Android has become the most prevalent mobile system, but in the meanwhile malware on this platform is widespread. System call sequences are studied to detect malware. However, malware detection with these approaches relies on common system-call-subsequences. It is not so efficient because it is difficult to decide the appropriate length of the common subsequences. To address this issue, the authors propose a new approach, back-propagation neural network on Markov chains from system call sequences (BMSCS). It treats one system call sequence as a homogeneous stationary Markov chain and applies back-propagation neural network (BPNN) to detect malware by comparing transition probabilities in the chain. Since transition probabilities from one system call to another in malware are significantly different from those in benign applications, BMSCS can efficiently detect malware by capturing the anomaly in state transitions with the help of BPNN. The authors evaluate the performance of BMSCS by experiments with real application samples. The experiment results show that the F 
-score of BMSCS achieves up to 0.982773, which is higher than the other methods in the literature.

https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/iet-ifs.2015.0211

Back-propagation neural network on Markov chains from system call sequences: a new approach for detecting Android malware with system call sequences

The recent increasing cases released worldwide on espionage require a knowledge systematization study in this area. This paper presents a general scheme of cyber espionage process based on a literature review of remarkable cases which generated news about this topic and includes the malware report analysis made by security vendors. To understand the aspects involved and the approaches employed, we defined a general model to cover all phases used by cyber espionage. Our model considers two main aspects: first, the technical aspect driven by the rapid advance of information and communication technologies (ICT), as well as the software engineering level used by cybercriminals to create sophisticated malware; second, the human aspect influenced by the power struggle between nations and politicians, also considering the lack of technological knowledge or training in organizations. As a result, it allows the attackers using social engineering as the most effective mean for systems intruding.

An Analysis of Cyber Espionage Process

With the launch and development of the Android system, it is urgent to solve its terminal security protection problem. Based on three aspects, i.e., Android features, security architecture and security mechanisms, this paper analyses the security threats and the corresponding risks faced by the terminal from the technical level and management level respectively. Moreover, a security ecosystem architecture based on Android platform is designed reasonably and effectively to regulate the Android management system. The proposed ecosystem is benefit to solve the security problems such as open-source vulnerability and App store management chaos. The achievement of this paper promotes researches of security risk issues positively.

http://ieeexplore.ieee.org/iel7/6745500/6748549/06748619.pdf

Research of secure ecosystem based on Android platform

With the rapid development of information technology, people more and more dependent on cyberspace, cyberspace connects billions of users all over the world. It offers great convenience to people; but it also provides a lot of opportunities for criminals to commit crime using the new information tools. Cyberspace has been faced many security challenges like identity tracing, identity theft, cyberspace terrorism and cyberspace warfare. In this paper, we focus on analysis these security challenges, and give some possible solutions offered by law and technology.

Jinhua Liu

Papers

Research of secure ecosystem based on Android platform

Security in cyberspace: issues, challenges and suggestion

Evaluation of Urban Resilience in the Post-COVID-19 Period: A Case Study of the Yangtze Delta City Group in China