A comparative recognition research on excretory organism in medical applications using artificial neural networks.

In the contemporary era, a significant number of individuals encounter various health issues, including digestive system ailments, even during their advanced years. The major purpose of this study is based on certain observations that are made in internal digestive systems in order to prevent severe cause that usually occurs in elderly people. To solve the purpose of the proposed method the proposed system is introduced with advanced features and parametric monitoring system that are based on wireless sensor setups.

Techniques and countermeasures for preventing insider threats.

With the wide use of technologies nowadays, various security issues have emerged. Public and private sectors are both spending a large portion of their budget to protect the confidentiality, integrity, and availability of their data from possible attacks. Among these attacks are insider attacks which are more serious than external attacks, as insiders are authorized users who have legitimate access to sensitive assets of an organization.

An Insider Data Leakage Detection Using One-Hot Encoding, Synthetic Minority Oversampling and Machine Learning Techniques.

Insider threats are malicious acts that can be carried out by an authorized employee within an organization. Insider threats represent a major cybersecurity challenge for private and public organizations, as an insider attack can cause extensive damage to organization assets much more than external attacks. Most existing approaches in the field of insider threat focused on detecting general insider attack scenarios.