| Title | An Effective Swarm Optimization Based Intrusion Detection Classifier System for Cloud Computing |
| Publication Type | Conference Paper |
| Year of Publication | 2019 |
| Authors | Kalaivani, S., Vikram, A., Gopinath, G. |
| Conference Name | 2019 5th International Conference on Advanced Computing Communication Systems (ICACCS) |
| Date Published | mar |
| Keywords | ABC algorithm, Artificial Bee Colony, artificial bee colony algorithm, artificial intelligence, Classification algorithms, cloud computing, cloud computing environment, Communication systems, composability, compositionality, computer network security, DoS attack, effective classifier, effective swarm optimization based intrusion detection classifier system, Flooding Attack, foraging characteristics, Intrusion detection classifier, numerical problems, Optimization, particle swarm optimisation, particle swarm optimization, pubcrawl, replay attack, swarm intelligence, Swarm intelligence algorithm, Swarm Intelligence Optimization, swarm optimization algorithms, Task Analysis |
| Abstract | Most of the swarm optimization techniques are inspired by the characteristics as well as behaviour of flock of birds whereas Artificial Bee Colony is based on the foraging characteristics of the bees. However, certain problems which are solved by ABC do not yield desired results in-terms of performance. ABC is a new devised swarm intelligence algorithm and predominately employed for optimization of numerical problems. The main reason for the success of ABC algorithm is that it consists of feature such as fathomable and flexibility when compared to other swarm optimization algorithms and there are many possible applications of ABC. Cloud computing has their limitation in their application and functionality. The cloud computing environment experiences several security issues such as Dos attack, replay attack, flooding attack. In this paper, an effective classifier is proposed based on Artificial Bee Colony for cloud computing. It is evident in the evaluation results that the proposed classifier achieved a higher accuracy rate. |
| DOI | 10.1109/ICACCS.2019.8728450 |
| Citation Key | kalaivani_effective_2019 |
An Effective Swarm Optimization Based Intrusion Detection Classifier System for Cloud Computing