Zhaoyu Liu

Bio: Zhaoyu Liu is an academic researcher from University of North Carolina at Charlotte. The author has contributed to research in topics: Intrusion detection system & Routing protocol. The author has an hindex of 2, co-authored 2 publications receiving 232 citations.

A dynamic trust model for mobile ad hoc networks

Abstract: This paper introduces a trust model for mobile ad hoc networks. Initially each node is assigned a trust level. Then we use several approaches to dynamically update trust levels by using reports from threat detection tools, such as intrusion detection systems (IDS), located on all nodes in the network. The nodes neighboring to a node exhibiting suspicious behavior initiate trust reports. These trust reports are propagated through the network using one of our proposed methods. A source node can use the trust levels it establishes for other nodes to evaluate the security of routes to destination nodes. Using these trust levels as a guide, the source node can then select a route that meets the security requirements of the message to be transmitted. This paper demonstrates important concepts for establishing a collaborative, dynamic trust model and for using this model as an example to enhance the security of message routing in mobile ad hoc networks.

User Behavior Identification for Trust Management in Pervasive Computing Systems

Abstract: Pervasive computing systems are becoming widespread as the next generation of computing systems. In pervasive computing systems, the users are frequently hopping from one computing space to another, which makes user profile management an essential component of the system. Because such a dynamic-populated computing system has to be new corner-friendly, malicious users with bad reputation to a system may take advantage of the system by claiming themselves as new users. In addition, user identity can also be compromised by controlling the victim node via normal invasions or even by inside identity thefts. A valid user identity is the foundation and prerequisite of trust. Failures to correctly identify a user are catastrophic to trust management system. Traditional intrusion detection systems can only detect an attack when it already happens. But before the intrusion the attackers may have some specific behavioral signatures indicating of their suspicious identities. We need a more powerful and practical system to identify these suspicious behaviors and signal an early warning to stop them. In this paper we assume that user identity is compromised either by attacking and controlling a node or by malicious users' claiming themselves as new users. We introduced a novel user behavior identification and profile management system to detect the suspicious behaviors, and a dynamically triggered reaction module to monitor the suspicious node and collect the necessary evidences

Research on computer network information security management and protection strategy

Abstract: With the rapid development of network information technology, we have entered the era of big data. Under this background, computer network information security has also become a major hidden danger. It is extremely important to strengthen the security maintenance of computer network. Therefore, the problem of network information security needs to be solved urgently. This paper presents a computer network information security management method based on big data. Deploy the network probe on the PC server to obtain the network traffic information; Principal component analysis and tabu search algorithm will be used to select the characteristic index of network traffic information; Based on BP neural network classification and identification of abnormal behavior, in order to prevent illegal attacks in time and ensure the security of network information. The experimental results show that the detection rate of the four attack modes using the design method is more than 95%, and the false positive rate is less than 1.5%, which proves that the security management effect of this method is good.

A Survey on Trust Management for Mobile Ad Hoc Networks

Abstract: Managing trust in a distributed Mobile Ad Hoc Network (MANET) is challenging when collaboration or cooperation is critical to achieving mission and system goals such as reliability, availability, scalability, and reconfigurability. In defining and managing trust in a military MANET, we must consider the interactions between the composite cognitive, social, information and communication networks, and take into account the severe resource constraints (e.g., computing power, energy, bandwidth, time), and dynamics (e.g., topology changes, node mobility, node failure, propagation channel conditions). We seek to combine the notions of "social trust" derived from social networks with "quality-of-service (QoS) trust" derived from information and communication networks to obtain a composite trust metric. We discuss the concepts and properties of trust and derive some unique characteristics of trust in MANETs, drawing upon social notions of trust. We provide a survey of trust management schemes developed for MANETs and discuss generally accepted classifications, potential attacks, performance metrics, and trust metrics in MANETs. Finally, we discuss future research areas on trust management in MANETs based on the concept of social and cognitive networks.

Trust Computations and Trust Dynamics in Mobile Adhoc Networks: A Survey

Abstract: Trust is an important aspect of mobile adhoc networks (MANETs). It enables entities to cope with uncertainty and uncontrollability caused by the free will of others. Trust computations and management are highly challenging issues in MANETs due to computational complexity constraints, and the independent movement of component nodes. This prevents the direct application of techniques suited for other networks. In MANETs, an untrustworthy node can wreak considerable damage and adversely affect the quality and reliability of data. Therefore, analyzing the trust level of a node has a positive influence on the confidence with which an entity conducts transactions with that node. In this work we present a detailed survey on various trust computing approaches that are geared towards MANETs. We highlight the summary and comparisons of these approaches. In addition, we analyze various works on trust dynamics including trust propagation, prediction and aggregation algorithms, the influence of network dynamics on trust dynamics and the impact of trust on security services.

Group-Based Trust Management Scheme for Clustered Wireless Sensor Networks

Abstract: Traditional trust management schemes developed for wired and wireless ad hoc networks are not well suited for sensor networks due to their higher consumption of resources such as memory and power. In this work, we propose a new lightweight group-based trust management scheme (GTMS) for wireless sensor networks, which employs clustering. Our approach reduces the cost of trust evaluation. Also, theoretical as well as simulation results show that our scheme demands less memory, energy, and communication overheads as compared to the current state-of-the-art trust management schemes and it is more suitable for large-scale sensor networks. Furthermore, GTMS also enables us to detect and prevent malicious, selfish, and faulty nodes.