Visible to the public Biblio

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SAADI, C., kandrouch, i, CHAOUI, H..  2019.  Proposed security by IDS-AM in Android system. 2019 5th International Conference on Optimization and Applications (ICOA). :1—7.

Mobile systems are always growing, automatically they need enough resources to secure them. Indeed, traditional techniques for protecting the mobile environment are no longer effective. We need to look for new mechanisms to protect the mobile environment from malicious behavior. In this paper, we examine one of the most popular systems, Android OS. Next, we will propose a distributed architecture based on IDS-AM to detect intrusions by mobile agents (IDS-AM).

Kumari, Alpana, Krishnan, Shoba.  2019.  Analysis of Malicious Behavior of Blackhole and Rushing Attack in MANET. 2019 International Conference on Nascent Technologies in Engineering (ICNTE). :1–6.

Mobile Adhoc Network (MANET) are the networks where network nodes uses wireless links to transfer information from one node to another without making use of existing infrastructure. There is no node in the network to control and coordinate establishment of connections between the network nodes. Hence the network nodes performs dual function of both node as well as router. Due to dynamically changing network scenarios, absence of centralization and lack of resources, MANETs have a threat of large number of security attacks. Hence security attacks need to be evaluated in order to find effective methods to avoid or remove them. In this paper malicious behavior of Blackhole attack and Rushing attack is studied and analyzed for QoS metrics.

Chen, Guangxuan, Wu, Di, Chen, Guangxiao, Qin, Panke, Zhang, Lei, Liu, Qiang.  2019.  Research on Digital Forensics Framework for Malicious Behavior in Cloud. 2019 IEEE 4th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC). 1:1375—1379.

The difficult of detecting, response, tracing the malicious behavior in cloud has brought great challenges to the law enforcement in combating cybercrimes. This paper presents a malicious behavior oriented framework of detection, emergency response, traceability, and digital forensics in cloud environment. A cloud-based malicious behavior detection mechanism based on SDN is constructed, which implements full-traffic flow detection technology and malicious virtual machine detection based on memory analysis. The emergency response and traceability module can clarify the types of the malicious behavior and the impacts of the events, and locate the source of the event. The key nodes and paths of the infection topology or propagation path of the malicious behavior will be located security measure will be dispatched timely. The proposed IaaS service based forensics module realized the virtualization facility memory evidence extraction and analysis techniques, which can solve volatile data loss problems that often happened in traditional forensic methods.

S. Saquib, R. Ali.  2015.  Malicious behavior in online social network. 2015 IEEE Workshop on Computational Intelligence: Theories, Applications and Future Directions (WCI). :1-6.

Nowadays, Online Social Networks (OSNs) are very popular and have become an integral part of our life. People are dependent on Online Social Networks for various purposes. The activities of most of the users are normal, but a few of the users exhibit unusual and suspicious behavior. We term this suspicious and unusual behavior as malicious behavior. Malicious behavior in Online Social Networks includes a wide range of unethical activities and actions performed by individuals or communities to manipulate thought process of OSN users to fulfill their vested interest. Such malicious behavior needs to be checked and its effects should be minimized. To minimize effects of such malicious activities, we require proper detection and containment strategy. Such strategy will protect millions of users across the OSNs from misinformation and security threats. In this paper, we discuss the different studies performed in the area of malicious behavior analysis and propose a framework for detection of malicious behavior in OSNs.

Salman, A., Elhajj, I.H., Chehab, A., Kayssi, A..  2014.  DAIDS: An Architecture for Modular Mobile IDS. Advanced Information Networking and Applications Workshops (WAINA), 2014 28th International Conference on. :328-333.

The popularity of mobile devices and the enormous number of third party mobile applications in the market have naturally lead to several vulnerabilities being identified and abused. This is coupled with the immaturity of intrusion detection system (IDS) technology targeting mobile devices. In this paper we propose a modular host-based IDS framework for mobile devices that uses behavior analysis to profile applications on the Android platform. Anomaly detection can then be used to categorize malicious behavior and alert users. The proposed system accommodates different detection algorithms, and is being tested at a major telecom operator in North America. This paper highlights the architecture, findings, and lessons learned.