Identification of Attack on Data Packets Using Rough Set Approach to Secure End to End Communication

Abstract EN

Security has become one of the important factors for any network communication and transmission of data packets.

An organization with an optimal security system can lead to a successful business and can earn huge profit on the business they are doing.

Different network devices are linked to route, compute, monitor, and communicate various real-time developments.

The hackers are trying to attack the network and want to draw the organization’s significant information for its own profits.

During the communication, if an intrusion or eavesdropping occurs, it will lead to a severe disfigurement of the whole communication network, and the data will be controlled by wrong malicious users.

Identification of attack is a way to identify the security violations and analyze the measures in a computer network.

An identification system, which is effective and accurate, can add security to the existing system for secure and smooth communication among end to end nodes and can work efficiently in the identification of attack on data packets.

The role of information security is to design and protect the entire data of networks and maintain its confidentiality, integrity, and availability for their right users.

Therefore, there is a need for end to end security management, which will ensure the security and privacy of the network and will save the data inside networks from malicious users.

As the network devices are growing, so the level of threats is also increasing for these devices.

The proposed research is an endeavor toward the detection of data packets attack by using the rough set theory for a secure end to end communication.

The experimental work was performed by the RSES tool.

The accuracy of the K-NN was 88% for the total objects of 8459.

For cross validation purposes, the decision rules and decomposition tree algorithms were used.

The DR algorithm showed accuracy of 59.1%, while the DT showed accuracy of 61.5%.

The experimental results of the proposed study show that the research is capable of detecting data packets attack.