Attack Modeling Techniques Research Articles

A Compendium on Risk Assessment of Phishing Attack Using Attack Modeling Techniques

With the advent of new attacking methodologies and types of attacks, it has become difficult to protect the systems. Therefore, it is necessary to decipher the impact of attacks before and after its occurrence to provide better security. It is hard to speculate future attacks, without understanding the network vulnerability and therefore, it is important to examine the network for identifying potential vulnerabilities using attack modeling. Phishing attacks is one of the prominent network attacks that pose continual threat to the network and organization. This article presents and discusses in brief attack modeling techniques that can be applied for risk assessment. The paper presents in detail modeling of phishing attack using attack graphs, cyber kill chain, diamond model, security incident response matrix, and data description model. Moreover, the article also discusses role of network defenders and system engineers in assessing risk and how attack models can be helpful to them for modeling attacks. The review presented in this paper can serve as a platform for researchers in the field of network security and risk assessment for developing effective and secure network environment.

Toward Attack Modeling Technique Addressing Resilience in Self-Driving Car

Self-driving cars are going to be the main future mode of transportation. However, such systems like, any other cyber-physical system, are vulnerable to attack vectors and uncertainties. As a response, resilience-based approaches are being developed. However, the approaches lack a sound attack model that recognizes the attack vectors and vulnerabilities such a system would have and that does a proper severity analysis of such attacks. Moreover, the existing attack models are too generic. Currently, the domain lacks such specific work pertaining to self-driving cars. Given the technology and architecture of self-driving cars, the field requires a domain-specific attack model. This paper gives a review of the attack models and proposes a domain-specific attack model for self-driving cars. The proposed attack model, severity-based analytical attack model for resilience (SAAMR), provides attack analysis based on existing models. Also, a domain-based severity score for attacks is calculated. Further, the attacks are classified using the decision-tree method and predictions of the type of attacks are given using long short-term memory network.

An Empirical Evaluation of the Effectiveness of Attack Graphs and Fault Trees in Cyber-Attack Perception

Perceiving and understanding cyber-attacks can be a difficult task. This problem is widely recognized and welldocumented, and more effective techniques are needed to aid cyber-attack perception. Attack modeling techniques (AMTs), such as attack graphs and fault trees, are useful visual aids that can aid cyber-attack perception; however, there is little empirical or comparative research which evaluates the effectiveness of these methods. This paper reports the results of an empirical evaluation between an adapted attack graph method and the fault tree standard to determine which of the two methods is more effective in aiding cyber-attack perception. An empirical evaluation (n = 63) was conducted through a 3 × 2 × 2 factorial design. Participants from computer-science and non-computerscience backgrounds were divided into an adapted attack graph and fault tree group and then asked to complete three tests which tested the ability to recall, comprehend, and apply the AMT. A mean assessment score (mas) was calculated for each test. The results show that the adapted attack graph method is more effective at aiding cyber-attack perception when compared with the fault tree method (p <; 0.01). Participants that have a computer science background outperformed other participants when using both methods (p <; 0.05). These results indicate that the adapted attack graph method can be an effective tool for aiding cyber-attack perception amongst experts. This paper underlines the need for further comparisons in a broader range of settings involving additional techniques, and makes several suggestions for further work.

Generating attack scenarios for the system security validation

Next Generation Network (NGN) is a completely new architectural concept for providing end-users with voice, video, and all sorts of data services. However, secure communication is a key and challenging requirement for NGN service providers. In this paper, we propose an innovative attack script generation and injection approach to evaluate the security of the communication system and consequently detect its security flaws. We apply attack modeling technique to describe the system vulnerabilities and generate system context attack scenarios. The attack scenarios are then refined to executable attack scripts which are executed by communication testing tools in charge of emulating the system attacks. The approach is applied to Wireless Application Protocol (WAP), which is a customized protocol used in resource constrained mobile devices. We performed experiments using specific attacks of the mobile protocol such as Denial of Service (DoS) and Message Truncation attacks. The experiments results demonstrate the effectiveness of the attack injection approach in the role of detecting security vulnerabilities in the communication system.