Ilkyeun Ra

An efficient and reliable DDoS attack detection using a fast entropy computation method

The threat of Distributed Denial of Service (DDoS) has become a major issue in network security and is difficult to detect because all DDoS traffics have normal packet characteristics. Various detection and defense algorithms have been studied. One of them is an entropy-based intrusion detection approach that is a powerful and simple way to identify abnormal conditions from network channels. However, the burden of computing information entropy values from heavy flow still exists. To reduce the computing time, we have developed a DDoS detection scheme using a compression entropy method. It allows us to significantly reduce the computation time for calculating information entropy. However, our experiment suggests that the compression entropy approach tends to be too sensitive to verify real network attacks and produces many false negatives. In this paper, we propose a fast entropy scheme that can overcome the issue of false negatives and will not increase the computational time. Our simulation shows that the fast entropy computing method not only reduced computational time by more than 90% compared to conventional entropy, but also increased the detection accuracy compared to conventional and compression entropy approaches.

QoS Mesh Routing Protocol for IEEE 802.16 based Wireless Mesh Networks

This paper proposes QoS Mesh routing protocol for IEEE 802.16 based wireless mesh networks. QoS Mesh Routing Protocol proposed in this paper is a proactive hop-by-hop QoS routing protocol. The goal of our protocol is not only to find routes from a source to a destination node, but also optimal routes that satisfies QoS requirements, given in terms of bandwidth and delay as default QoS parameters. In this paper, we first analyze possible types of routing protocols that have been studied for MANET and show proactive hop-by-hop routing protocols are the most appropriate for wireless mesh networks. Then, we present a network model for IEEE 802.16 based wireless mesh networks and propose a proactive hop-by-hop QoS routing protocol. Through our simulation, we represent that our routing protocol outperforms QOLSR protocol in terms of end-to-end delay, packet delivery ratio and routing overhead.

e-Lollapalooza: A Process-Driven e-Business Service Integration System for e-Logistics Services

There are two newly emerging research issues in the enterprise information systems literature. One is the scalability issue for rapidly increasing choreographic volumes between interrelated organizations. The other is the business intelligence issue for traceable and monitorable business processes and services interchanging e-Business data and applications across organizations. Based upon these emerging issues, through a functional extension of the ebXML technology we have developed a process-driven eBusiness service integration (BSI) system, which is named ‘e-Lollapalooza’. It consists of three major components – the Choreography Modeler coping with the processdriven collaboration issue, the Runtime & Monitoring Client for coping with the business intelligence issue and the EJB-based BSI Engine coping with the scalability issue. This paper particularly focuses on the e-Lollapalooza’s development aspects for supporting the ebXML-based choreography and orchestration among the engaged organizations in a process-driven multiparty collaboration for e-Logistics and eCommerce services. Here, it is fully deployed in an EJB-based middleware computing environment for e-Logistics process automation and B2B choreography.

Adaptive DDoS Detector Design Using Fast Entropy Computation Method

Recently, the threat of DDoS (Distributed Denial-of-Service) attacks is growing continuously and acquiring attacking tools via Internet is getting easy. One of the researches introduced a fast method to detect attacks using modified information entropy (so called Fast Entropy). Fast Entropy shows the significant reduce of computational time compared to conventional entropy computation while it maintains detection accuracy. However, Fast Entropy needs the manual threshold settings during detection process which is not realistic in real detection facility. We introduce adaptive detector with dynamic detection window size and adaptive threshold shifting using Fast Entropy, called AFEA (Adaptive DDoS attack detection using Fast Entropy Approach). Our adaptive DDoS detector successfully demonstrates that its performance of the DDoS detection can be enhanced by the best result of Fast Entropy detection scheme without manual threshold setting and system training while it maintains the same computational time of Fast Entropy detection scheme. In addition, we found that Dynamic AFEA can enhance detection level more than fixed (non-dynamic) one when it is equipped with Fast Entropy

Adaptive-gossiping for an energy-aware routing protocol in wireless sensor networks

Energy efficiency is the essential consideration in advances of wireless sensor networks (WSNs) usefully designed for low data rate, low power consumption, and low-cost networking. Mindful of the above constraints, selecting an appropriate routing protocol can significantly improve overall performance with limited sensor network resources, especially energy awareness in WSNs. We propose an energy-aware routing protocol improved by our adaptive-gossip algorithm that will reduce the redundant routing messages so that it can minimize the overall energy consumption of a WSN. To analyze the energy efficiency, we introduce two energy performance metrics: Delay*Energy and Normalized-RoutingLoad*Energy. These metrics suggest that energy consumption heavily depends on both packet losses and packet delivery successes that affect delay and routing overhead respectively. We present both analytical and experimental results thoroughly to evaluate our adaptive-gossip proposal, and demonstrate its advantages over flooding and static-gossiping based protocols for densely deployed networks and different types of network such as peer-to-peer and multi-to-one.

Network resource efficient routing in mobile ad hoc wireless networks

Network resources in mobile ad hoc wireless networks (MANETs) are constrained due to their dynamic topology and lack of centralized control. Mobile nodes in MANETs tend to broadcast packets to exchange information and consume lots of network resources such as network bandwidth and battery power of each node during forwarding their packets. Hence, the conserving network resource is crucial to maintain the quality of network services without interruptions. In order to discover an ideal routing algorithm that should use minimum network resources and improve network performance, we propose an adaptive-gossiping routing algorithm that saves network bandwidth and energy consumption at each node by reducing the duplicated routing messages. Our new analytical model of adaptive-gossiping probability

Design and Evaluation of a Network Forensic Logging System

p_{n}

Toward a voice interface and personalized local web search in smart phones

pn provides a less routing overhead which results in conserving network resources and reducing the end-to-end delay. The both analytical and experimental results of our proposed method confirm its advantages over flooding and static-gossiping based routing protocols in large-scale networks.