Advanced Persistent Threat Detection and Mitigation Using Machine Learning Model

The detection of cyber threats has recently been a crucial research domain as the internet and data drive people’s livelihood.Several cyber-attacks lead to the compromise of data security.The proposed system offers complete data protection from Advanced Persistent Threat(APT)attacks with attack detection and defence mechanisms.The modified lateral movement detection algorithm detects the APT attacks,while the defence is achieved by the Dynamic Deception system that makes use of the belief update algorithm.Before termination,every cyber-attack undergoes multiple stages,with the most prominent stage being Lateral Movement(LM).The LM uses a Remote Desktop protocol(RDP)technique to authenticate the unauthorised host leaving footprints on the network and host logs.An anomaly-based approach leveraging the RDP event logs on Windows is used for detecting the evidence of LM.After extracting various feature sets from the logs,the RDP sessions are classified using machine-learning techniques with high recall and precision.It is found that the AdaBoost classifier offers better accuracy,precision,F1 score and recall recording 99.9%,99.9%,0.99 and 0.98%.Further,a dynamic deception process is used as a defence mechanism to mitigateAPTattacks.A hybrid encryption communication,dynamic(Internet Protocol)IP address generation,timing selection and policy allocation are established based on mathematical models.A belief update algorithm controls the defender’s action.The performance of the proposed system is compared with the state-of-the-art models.

Modeling lateral placement and movement of vehicles on urban undivided roads in mixed traf?c:A case study of India

In India,the majority of urban roads are undivided where the behavior of flows in a particular direction is predominantly influenced by the opposing traffic.Due to lack of lane segregation,the vehicles in ongoing direction occupy the opposing lane,which increases the lateral interactions between vehicles.These lateral interactions are influenced by various parameters such as vehicle types,driver behavior and vehicular speeds.Study of such complex interactions plays an important role in evaluating various management measures using microscopic simulation models.The lateral characteristics of vehicles,such as placement,separation and movement,act as necessary input for simulation models.The present study aims to analyze and model the lateral characteristics of vehicles on two-lane urban undivided roads.To achieve this,traffic flow data were collected from an urban undivided mid-block section in Bangalore City,India,using video graphic technique.Multiple linear regression model was developed for predicting the lateral placement of subject vehicle and it was found that lateral placement of subject vehicle is influenced by types and speeds of subject and opposing vehicles.Lateral separation for different types of ongoing(subject)and opposing pairs was also analyzed.The results show that both the ongoing and opposing vehicles have less freedom to move laterally when their sizes increase and hence,lateral separation decreases.The choice of path of vehicles’lateral shifts(left,current and right)on urban undivided roads was modeled using multinomial logistic regression.Lateral shift of a vehicle is influenced by speeds of subject vehicle and leader vehicle in current path,speed of leader vehicle in target path,and lateral gap between leader vehicles in current path and target path.

Dynamic Modeling of a Non-Uniform Flexible Tail for a Robotic Fish

In this paper, a non-uniform flexible tail of a fish robot was presented and the dynamic model was developed. In this model, the non-uniform flexible tail was modeled by a rotary slender beam. The hydrodynamics forces, including the reactive force and resistive force, were analyzed in order to derive the governing equation. This equation is a fourth-order in space and second-order in time Partial Differential Equation （PDE） of the lateral movement function. The coefficients of this PDE were not constants because of the non-uniform beams, so they were approximated by exponential functions in order to obtain an analytical solution. This solution describes the lateral movement of the flexible tail as a function of material, geometrical and actuator properties. Experiments were then carried out and compared to simulations. It was proved that the proposed model is suitable for predicting the real behavior of fish robots.

Dynamic Modeling and Experiment of a Fish Robot with a Flexible Tail Fin

This paper presents the dynamic modeling of a flexible tail for a robotic fish. For this purpose firstly, the flexible tail was simplified as a slewing beam actuated by a driving moment. The governing equation of the flexible tail was derived by using the Euler-Bernoulli theory. In this equation, the resistive forces were estimated as a term analogous to viscous damping. Then, the modal analysis method was applied in order to derive an analytical solution of the governing equation, by which the relationship between the driving moment and the lateral movement of the flexible tail was described. Finally, simulations and experiments were carried out and the results were compared to verify the accuracy of the dynamic model. It was proved that the dynamic model of a fish robot with a flexible tail fin well explains the real behavior of robotic fish in underwater environment.