The need for efficient intrusion detection systems increases every day to protect network traffic against emerging attacks. Unfortunately, increasing network speeds and number of signatures makes it harder for the existing signature-based intrusion detection systems to keep up. This makes those systems the weak link and the bottleneck which decreases the overall network performance. Researchers found that 30%–60% of the overall processing time of signature-based intrusion detection systems is spent on pattern matching operations [1]. In this paper, we present a novel and fast software-based pattern matching algorithm to reduce the number of times to perform pattern matching. This new algorithm introduces an exclusion-inclusion filter programmed only with signatures prefixes. It filters out the clean traffic without requiring pattern matching and weeds out suspicious packets to be searched using a specially modified Wu-Manber pattern matching algorithm. The exclusion-inclusion filter is a modified Bloom filter that produces a list of probable matching signatures for each suspect packet. The remaining few suspicious packets are searched only for the probable matches. Compared to the Wu-Manber algorithm used in intrusion detection systems, the experimental results indicate a speed up of 3.4 times on average, 5.5 times for regular traffic, and 1.6 times for worst case traffic. The memory overhead added by the algorithm was limited to 0.11%.

/pdf/exscind-fast-pattern-matching-for-intrusion-detection-using-1rk6pfce3s.pdf

Exscind: Fast pattern matching for intrusion detection using exclusion and inclusion filters

The WM-q multiple exact string matching algorithm for DNA sequences

Compressing web traffic using standard GZIP is becoming both popular and challenging due to the huge increase in wireless web devices, where bandwidth is limited. Security and other content based networking devices are required to decompress the traffic of tens of thousands concurrent connections in order to inspect the content for different signatures. The overhead imposed by the decompression inhibits most devices from handling compressed traffic, which in turn either limits traffic compression or introduces security holes and other dysfunctionalities. The ACCH algorithm [1] was the first to present a unified approach to pattern matching and decompression, by taking advantage of information gathered in the decompression phase to accelerate the pattern matching. ACCH accelerated the DFA-based Aho-Corasick multi-pattern matching algorithm. In this paper, we present a novel algorithm, SPC (Shift-based Pattern matching for Compressed traffic) that accelerates the commonly used Wu-Manber pattern matching algorithm. SPC is simpler and has higher throughput and lower storage overhead than ACCH. Analysis of real web traffic and real security devices signatures shows that we can skip scanning up to 87.5% of the data and gain performance boost of more than 51% as compared to ACCH. Moreover, the additional storage requirement of the technique requires only 4KB additional information per connection as compared to 8KB of ACCH.

/pdf/shift-based-pattern-matching-for-compressed-web-traffic-4uhnfnor9m.pdf

Shift-based pattern matching for compressed web traffic

The internet revolution has made the digital information easy to capture, process, store, distribute, and transmit. There is a significant development in computation and related technologies. In different walks of life, there is ever expanding usage of these technologies. As a result there is a continuous collection and storage of huge amount of data of diverse characteristics in data bases. It is indeed a challenge for the retrieval of information from this enormous amount of data. The information retrieval is an attempt to make sense of the information explanation embedded in this huge volume of data. All these aspects suggest the need of intelligent data retrieval methodologies for the retrieval of useful information. In this paper, as a concurrent information retrieval system (IRS) with multiple pattern multiple (
 $$2^\mathrm{N})$$
 shaft sequential and parallel string matching algorithms is proposed. The proposed approach concurrently retrieves the searching information from huge volume of data. Experimental results have shown that the proposed string matching algorithms reduced the search time very well in both the sequential and parallel environments.

Concurrent Information Retrieval System (IRS) for Large Volume of Data with Multiple Pattern Multiple ($2^\mathrm{N}$) Shaft Parallel String Matching

String matching algorithms is become one of the most important topic in the computer science world. These algorithms are used in many real world problems like as scanning the threat in intrusion detection system, finding the pattern in text mining, match the similarity of the document in the plagiarism detection system, recognition in bio informatics and so on. String Matching Algorithms are broadly categorized into single pattern string matching and multiple pattern string matching algorithms. To get the faster solution of the problem most of the cases multiple pattern matching is the best choice. Aho-Corasick, Shift-OR, Robin Karp but Wu Manber Algorithm is better choice because it search the pattern faster(take less time) as well as occupies less space. This paper discus the various pit falls of the wu manber algorithm with their detailed explanation. Also discuss the various improved wu manber algorithm and comparison between these algorithms.

/pdf/a-comparative-study-of-wu-manber-string-matching-algorithm-g3ul10feit.pdf

A Comparative Study of Wu Manber String Matching Algorithm and its Variations

Wu-Manber is a widely used multiple patterns matching algorithm. But in practical application, it exist the following limitations. First, there are redundant information and operations. Second, the prefix table is established, but is hardly used. Third, need to traverse the whole link list. These limitations make the algorithm complicated and affect the performance of it. Though some limitations have been indicated by others, different ways are taken in this paper. Prefix table is used to filter the patterns. Address filtering based search method avoids traversing the whole link list. Experimental result shows that the improved algorithm has a good performance than the original one.

Address Filtering Based Wu-Manber Multiple Patterns Matching Algorithm

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Address Filtering Based Wu-Manber Multiple Patterns Matching Algorithm