MUMBAI, India, Nov. 2 -- Intellectual Property India has published a patent application (202641121835 A) filed by A. Sarkunavathi; Dr. B. Sangeetha; S. Ramya; Manju Bagga; Jalamanayani Sivarani; and Dr. R. Thiagarajan on October 12, 2026, for Predicting And Identifying Tcp Attacks Using Machine Learning During Acknowledgement Transmission.
Inventors include A. Sarkunavathi; Dr. B. Sangeetha; S. Ramya; Manju Bagga; Jalamanayani Sivarani; and Dr. R. Thiagarajan.
The application for the patent was published on October 30, 2026, under issue no. 44/2026.
Abstract: Abstract The Transmission Control Protocol (TCP) protocol, especially the ACK (acknowledgment) mechanism, is the target of a TCP session ACK request attack, an instance of network assault. TCP employs ACK packets to ensure that data is reliably sent across network endpoints. A target network or system is bombarded by numerous ACK packcts during a TCP session ACK request attack. Several ACK packets are transmitted in an effort to overload the target's network resources, which could end up in network congestion, service interruption, or possibly a denial of service (DoS) scenario. Usually, the attack entails the attacker sending numerous ACK packets to the target, occasionally with spoofed or forged source IP addresses to render it challenging to identify the attacker. In response, the target system uses resources processing and reacting to these numerous ACK packets, leading to an impairment in network performance or even the accessibility of services. Attacks using TCP session ACK requests may take advantages of flaws in the protocol's handling of ACK packets or in the network infrastructure's capacity to manage high traffic requirements. These attacks have the potential to interfere with regular network operations, reduce the availability of services, and cause monetary losses or reputational harm. The key objective is to use several machine learning (ML) methodologies to evaluate and identify TCP-ACK attacks that occur during packet transmission while obtaining higher performance in terms of precision, recall, and accuracy.In this research, it is shown that recognizing and preventing TCP session ACK request attacks requires maintaining an eye upon network activity, examining ACK packet patterns, and setting in place the necessary security safeguards, including firewalls, intrusion detection systems (IDS), and limitation of rate techniques using machine learning techniques. Keywords: TCP-ACK Request, Intrusion Detection Systems (IDS), Machine Learning, ACK Packets, High Traffica
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