An Indigenous Solution for SYN Flooding

SYN flooding is one of the most challenging problems that many networks applications face, particularly those that are security-related. Disrupting a server's daily function and assigning it to other tasks leaves it a constantly busy server that processes little usable data. In this research, a comprehensive INDIGSOL approach is demonstrated that not only detects SYN flooding but also prevents the attacker(s) from making such attempts in the future. The designed approach has four modules such as node registration and validation, packet capturing, dynamic check system, and hook activation. The approach is further checked and compared with some state-of-the-art baselines on various parameters like detection time, response/processing time, and number of malicious packets detection. It is observed that INDIGSOL performed better than other baselines with an average accuracy of 99% malicious packet detection in six scenarios along with 13.4% faster detection time and 11.2% faster response/processing time. Overall, the provided solution is scalable, robust, and highly accurate that prevents SYN flooding in a timely manner.

Performance Analysis of Preemptive Priority Retrial Queueing System with Disaster under Working Breakdown Services

In this investigation, a novel sort of retrial queueing system with working breakdown services is introduced. Two distinct kinds of customers are considered, which are priority and ordinary customers. The normal busy server may become inadequate due to catastrophes at any time which cause the major server to fail. At a failure moment, the major server is sent to be fixed and the server functions at a lower speed (called the working breakdown period) during the repair period. The probability generating functions (PGF) of the system size is found using the concepts of the supplementary variable technique (SVT). The impact of parameters in system performance measures and cost optimization are examined numerically.

A Single Server Queue with Immediate Feedback, Working Vacation and Server Breakdown

This paper deals with analyze of a single server queueing system with immediate feedbacks and working vacation. Upon arrival if the customer sees the server to be busy then it joins the tail end of queue. Otherwise if server is idle, the customer gets into service. After completion of service, the customer is allowed to make an immediate feedback in finite number. Busy server may fail for a short interval of time. Using supplementary variable technique the steady state results are deduced. Some system performance measures are discussed

Sensitivity analysis of an M/G/1 retrial queueing system with disaster under working vacations and working breakdowns

This paper deals with the new type of retrial queueing system with working vacations and working breakdowns. The system may become defective by disasters at any point of time when the regular busy server is in operation. The occurrence of disasters forces all customers to leave the system and causes the main server to fail. At a failure instant, the main server is sent to the repair and the repair period immediately begins. As soon as the orbit becomes empty at regular service completion instant or disaster occurs in the regular busy server, the server goes for a working vacation and working breakdown (called lower speed service period). During this period, the server works at a lower service rate to arriving customers. Using the supplementary variable technique, we analyze the steady state probability generating function of system size. Some important system performance measures are obtained. Finally, some numerical examples and cost optimization analysis are presented.

Queues with random service output: the case of Poisson arrivals

A general class of single server queueing models is formulated. They distinguish between two factors that may influence the duration of service times: variability in the service requirements of customers, and variability (over time) in the service output of the server. Accordingly, we assume that the demands for service of successive customers form a sequence of independent, identically distributed random variables and that the amount of service produced by a busy server in a time interval is determined by the increment of a process with stationary independent increments over that interval. The results include the distribution of the busy period and the limiting distribution of the queue length. We also investigate the potential waiting process which is an extension of virtual waiting time process in existing queueing models.

Queues with random service output: the case of Poisson arrivals

A general class of single server queueing models is formulated. They distinguish between two factors that may influence the duration of service times: variability in the service requirements of customers, and variability (over time) in the service output of the server. Accordingly, we assume that the demands for service of successive customers form a sequence of independent, identically distributed random variables and that the amount of service produced by a busy server in a time interval is determined by the increment of a process with stationary independent increments over that interval. The results include the distribution of the busy period and the limiting distribution of the queue length. We also investigate the potential waiting process which is an extension of virtual waiting time process in existing queueing models.