<p>Today, the social interaction has transformed from the physical means to the OSN (Online Social Network) such as the most popular Facebook, Instagram, Twitter platforms. Its quiet apparent from the survey that an individual’s maximum time revolves around surfing the social networking sites and posting one’s personal happenings. Most of the people sharing remain unaware of the fact that the information they are sharing is subject to vulnerabilities and exploitation. Hence there is an urgent need of an effective security technique that’s aids in safeguarding the data as well as identifying any sort of Intrusion. The research put forth a novel approach of PRE-Confirmation Technique that ensures protection and privacy of user’s information that exists on the social networking platforms. Usually, the OSN provides the feature of setting priority and access to the user’s shared information to the relevant people only but the person who has the right to access can misuse or share the information further. Data mining encompasses a broad range of techniques such as classification, clustering, association rule mining, anomaly detection, and regression, each serving different analytical purposes. Without a clear description, it is uncertain whether the approach relies on supervised models (e.g., decision trees, SVM), unsupervised clustering (e.g., k-means, DBSCAN), or hybrid methods for detecting fraudulent or suspicious behavior. For resolving the aforementioned issue, an Artificial Intelligent technique has been recommended in accordance with ‘DPAFAD algorithm’ that evaluates, notifies and give a confirmation request to the actual user before the post is shared or used further. This ascertains that there is no mishandling or downloading of the actual user’s post. It’s well elucidated that the recommended framework proves effective in combating against spammers and hackers prevailing in the OSNs.</p>