Wafaa Al-Salihy

Security Analysis of Vehicular Ad Hoc Nerworks (VANET)

Vehicular Ad Hoc Networks (VANET) has mostly gained the attention of today’s research efforts, while current solutions to achieve secure VANET, to protect the network from adversary and attacks still not enough, trying to reach a satisfactory level, for the driver and manufacturer to achieve safety of life and infotainment. The need for a robust VANET networks is strongly dependent on their security and privacy features, which will be discussed in this paper. In this paper a various types of security problems and challenges of VANET been analyzed and discussed; we also discuss a set of solutions presented to solve these challenges and problems.

Efficient certificate management in VANET

Vehicular Ad hoc Networks is one of the most challenging research area in the field of Mobile Ad Hoc Networks, in this research We propose a flexible, simple, and scalable design for VANET certificates, and new methods for efficient certificate management, which will Reduce channel overhead by eliminating the use of CRL, and make Better certificate Revocation Management. Also it will increase the security of the network and helps in identifying the adversary vehicle.

Indoor WLAN Monitoring and Planning Using Empirical and Theoretical Propagation Models

The wireless propagation prediction and measurement techniques are the ideas behind a successful deployment of indoor wireless local area network (WLAN). Therefore, a solution is proposed to monitor and plan the WLAN, based on the propagation prediction and measurement techniques with coloured contour visualization for IEEE 802.11 a/b/g/n standards. The solution is able to help wireless designers to visualize the WLAN signal coverage, overlapping channel interference, data rate and signal to noise ratio (SNR). The radio predictions or planning works are based on the theoretical model and the measurements or monitoring works are based on empirical model. The visualization will show the results of the WLAN monitoring and planning works with indoor wireless propagation effects from the multiple floors of the building. The experimental devices are two dual band 2.4 GHz and 5 GHz (IEEE 802.11n) access points, a 2.4 GHz (802.11g) access point, and a wireless receiver from a laptop.

Integrating Identity-Based Encryption in the Return Routability Protocol to Enhance Signal Security in Mobile IPv6

In Mobile IPv6 (MIPv6), the authentication procedure between nodes has recently been an active research area. Return Routability Protocol (RRP) is a mechanism used in MIPv6 to provide the nodes with some authentication and to secure binding update messages. A large number of studies have discussed the weaknesses of this mechanism and its enhancement. In the current paper, a new approach called Return Routability Identity-Based Encryption protocol is proposed for the enhancement of security and authentication in the predecessor RRP. Hence, the proposed protocol is simulated and verified using a Murphi model checker. Finally, the simulation results show that strong security and authentication between the nodes have been achieved, and the current attacks in Return Routability have been addressed.

A new security mechanism for vehicular communication networks

Vehicular communication networks is a promising and emerging technology to facilitat road safety, Safety of life, traffic management, and infotainment dissemination for drivers and passengers. One of the ultimate goals in the design of such networking is to resist various malicious abuses and security attacks. In this research new security mechanisms are proposed to achieve secure certificate revocation, which is considered among the most challenging design objective in vehicular ad hoc networks.

Combination of neural network based clustering and genetic algorithm for multi-objective 802.11n planning

Wireless local area network (WLAN) planning process is a complicated task and requires constant monitoring as the health of WLAN can be easily interfered by many factors. With 802.11n access points and routers deployment, managing the WLAN can be further complicating the usual tasks for wireless administrator. This paper presents a network plan for IEEE 802.11 based WLAN as pre-deployment plan for the WLAN 802.11n standard devices. The strategy to be used is a combination of neural network based clustering and genetic algorithm for collecting real WLAN data and a pure genetic algorithm for simulation. Computational results show that this hybrid approach provides good enough quality solutions within a reasonable amount of time. His document gives formatting instructions for authors preparing papers for publication in the Proceedings of an IEEE conference. The authors must follow the instructions given in the document for the papers to be published. You can use this document as both an instruction set and as a template into which you can type your own text.

Research Proposal: An Intrusion Detection System Alert Reduction and Assessment Framework Based on Data Mining

The Intrusion Detection System (IDS) generates huge amounts of alerts that are mostly false positives. The abundance of false positive alerts makes it difficult for the security analyst to identify successful attacks and to take remedial actions. Such alerts to have not been classified in accordance with their degree of threats. They further need to be processed to ascertain the most serious alerts and the time of the reaction response. They may take a long time and considerable space to discuss thoroughly. Each IDS generates a huge amount of alerts where most of them are real while the others are not (i.e., false alert) or are redundant alerts. The false alerts create a serious problem for intrusion detection systems. Alerts are defined based on source/destination IP and source/destination ports. However, one cannot know which of those IP/ports bring a threat to the network. The IDSs’ alerts are not classified depending on their degree of the threat. It is difficult for the security analyst to identify attacks and take remedial action for this threat. So it is necessary to assist in categorizing the degree of the threat, by using data mining techniques. The proposed framework for proposal is IDS Alert Reduction and Assessment Based on Data Mining (ARADMF). The proposed framework contains three systems: Traffic data retrieval and collection mechanism system, reduction IDS alert processes system and threat score process of IDS alert system. The traffic data retrieval and collection mechanism systems develops a mechanism to save IDS alerts, extract the standard features as intrusion detection message exchange format and save them in DB file (CSV-type). It contains the Intrusion Detection Message Exchange Format (IDMEF) which works as procurement alerts and field reduction is used as data standardization to make the format of alert as standard as possible. As for Feature Extraction (FE) system, it is designed to extract the features of alert by using a gain information algorithm, which gives a rank for every feature to facilitate the selection of the feature with the highest rank. The main function of reduction IDS alert processes system is to remove duplicate IDS alerts and reduces the amount of false alerts based on a new aggregation algorithm. It consists of three phases. The first phase removes redundant alerts. The second phase reduces false alerts based on threshold time value and the last phase reduces false alerts based on rules with a threshold common vulnerabilities and exposure value. Threat score process of IDS alert system is characterized by using a proposed adaptive Apriori algorithm, which has been modified to work with multi features, i.e., items and automated classification of alerts according to their threat’s scores. The expected result of his proposed will be decreasing the number of false positive alert with rate expected 90% and increasing the level of accuracy compared with other approaches. The reasons behind using ARADMF are to reduce the false IDS alerts and to assess them to examine the threat score of IDS alert, that is will be effort to increase the efficiency and accuracy of network security.

Distributed iSCSI protocol over Hypervisor Storage on Local Area Network

Internet Small Computer System Interface (iSCSI) is a protocol that can run on a TCP/IP transport layer in order to transfer SCSI commands to allow block-level access on storage devices which is standardized by IETF. Hypervisor Storage is the storage abstraction layer on Virtual Machines. This paper examines the performance of iSCSI protocol implementation accessing Hypervisor Storage in Virtual Machines (guest OS) over Gigabit Ethernet Local Area Network (GE-LAN). The results of this experiment are benchmark with results that we obtained from a Network Attached Storage (NAS) Server using CIFS/SMB protocol running on the Hypervisor Storage and results obtained from local access on virtual machines. We found that iSCSI has low throughput, heavy utilization of CPU, and high I/O latency compared to CIFS/SMB Protocol on NAS and local virtual disk access results which are significantly similar.