Maheyzah Md Siraj ¹, Hashim Hussein Taha Albasheer ², Mazura Mat Din ¹

Affiliations
1 Information Assurance and Security Research Group (IASRG), Faculty of Computing, Universiti Teknologi Malaysia, Skudai, Johor, MY
2 Department of Information Systems, Faculty of Computer, King Khalid University - 62529, SA

Abstract

Despite of Network Intrusion Detection System/Sensors (NIDSs) deployment in the computer networks to detect various attacks, it raises a serious problem. They generate a high volume of low-quality intrusion alerts when attack scenarios have taken place. Worst, NIDSs cannot extract or even predict sequence of attack scenarios. Thus, alert post-processing or known as Alert Correlation (AC) is much needed to derive current system security. AC aims to identify the complete relationship among intrusion alerts that can reveal the attacker strategy (i.e., sequence of attack scenarios). Current works do not provide attack prediction and proactive actions when attack scenarios were launched. Prediction can assists early warning and prevention to avoid the attack from escalating and damaging the network. In this paper, we highlight the important research problems in developing AC which has motivate us to propose a new AC framework design that include attack prediction and proactive step in a real-time multiple sensors environment. It is worth mentioning that to complement NIDSs in detecting the incoming attacks, intrusion alert prediction is an exploratory area for future research for the purpose of improving the quality of correlation and predicting the next attacker scenario as a proactive step.

Keywords

Attack Scenarios Prediction, Intrusion Alert Prediction, Network Security, NIDS, Real-Time Alert Correlation

Full Text

   

Rosilawati Mohd Rasol ¹, Norhazilan Md Noor ¹, Mazura Mat Din ²

Affiliations
1 Faculty of Civil Engineering, Universiti Teknologi Malaysia 81310 Skudai, Johor Bahru, Johor, MY
2 Faculty of Computing, Universiti Teknologi Malaysia, Skudai, Johor Bahru - 81310, Johor, MY

Abstract

In the oil and gas industry, pipeline is the major transportation medium to deliver the products. MIC has been identified as one of the major causes of underground pipeline corrosion failure and Sulphate Reducing Bacteria (SRB) are the main reason causing MIC, by accelerating corrosion rate. The objectives of this paper is to study the SRB growth namely, Desulfovibrio desulfuricans ATCC 7757 correlating to one of the important environment parameter which is temperature. Thus, a determination of the optimum value for the parameter influencing the corrosion process on the internal pipe of carbon steel grade API X70 is unveiled. This research conducted via laboratory works and One-Factor-at-A-Time (OFAT) method is used for the analysis. The result shows that the SRB growth well at temperature ranging from 20°C to 37°C with the maximum exposure time of 28 days which produce the maximum Cr value of 3.746 mm/year at 37°C. The results in this study prove that the corrosion phenomena on carbon steel by the environment parameter such as temperature and time plays a role in the corrosion process. Furthermore, the study identified that the pitting type of corrosion is detected and accelerated at carbon steel pipe.

Keywords

Corrosion, MIC, Microorganisms, Sulphate Reducing Bacteria (SRB)

Full Text