The advent of Advanced Persistent Threat (APT) as a new concept in cyber warfare has raised many concerns in recent years. APT based cyber-attacks are usually stealthy, stepwise, slow, longterm, planned, and based on a set of varied zero-day vulnerabilities. As a result, these attacks behave as diverse and dynamic as possible, and hence the generated alerts for these attacks are normally below the common detection thresholds of the conventional attacks. Therefore, the present approaches are not mostly able to effectively detect or analyze the behavior of this class of attacks. In this paper, an approach for real-time detection of APT based cyber-attacks based on causal analysis and correlating the generated alerts by security and non-security sensors is introduced. The proposed method computes the infection score of hosts by modeling, discovery, and analysis of causal relationships among APT steps. For this purpose, a dynamic programming algorithm is introduced which works on alerts of each host separately and conducts a long-term analysis on the attack process to combat the outlasting feature of the APT attacks yet coping with a high volume of alert information. The proposed method is implemented and extensively evaluated using a semi real-world dataset and simulation. The experimental results show that the proposed approach can effectively rank hosts based on their infection likelihood with acceptable accuracy.

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This paper aimed to investigate the cornering characteristics of a Regional Haul Steer II, RHS 315/80 R22.5 truck tire traveling on a dry, hard surface using the Finite element analysis (FEA). This research was carried out using commercial Finite Element software and Pam-Crash in an Explicit Environment. A finite element truck tire model was developed to apply the tire terrain cornering condition. The concentrated loads and boundary conditions for the rim and wheel were applied to the model. The rubber material was defined using the Mooney–Rivlin model. The truck tire cornering operating conditions, including three different speeds with respect to various positive slip angles, were investigated. Several simulations were repeated at various operating conditions, including three different inflation pressures and three different vertical loads. Subsequently, the tire lateral force was computed using the local and global frame coordinates. Additionally, the self-aligning moment was extracted from the tire cross-section at each operating condition. Finally, a comparison between the simulation results showed that the tire lateral force was highly sensitive to the variation of the slip angles at the higher domain, and also that the tire inflation pressure, regardless of the speed, was considered to be one of the main parameters directly affecting the tire-cornering properties.

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