposal also downloads some convenient traffic forwarding decisions from the SDN controller to network devices. The evaluation results suggest that our proposal timely detects several types of cyber-attacks based on DDoS, mitigates their negative impacts on the network performance, and ensures the correct data delivery of normal traffic. Our work sheds light on the programming relevance over an abstracted view of the network infrastructure to timely detect a Botnet exploitation, mitigate malicious traffic at its source, and protect benign traffic.

scholarly journals A Review of Cloud-Based Malware Detection System: Opportunities, Advances and Challenges

2021 ◽  
Vol 6 (3) ◽  
pp. 1-8
Author(s):  
Ömer Aslan ◽  
Merve Ozkan-Okay ◽  
Deepti Gupta
Keyword(s):  
Detection System ◽  
Hybrid Approach ◽  
Malware Detection ◽  
Cyber Attacks ◽  
Easy Access ◽  
Cyber Attack ◽  
Daily Lives ◽  
Advantages And Disadvantages ◽  
Detection Approach ◽  
Cloud Environments

Cloud computing has an important role in all aspects of storing information and providing services online. It brings several advantages over traditional storing and sharing schema such as an easy access, on-request storage, scalability and decreasing cost. Using its rapidly developing technologies can bring many advantages to the protection of Internet of Things (IoT), Cyber-Physical Systems (CPS) from a variety of cyber-attacks, where IoT, CPS provides facilities to humans in their daily lives. Since malicious software (malware) is increasing exponentially and there is no well-known approach to detecting malware, the usage of cloud environments to detect malware can be a promising method. A new generation of malware is using advanced obfuscation and packing techniques to escape from detection systems. This situation makes almost impossible to detect complex malware by using a traditional detection approach. The paper presents an extensive review of cloud-based malware detection approach and provides a vision to understand the benefit of cloud for protection of IoT, CPS from cyber-attack. This research explains advantages and disadvantages of cloud environments in detecting malware and also proposes a cloud-based malware detection framework, which uses a hybrid approach to detect malware.

Mitigating Cyber-Attacks in Cloud Environments

2021 ◽  
Vol 11 (4) ◽  
pp. 43-57
Author(s):  
Jitendra Singh
Keyword(s):  
Cloud Computing ◽  
Data Center ◽  
Cyber Attacks ◽  
Security Threats ◽  
Cloud Data Center ◽  
Internet Service ◽  
Cloud Data ◽  
Entry Points ◽  
Cloud Environments ◽  
Process Level

Involvement of multiple cloud providers enhances the security complexity in cloud computing. Despite engaging best in class human and hardware resources, cyber-attacks in cloud paradigm continue to rise. This work aims to explore the cloud vulnerabilities that arise due to the multiple entry points. Underlying security threats are categorized into resources at providers' end, hardware security, transmission security, process security, and endpoint security. To mitigate the cyber-attacks in cloud, this work proposed a comprehensive multi-point-based framework that leverages the underlying hardware to strengthen the security at the user's end, internet service provider's end, and at the cloud data center. Security is further fortified by including the process level interaction at terminals. Framework is advanced enough to accommodate the vulnerable points of a system and a network. With the implementation of the proposed system, potential attacks can be detected during early state of penetration.

scholarly journals Detection of Different DDoS Attacks Using Machine Learning Classification Algorithms

2021 ◽  
Vol 26 (5) ◽  
pp. 461-468
Author(s):  
Kishore Babu Dasari ◽  
Nagaraju Devarakonda
Keyword(s):  
Machine Learning ◽  
Cyber Security ◽  
Good Accuracy ◽  
Denial Of Service ◽  
Cyber Attacks ◽  
Classification Algorithms ◽  
Negative Consequences ◽  
Ddos Attacks ◽  
Machine Learning Classification ◽  
Ddos Attack

Cyber attacks are one of the world's most serious challenges nowadays. A Distributed Denial of Service (DDoS) attack is one of the most common cyberattacks that has affected availability, which is one of the most important principles of information security. It leads to so many negative consequences in terms of business, production, reputation, data theft, etc. It shows the importance of effective DDoS detection mechanisms to reduce losses. In order to detect DDoS attacks, statistical and data mining methods have not been given good accuracy values. Researchers get good accuracy values while detecting DDoS attacks by using classification algorithms. But researchers, use individual classification algorithms on generalized DDoS attacks. This study used six machine learning classification algorithms to detect eleven different DDoS attacks on different DDoS attack datasets. We used the CICDDoS2019 dataset which is collected from the Canadian Institute of Cyber security in this study. It contains eleven different DDoS attack datasets in CSV file format. On each DDoS attack, we evaluated the effectiveness of the classification methods Logistic regression, Decision tree, Random Forest, Ada boost, KNN, and Naive Bayes, and determined the best classification algorithms for detection.

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