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An Effective Technique to Identify Anomalous Accounts on Social Networks using Bloom Filter
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 164 - Number 11 |
| Year of Publication: 2017 |
| Authors: Sarbjeet Kaur, Prabhjot Kaur |
10.5120/ijca2017913732
|
Sarbjeet Kaur, Prabhjot Kaur . An Effective Technique to Identify Anomalous Accounts on Social Networks using Bloom Filter. International Journal of Computer Applications. 164, 11 ( Apr 2017), 38-41. DOI=10.5120/ijca2017913732
Abstract
The anomaly detection is the technique which is applied to detect malicious activities from the social network data. The existing technique is based on to classify the Facebook accounts into three classes which are fake, genuine and moderate. To increase accuracy of account classification is increased when bloom filter is being applied in the algorithm. The bloom filter is the algorithm which learns from the previous experiences and drive new values. When the bloom filter is applied the accounts are classified into two classes. The simulation is being performed in MATLAB and it is being analyzed that accuracy is increased and execution time is reduced.
References
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