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Thiraviaselvi, G.
- Anomalous Insiders Detection System using K-NN in Collaborative Information Systems
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Authors
Affiliations
1 Department of Information Technology, Francis Xavier Engineering College, Tirunelveli, Tamil Nadu, IN
2 Wicmad Technologies, Tirunelveli, Tamil Nadu, IN
1 Department of Information Technology, Francis Xavier Engineering College, Tirunelveli, Tamil Nadu, IN
2 Wicmad Technologies, Tirunelveli, Tamil Nadu, IN
Source
Journal of Network and Information Security, Vol 8, No 1&2 (2020), Pagination: 31-35Abstract
Collaborative Information Systems (CIS) allow users to belong to different groups to communicate and interfere with shared tasks or documents for collaboration. Current Intrusion Detection Systems are not effective in detecting insider threats where users work in dynamic teams. A malicious hacker who works as an employee of an organization or an outsider who acts as an employee by obtaining false credentials is called an insider threat and that malicious hacker may cause damages to the shared information. The proposed Neighborhood Anomaly Detection System (NADS), is an unsupervised learning framework to detect insider threats. NADs makes use of access logs of collaborative environments for Intrusion Detection. This framework is based on the observation that typical CIS users tend to form Neighborhood structures based on the subjects accessed. NADS consists of two components: 1) relational pattern extraction, where Neighborhood structures are derived and 2) anomaly prediction, which uses a statistical model based on relational pattern extraction. Based on the observations, the deviation of users from the communities they belong to is detected. It is capable to detect anomalous insiders in systems that use dynamic teams.Keywords
Anomaly Detection, Data Mining, Insider Threat, Network Analysis.
References
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- A Cluster-based Overlay Network Embedding using Ruckpack++ Algorithm in Distributed Environment
Abstract Views :242 |
PDF Views:0
Authors
Affiliations
1 Department of Information Technology, Francis Xavier Engineering College, Tirunelveli, Tamil Nadu, IN
2 Department of Mechanical Engineering, Anna University Regional Campus, Tirunelveli, Tamil Nadu, IN
1 Department of Information Technology, Francis Xavier Engineering College, Tirunelveli, Tamil Nadu, IN
2 Department of Mechanical Engineering, Anna University Regional Campus, Tirunelveli, Tamil Nadu, IN
Source
International Journal of Advanced Networking and Applications, Vol 12, No 2 (2020), Pagination: 4555-4560Abstract
Network Virtualization is one of the emerging fields of Research as it becomes pillar of the future Network. Here, Overlay Network Embedding (Virtual Network Embedding) is the major problem to be addressed to have optimized resource utilization. The main purpose of Overlay Network embedding is to efficiently utilize the physically networked resources to offer the supporting of virtual nodes. While most of the Overlay Network Embedding algorithms consider it as a mapping problem, Ruckpack++ algorithm uses cluster-based and greedy approach to select the optimized physical node. In the proposed algorithm, topology awareness is also included. Extensive simulations have shown that the proposed algorithm produces better Acceptance Ratio and node Utilization when compared to other state-of-the-art algorithms.Keywords
Distributed Computing, Network Virtualization, Overlay Network Embedding, Ring Topology.Full Text