01752nas a2200169   4500008004100000245008000041210006900121260001000190300001200200490000700212520123000219100002001449700001601469700001901485700002201504856005601526       2018                        eng d00aNew approach for intrusion detection in Big Data as a service in the Cloud-0 aNew approach for intrusion detection in Big Data as a service in  c10/12  a258-2700 v163 a<p>&nbsp;Nowadays, Big Data has reached every area of our lives because it covers many tasks in different operation. This new technique forces the cloud computing to use it as a layer, for this reason cloud technology embraces it as Big Data as a service (BDAAS). After solving the problem of storing huge volumes of information circulating on the Internet, remains to us how we can protect and ensure that this information are stored&nbsp; without loss or distortion. The aim of this paper is to study the problem of safety in BDAAS, inparticularly we will cover the problem of Intrusion detection system (IDS). In order to solve the problems tackled in this paper, we have proposed a Self-Learning Autonomous Intrusion Detection system (SLA-IDS) which is based on the architecture ofautonomic system to detect the anomaly data. In this approach, to add the autonomy aspect to the proposed system we have used mobile and situated agents. The implementation of this model has been provided to evaluate our system. The obtained findings show the effectiveness of our proposed model. We validate our proposition using Hadoop as Big Data Platform and CloudSim, machine learning Weka with java to create Model of detection.</p>
1 aKassimi, Dounya1 aKazar, Okba1 aBoussaid, Omar1 aMerizig, Abdelhak  uhttp://dline.info/fpaper/jdim/v16i5/jdimv16i5_5.pdf