Adapting a Social Physics Approach for detection and prevention of Cyber Terrorist activity against personal data

Abstract

This study proposed for determining the use of social physics for detecting and preventing cyber-terrorism in concern to private data access. The adaption of the social physics approach is essential for organizations or individuals to provide cybersecurity to personal and crucial data. In this study, the social physics approach is explained in a manner where personal or private data can be secured as this approach includes the engagement with cyberspace to solve significant data security issues. Moreover, detection of malicious behavior and prevention of malicious behavior is included in the social physics approach.

Introduction

During the last decade, the cyber-attack becomes the most practical issue in information technology. In this, issues related to personal data hacking has been identified most where multifaceted aspects of our lives are lived out within the hyperspace of the cyber environment. It is leading us to determine how to save our data and virtual lives. Increasingly the public is forming online social networking and leaving digihttps://studygroom.com/optics/tal footprints (Saint-Simons, 1803). With this development, it is essential to have attention to the detection and prevention of cyber-terrorism from a behavioral perceptive rather than approaching the issue from technological progress. In this paper, an examination of the current research is developed for investigating the tools and techniques application that is used within social physics for detecting and preventing cyber terrorism and associated adverse activities. However, the main objective of this study is to determine the use of social physics in concern to detect and prevent cyber terrorism from the position of access to personal data.

Analysis of Literature

The social physics can also be considered a concept. Originally developed through the works of Saint-Simons and Comte, social physics was referred to as the science that occupies itself with social phenomena (Coelho, 2016). In addition to this, the recent research study of Pentland (2014), it is identified that social physics can be further refined as a field of science that usages the mathematical tools inspired by physics in order to develop the understanding of the behavior of large groups. For the purposes of this paper, social physics will be viewed as the application of mathematical models and tools used to understand human people through the application of those methods to big data (Small, 2015).

Social Physics engagement in Cyberspace

Social physics is considered as a field of science that is useful to understand human crowds’ behavior using mathematical tools inspired by physics. In the research paper of Altshuler et al. (2011), it is demonstrated that the behavioral information can be used through the use of social physics concepts for new and highly efficient attacks. For example, through the use of inference techniques and data collection, cybercrime can be attempted to steal behavioral information and social network. It is considered a more dangerous theft than other kinds of theft (Bringas, 2008). However, social physics is regarded as a social phenomena analysis with big data in new commercial use.

Social physics can relate to econophysics, where physics methods are used to describe economics. In support of this, the research study of Small (2015) has explained that the concept of Social physics has attention its use in the online social communities for determining or quickly accessing the personal information such as information available on Facebook, Twitter, YouTube, etc. Based on these studies, it can be said that the catalyst for an examination into the use of social physics in the detection and prevention of acts of cyber terrorism (Sezan, 2015).

Detection of Malicious Behavior

The social physics is used in businesses for the geographical distribution of human performance and interaction. Similarly, from the research of Canan and Sousa-Poza (2017), it is examined that in the context modeling, social physics is used as the dynamic representation of interaction patterns within cyberspace. In several business organizations, it draws human interaction and human performance concepts in order to mitigate the issue of geographical distance. With the use of moderated meetings, the undertaken of this modeling is supportive of allowing the visualization of group interaction. On the other hand, Pentland (2014) described that the way of occurrence of human interaction and their tracking system is considered as the essential challenge in the use of cyberspace (Baum, 2018).

In the context of cyber-terrorism, it can be said that the situational awareness must be developed in public, and the applications also get for tracking information flow to detect the redundant interactions and unauthorized decision. According to Canan and Sousa-Poza (2017), it is identified that through this work, the importance of developing situational awareness within cyberspace as a warfare domain. It is stated that ‘the specific aspects of the cyber situations that a given individual needs to be aware of depending on the role of that individual in operation.’  Based on this statement, it is implied that only full situational awareness can be achieved through group interaction (Gomez-Hidalgo, 2010). The information operation awareness should be increased among target audiences for social exploration. In support of this, Canan & Sousa-Poza (2018) suggested that increased social exploration and engagement with target audiences emphasize the need for a complete framework to study information operations. However, it can be said that situational awareness can play an essential role in overcoming the issue of cyber situations in specific aspects.

Currently, it is seen that the cyber-attacks on smart buildings are regularly increasing in developed countries. As per Mylrea and Gourisetti (2017), it is explored that the phenomenon of cyber-attacks on smart buildings is growing rapidly where the energy section is particularly targeted. In these attacks, the smart building controls are exploited as well as corporate networks are also breached. Due to these attacks, it is important to have increased attention to potential prevention and mitigation measures that will be supportive of shorting out the issues (Pace, 2019). For the solution of these attacks, the authors have identified several useful solutions that would be supportive of enhancing smart building security that is showing an excellent interest to this paper in the use of social physics. It is identified that AI platforms improvement and effective use of Metadata for collect, share, and optimize the data in a better way. However, it is considered as a preventative measure for countering any attacks on the system. On the other hand, the authors have not provided detailed information about how these actions might be implemented beyond it as a recommended course of action. In order to use social physics, speculation can be offered that could provide benefits by combining and integrating artificial intelligence, machine learning, and cognitive sensing.

Malicious Behavior Prevention

From the position of social physics, the prevention of malicious behavior cannot be identified by research focused on a review of the literature. Based on the research of Manmadhan and Achuthan (2014), it is proposed that the information leakage could be led by the model user behavior mechanism as it captures the deviations in the intention of the user. On the basis of the proposed model description, it would be simple to adopt a social physics approach. This approach would add in data collection and pattern analysis of the behavior of users (Ball, 2012). However, it can be said that preventive measures from a behavioral perspective were present. With the increased use of the social web, it is essential to provide security to user’s data from potential threats. In support of this, Gomez-Hidalgo et al. (2010) also identified the rise of the ‘social web’ and the need to address concerns over privacy and potential threats to individual data. In this, particular apprehension regarding risks is highlighted by authors that confidentiality is not only crucial for business organizations but also it is useful for individuals to mitigate data loss by suggesting several preventive measures (Mylrea, 2017). At the same time, the earlier study of Bringas et al. (2008) has included data mining and machine learning for identifying the behavior of the users that broke privacy security policies. However, based on this study, it can be said that the network modeling employed is reflective of the emergence of social physics in its current form that is identified by Pentland in his initial work.

Frameworks for Cyber Security

In concern to cybersecurity, situational awareness frameworks play an essential role in tracking cyber-attacks. Bhatt et al. (2014) have proposed a framework for the Security Operations Center (SOC) with activities of performing CSA (Cyber Situational Awareness) capability. The framework is supportive of detecting and analyzing multistage cyber-attacks on security architectures that are layered (Canan, 2017). As per the author, the first is a layered security architecture model that is supportive of protecting a series of privilege levels layers. In this, a set of privileges is required in each identified layer for accessing the assets (Buchanan, 2007). This model some assets include Management team credentials and External Host Files in the external ring and Firewall ACL, Admin credential, Security Server Files, Internal Host files in the internal ring. In this model, the cyber-attacks are prevented through Firewall and Host ACL.

The multistage attack model is supportive of protecting the individual’s data or information through tracking the attack tree used by the attacker. Moreover, Bhatt et al. (2014) also proposed the multistage attack model where attackers use attack trees to achieve goals. It is important for defenders to have good knowledge of different phases that will be achieved by an attacker. For example, an attacker can attack the files server by the use of some specific ways like admin credential and internal host access (Pentland, 2014). The author has suggested seven phases of the Kill Chain Model that an attacker needs to follow for carrying out intrusions like gathering information, weaponization, delivery, exploitation, installation, C2 (Command & Control), and actions. Conversely, it can be said that all the phases given by the Kill Chain Model can be supportive to prevent the cyber-threat.

Intrusion Management System (IMS) is essential to manage all the collected logs and information from different sources in the past one or two years from the web server, mail server, NIDS, and HIDS. At the same time, Intrusion Management System is also proposed by Bhatt et al. (2014) as a framework to prevent the cyber-attack. This model offers rapid processing of big data security for structured or unstructured logs in text files collected from different sources. IMS includes several modules like logging module, log management module, intelligence module, malware analysis modules, and control module (Manmadhan, 2014). Conversely, it can be said that IMS processes or manages all the past data reserved the system space. Based on the above three frameworks, the business organization or an individual can manage their data or information in a more effective manner for privation self-data from cyber-attacks (Canan, Integrating Cyberspace Power into Military Power in Joint Operations Context., 2018). In this concern, Mylrea & Gourisetti, (2017) have also suggested that situational awareness offers elements’ perception within a specified period of time and space. The perception of attacks and attack tracks are involved in the CSA (Cyber Situational Awareness). CSA also includes a comprehension of patterns of attack and correlations that develops a projection about happening in the future regarding information and network assets impacts with identifying threat levels.

Discussion

On the basis of the above literature reviews, it is identified that social physics is a useful approach to detect and prevent cyber-attacks or cyber-terrorist activities against the personal data of an individual and organization. The above literature review divided into two different practical approaches, including detection and prevention that are developing a logical connection between them (Altshuler, 2011). The high literature reviews have suggested that some more considerable research should be undertaken on the detection of malicious behavior. In this, the researcher should identify the particular viewpoint of applying the tools and technics found within the sphere of social physics. Based on the above researches, it can also be discussed that the study does not preclude any notion for preventing cyber-attack behavior that social physics would be equally effective with the prevention (Han, 2014). The above research has also examined the limited literature that is suggesting that the application of social physics and behavioral networking monitoring could be a valuable tool in the battle against cyber terrorism and its associated behaviors. It is also discussed by Pentland, (2014) that the engagement of social physics in Cyberspace is supportive of detecting and preventing cyber-attacks as it offers essential methods and tools. At the same time, it is also discussed that social physics is useful to detect the malicious behaviors of the attacker. It is supported by Gomez-Hidalgo et al. (2010) that increasing the use of the social web can address the privacy and potential threats concerns over individual data. In addition to this, malicious behavior can be prevented by the use of social physics as it includes data mining and machine learning for identifying the behavior of the users. The network modeling employed is reflective for the emergence of social physics in its current form

Limitations and gaps in the literature

This study has included the limited number of literature for investigating the social physics approach. It is young relational nature of the research into the field of social physics in its current form during identified work is not provided its limitations. The key limitation of this research is that this investigation has only focused on the social physics approach. It is because a number of approaches are available that can be utilized to detect and prevent cyber-attacks. As such, limitations and gaps within the limited literature are a result of an emerging field of study and investigative. Moreover, this research is only based on the theoretical understanding basis that provides only a single side of the study. It is not targeting a particular area or group for which this research is conducted that develops confusing results.

Conclusion and recommendations for further research

Based on the above study, it is concluded that the adaption of the social physics approach is beneficial for an individual or organization to detect and prevent the activities related to cyber-terrorist attacks against personal or private data. As per this study, personal or private data can be secured by the use of a social physics approach. It is because social physics includes the engagement with cyberspace for solving the issues related to data security. In addition, this study also developed literature on the detection of malicious behavior of the cyber attackers. Moreover, on the basis of the above study, it is also concluded that the prevention of malicious behavior is also possible by the use of the social physics approach in online tools and websites. There is immense scope to undertake further research in the emergent field of social physics, mainly as it pretends to the detection and prevention of harmful and malicious behavior. With the use of the research study, the previously developed studies on social physics tools and techniques could be re-examined. However, further development on the same topic would allow the specific targets of malicious online behavior.

References