所有组织都有一个协同信息系统,它是组织中员工与团队之间的共享系统。组织中所有这类信息系统都需要无瑕的安全。通过人工智能、深度学习和区块链等最新技术来保障信息系统的安全是信息科学的最新趋势之一。本文试图通过用户登录时间和在网站上花费的时间以及用户行为的数据对它们进行详细的探讨。目标是开发一个用于用户身份验证的模型。这将允许及早发现欺诈行为,以便提前很好地发起阻断用户访问等预防和补救行动。?开发该模型所用的数据集是用户日志数据,使用逻辑回归技术创建回归模型,用于用户的身份验证。对记录和分析系统上记录的条目所采取的属性采用基于Logistic回归的分类,导致识别一个基于正常和可疑用户的聚类。为保障协同系统的安全,分析并实现了逻辑回归的准确性。本研究将有助于研究者在系统中实施AI。它还讨论了它的未来前景和信息系统实施方面的破坏性变化。最后,研究考虑将区块链( BC )和深度学习( DL )与人工智能( AI )相结合,探讨快速推进人工智能领域将带来的革命性变化。

All organizations have a collaborative information system, which is a shared system between employees and teams in the organisation. All such information systems in organizations need to be flawlessly secure. Securing information systems through the latest technologies like Artificial Intelligence, Deep Learning and Blockchain is one of the latest trends in information sciences. This paper tries to explore them in detail through data on user’s login time and time spent on the websites along with user actions. The objective is to develop a model that will be used for authentication of the user. This will allow early detection of frauds so that preventive and remedial actions like blocking access to the user can be initiated well in advance.  The dataset used to develop this model is the user log data and technique of logistic regression is used to create the regression model for authentication of the user. Logistic regression-based classification is used on the attributes taken to record and analyze entries recorded on the system leading to identification of a cluster based on normal and suspicious users. The accuracy of logistic regression has been analyzed and implemented to secure the collaborative system. This study will help the researcher to implement the AI in the system. It also discusses its future prospects and the disruptive changes in implementation of Information Systems. Finally, the research considers combining blockchain (BC) and deep learning (DL) with Artificial Intelligence (AI) and discusses the revolutionary changes that would result by rapidly advancing the AI field.