Adaptive IP traceback mechanism for detecting low rate DDoS attacks

2013 ◽  
Author(s):  
M. Baskar ◽  
T. Gnanasekaran ◽  
S. Saravanan
Keyword(s):  
Ddos Attacks ◽  
Ip Traceback ◽  
Low Rate

scholarly journals SOFT COMPUTING BASED AUTONOMOUS LOW RATE DDOS ATTACK DETECTION AND SECURITY FOR CLOUD COMPUTING

2019 ◽  
Vol 2019 (2) ◽  
pp. 80-90 ◽  
Author(s):  
Mugunthan S. R.
Keyword(s):  
Cloud Computing ◽  
Soft Computing ◽  
High Speed ◽  
Denial Of Service ◽  
Attack Detection ◽  
Ddos Attacks ◽  
Counter Measures ◽  
Cloud Architecture ◽  
Ddos Attack Detection ◽  
Low Rate

The fundamental advantage of the cloud environment is its instant scalability in rendering the service according to the various demands. The recent technological growth in the cloud computing makes it accessible to people from everywhere at any time. Multitudes of user utilizes the cloud platform for their various needs and store their complete details that are personnel as well as confidential in the cloud architecture. The storage of the confidential information makes the cloud architecture attractive to its hackers, who aim in misusing the confidential/secret information’s. The misuse of the services and the resources of the cloud architecture has become a common issue in the day to day usage due to the DDOS (distributed denial of service) attacks. The DDOS attacks are highly mature and continue to grow at a high speed making the detecting and the counter measures a challenging task. So the paper uses the soft computing based autonomous detection for the Low rate-DDOS attacks in the cloud architecture. The proposed method utilizes the hidden Markov Model for observing the flow in the network and the Random forest in classifying the detected attacks from the normal flow. The proffered method is evaluated to measure the performance improvement attained in terms of the Recall, Precision, specificity, accuracy and F-measure.

Low-rate DDoS attacks detection method using data compression and behavior divergence measurement

2021 ◽  
Vol 100 ◽  
pp. 102107
Author(s):  
Xinqian Liu ◽  
Jiadong Ren ◽  
Haitao He ◽  
Qian Wang ◽  
Chen Song
Keyword(s):  
Data Compression ◽  
Detection Method ◽  
Ddos Attacks ◽  
Using Data ◽  
And Behavior ◽  
Low Rate

scholarly journals Implementation of a PSO-Based Security Defense Mechanism for Tracing the Sources of DDoS Attacks

Computers ◽  
2019 ◽  
Vol 8 (4) ◽  
pp. 88
Author(s):  
Hsiao-Chung Lin ◽  
Ping Wang ◽  
Wen-Hui Lin
Keyword(s):  
Defense Mechanism ◽  
Detection System ◽  
Denial Of Service ◽  
Packet Routing ◽  
Distributed Network ◽  
Ddos Attacks ◽  
Ip Traceback ◽  
Modified Particle Swarm Optimization ◽  
Network Intrusion ◽  
Management Techniques

Most existing approaches for solving the distributed denial-of-service (DDoS) problem focus on specific security mechanisms, for example, network intrusion detection system (NIDS) detection and firewall configuration, rather than on the packet routing approaches to defend DDoS threats by new flow management techniques. To defend against DDoS attacks, the present study proposes a modified particle swarm optimization (PSO) scheme based on an IP traceback (IPTBK) technique, designated as PSO-IPTBK, to solve the IP traceback problem. Specifically, this work focuses on analyzing the detection of DDoS attacks to predict the possible attack routes in a distributed network. In the proposed approach, the PSO-IPTBK identifies the source of DDoS attacks by reconstructing the probable attack routes from collected network packets. The performance of the PSO-IPTBK algorithm in reconstructing the attack route was investigated through a series of simulations using OMNeT++ 5.5.1 and the INET 4 Framework. The results show that the proposed scheme can determine the most possible route between the attackers and the victim to defend DDoS attacks.

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