tcp

Distributed Denial of Service (DDoS) attacks are of two kinds viz. high-rate DDoS (HRDDoS) attacks and low-rate DDoS (LRDDoS) attacks. A shrew attack is a LRDDoS attack that can prove to be more harmful than a HRDDoS attack since they are not easily noticeable and are stealthy. They cause TCP flows to attain near-zero throughput by sending attack pulses of very short bursts synchronized with the TCP retransmission timeout (RTO) value. Consequently, it compels the TCP packets to be dropped whenever it tries to retransmit again after the timeout. Thus, it may endanger the victim systems if not detected for a long time and reduce the overall quality of services without being noticed. In this paper, we perform the analysis of the network traffic based on a statistical approach where the deviation in the behavior of the flows is analyzed based on the packets sent during the normal and attack conditions. To do this, we determine the participation of a flow in congestion and its adherence to the legitimate TCP-compliant nature during attack conditions based on a priority determiner D. The shrew attack flows exhibit higher values of $D$ as they do not adhere to the TCP compliance and tend to contribute to more congestion to disrupt a server. This nature of attack flows enables us to filter them based on the values of $D$ and mitigate them by blocking these flows. The experimental results on various scenarios demonstrated high accuracy to substantiate the efficacy of the proposed method.

The congestion control problem is one of the most essential subjects in the Transmission Control Protocol (TCP) Network because of the complex nonlinear model, uncertainties, and external disturbances.  This paper extends the adaptive robust H∞ control finite-time approach to TCP network and presents a new solution to solve the congestion control problem employing Active Queue Management (AQM). Firstly, a modified nonlinear model of TCP network system with parametric uncertainties and external disturbance is given. Then, by several variable changes based on the backstepping method and Lyapunov function, adaptation and control laws were derived. Stability analysis is given to prove that all the signals of the closed-loop system are finite-time bounded. In addition, the results show that the proposed controller can guarantee both the transient and steady-state performance of the system, the queue of the TCP network system can track the desired queue and the disturbance is rejected satisfactory based on H∞ control part of the controller. Finally, a comparison example is considered to demonstrate the feasibility and superiority of the presented scheme.

Based on the recent Internet advances, congestion control is considered as an important issue and has spurred a significant amount of research. In this study, second-order sliding mode control is used to adjust the average queue length and maintain the closed-loop system performance. The control law is obtained in two steps. First, the nonlinear state-space form of the network is extracted based on state variables as the average queue length and congestion window size. Then, the proportional-Integrator-derivative and proportional- derivative sliding surface are defined according to the tracking error. Also, in order to avoid chattering, the derivative of the sliding surface is considered and the closed-loop system stability is investigated based on Lyapunov theory. The proposed scheme renders good tracking specifications and closed-loop system robustness. The simulation results show that the proposed methods outperform proportional integral (PI) and proportional integral derivative (PID) schemes. Also, robustness to disturbances increases and chattering and transient response degradation are avoided.

One of the major challenges facing researchers of tissue engineering is scaffold design with desirable physical and mechanical properties for growth and proliferation of cells and tissue formation. In this paper, firstly, β-tricalcium phosphate (β-TCP) nano powders with particle size of 50-70 nm were synthesized using a simple sol–gel route with calcium nitrate and potassium dihydrogenphosphate as calcium and phosphorus precursors, respectively. Then the porous ceramic scaffold containing 40, 50 and 60wt% of nβ-TCP was prepared by the polyurethane sponge replication method. The scaffolds were coated with P3HB for 30 s and 1 min in order to increase the scaffold’s mechanical properties. XRD, XRF, SEM, TEM and FT-IR were used in order to study the phase and element structure, morphology, particle size and determination of functional groups, respectively. Based on the results of compressive strength and porosimetry tests, the most appropriate type of scaffold is 50 wt% of nβ-TCP immersed for 30 sec in P3HB with 75% porosity in 200-600 μm, with a compressive strength of 1.09 MPa and a compressive modulus of 33MPa, which can be utilized in bone tissue engineering.

While the demand for bandwidth increases exponentially with the growing number of internet based devices, traditional TCP algorithms are turning to be sub optimal. Delay-based congestion control algorithms which are designed to overcome this challenge, are proven to be more satisfactory than loss-based congestion algorithms. On the one hand, Loss base congestion detection technique depends solely on packet loss. On the other hand delay-based algorithms have the advantage of proactively detecting congestion occurrences based on packet delays and as a result avoiding unnecessary packet loss. TCP-Vegas as the most referred variant of delay-based algorithms is promised to achieve between 40 and 70 percent better throughput. However there is some problems which are preventing TCP-Vegas to become widespread. One of these problems is lack of fairness in bandwidth allocation while delay and loss-based connection share a link. In this paper we made some modifications on the original TCP-Vegas which enabled the new algorithm to compete fairly with loss-based algorithm.