An Enhanced Entropy Approach to Detect and Prevent DDoS in Cloud Environment

Distributed Denial of Service (DDoS) attack launched in Cloud computing environment resulted in loss of sensitive information, Data corruption and even rarely lead to service shutdown. Entropy based DDoS mitigation approach analyzes the heuristic data and acts dynamically according to the traffic behavior to effectively segregate the characteristics of incoming traffic. Heuristic data helps in detecting the traffic condition to mitigate the flooding attack. Then, the traffic data is analyzed to distinguish legitimate and attack characteristics. An additional Trust mechanism has been deployed to differentiate legitimate and aggressive legitimate users. Hence, Goodput of Datacenter has been improved by detecting and mitigating the incoming traffic threats at each stage. Simulation results proved that the Enhanced Entropy approach behaves better at DDoS attack prone zones. Profit analysis also proved that the proposed mechanism is deployable at Datacenter for attack mitigation and resource protection which eventually results in beneficial service at slenderized revenu

Discrete R-Contiguous bit Matching mechanism appropriateness for anomaly detection in Wireless Sensor Networks

Resource exhaustion is one of the main challenges for the security of Wireless Sensor Networks (WSNs). The challenge can be addressed by using algorithms that are light weighted. In this paper use of light-weighted R-Contiguous Bit matching for attack detection in WSNs has been evaluated. Use of R-Contiguous bit matching in Negative Selection Algorithm (NSA) has improved the performance of anomaly detection resulting in low false positive, false negative and high detection rates. The proposed model has been tested against some of the attacks. The high detection rate has proved the appropriateness of R-Contiguous bit matching mechanism for anomaly detection in WSNs

Overhead in available bandwidth estimation tools: Evaluation and analysis

Current Available Bandwidth Estimation Tools (ABET) insert into the network probing packets to perform a single estimation. The utilization of these packets makes ABET intrusive and prone to errors since they consume part of the available bandwidth they are measuring. This paper presents a comparative of Overhead Estimation Tools (OET) analysis of representative ABET: Abing, Diettopp, Pathload, PathChirp, Traceband, IGI, PTR, Assolo, and Wbest. By using Internet traffic, the study shows that the insertion of probing packets is a factor that affects two metrics associated to the estimation. First, it is shown that the accuracy is affected proportionally to the amount of probing traffic. Secondly, the Estimation Time (ET) is increased in high congested end-to-end links when auto-induced congestion tools are use

Overhead in Available Bandwidth Estimation Tools: Evaluation and Analysis

The current Available Bandwidth Estimation Tools (ABET's) to perform an estimation, using probes packets are inserted into the network. The utilization These packages, makes ABET's are intrusive and consumes part of which is measuring bandwidth to noise known as "Overhead Estimation Tools" (OET); it’s can produce negative effects on measurements performed by the ABET. This paper presents a complete and comparative analysis of behavior of Available Bandwidth (av_bw), of the ABET's most representative, as well as: Abing, Diettopp, Pathload, PathChirp, Traceband, IGI, PTR, Assolo and Wbest. The study with real Internet traffic, shows the percentage of test that is a factor packets affecting two main aspects of the estimation. The first, the accuracy, and increased indicating that EOT is directly proportional to the percentage of RE, reaching up to 70% in the tool evaluated with most of 30% of Cross-Traffic (CT). And second, the techniques used to send probes packets highly influences the Estimation Time (ET), where some tools that use slops spend up to 240s to converge when there is 60% CT in the network, ensuring that the estimate this technique av_bw highly congested channel, OET as much is used, resulting in inaccuracies in measurement