GDPI: Signature based Deep Packet Inspection using GPUs

Deep Packet Inspection (DPI) is necessitated for many networked application systems in order to prevent from cyber threats. The signature based Network Intrusion and etection System (NIDS) works on packet inspection and pattern matching mechanisms for the detection of malicious content in network tr...

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Bibliographic Details
Published in:International journal of advanced computer science & applications 2017-01, Vol.8 (11)
Main Authors: Shoaib, Nausheen, Shamsi, Jawwad, Mustafa, Tahir, Zaman, Akhter, ul, Jazib, Gohar, Mishal
Format: Article
Language:English
Subjects:
Algorithms
Communications traffic
Computer science
Cybersecurity
Data centers
Efficiency
Graphics processing units
High speed
Inspection
Intrusion detection systems
Machine learning
Network latency
Pattern matching
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Summary:Deep Packet Inspection (DPI) is necessitated for many networked application systems in order to prevent from cyber threats. The signature based Network Intrusion and etection System (NIDS) works on packet inspection and pattern matching mechanisms for the detection of malicious content in network traffic. The rapid growth of high speed networks in data centers demand an efficient high speed packet processing mechanism which is also capable of malicious packets detection. In this paper, we proposed a framework GDPI for efficient packet processing which inspects all incoming packet’s payload with known signature patterns, commonly available is Snort. The framework is developed using enhanced GPU programming techniques, such as asynchronous packet processing using streams, minimizing CPU to GPU latency using pinned memory and zero copy, and memory coalescing with shared memory which reduces read operation from global memory of the GPU. The overall performance of GDPI is tested on heterogeneous NVIDIA GPUs, like Tegra Tk1, GTX 780, and Tesla K40 and observed that the highest throughput is achieved with Tesla K40. The design code of GDPI is made available for research community.
ISSN:2158-107X
2156-5570
DOI:10.14569/IJACSA.2017.081128