I V Viswanathan

Suresh P

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 ISSN : 2347 - 8446 (Online)
 ISSN : 2347 - 9817 (Print)
www.ijarcst.com
International Journal of Advanced Research in
Computer Science & Technology (IJARCST 2014)
© 2014, IJARCST All Rights Reserved 48
Vol. 2   Issue Special 1  Jan-March 2014 
A Systemfor High Throughput Performanceand Reduce Low 
Memoryusing Pattern Matching with Hash Key
IViswanathan.V, IISuresh.P
IPG Student, IIAssociate Professor
I,IIDept. of CSE, Sethu Institute of Technology, Affiliated Anna University Kariapatti
I. Introduction
In the recent decades, network security is very important to avoid 
the unauthorized access. Network security consists of the policies 
and provision adopted by administrator to prevent the unauthorized 
access, monitoring the network by maintaining traffic protecting 
the data and network resources.Pattern matching techniques have 
been recently applied to network security application such an 
intrusion detection virus production and spam filter. In a wider 
sense the techniques has been using for information retrieval, 
text editing by applying signature matching and to help detect 
malicious attackers against network. Pattern matching used in data 
mining for information retrieval.But are not suitable for matching 
multiple.In traditional symmetric-key encryption schemes, a user 
encrypts a message so that only the owner of the corresponding 
secret key can decrypt it. Decryption is all-or-nothing”; that 
is, with the key one can decrypt the message completely, and 
without the key one learns nothing about the message. Pattern 
matching is the act of checking a perceived sequence of tokens 
for the presence of the constituents of some pattern. In contrast to 
pattern recognition, the match usually has to be exact. The patterns 
generally have the form of either sequences or tree structures. Uses 
of pattern matching include outputting the locations (if any) of a 
pattern within a token sequence, to output some component of the 
matched pattern, and to substitute the matching pattern with some 
other token sequence (i.e., search and replace).Using a traditional 
encryption scheme, any global query on the data would require 
retrieving and decrypting the entire original data, negating many 
of the advantages of cloud storage. Then, using the secret key, the 
client can issue a query q by executing an interactive protocol with 
the server. For example, for pattern matching queries, a query q is a 
pattern string, the message M is a string, and F (M; q) returns the set 
of indices of all occurrences of q as a substring of M.For security, 
i think of the server as an adversary trying to learn information 
about the message and the queries. Ideally, I would like that an 
adversary that is given a cipher text and that engages in query 
protocols for several queries learns nothing about the message or 
the queries. Security that specifies explicitly what information is 
leaked, and guarantee that an adversary learns nothing more than 
the speed leakage. In the malicious model, the adversary tries to 
learn information, possibly by not following the protocol honestly.
Pattern matching encryption. Constructing a pattern matching 
encryption scheme, that is, a query able encryption scheme that 
support pattern matching queries {given a string s and a pattern 
string p, return all occurrences of p as a substring of s. In the 
genomic data application, for example, researchers may wish to 
query the database to determine whether a particular cancer marker 
sequence appears in any of the data.For efficiency, our goal is for 
space and computation complexity to be comparable to that of 
evaluating pattern matching queries in the unencrypted setting. 
By focusing on the specific functionality of pattern matching 
queries and achieves a scheme with much better efficiency. To 
construct a pattern matching encryption scheme, use suffix trees, 
a data structure used to efficiently perform pattern matching on 
unencrypted data. Combine basic symmetric-key primitives to 
develop a method that allows traversal of select edges in a suffix 
tree in order to efficiently perform pattern  matching on encrypted 
data, without revealing significant information about the string 
or the queries.
To obtain High throughputs (stateful and parallel processing) to 
reduce Storage of Aho-Corasick algorithm Stateful nature of Aho-
Corasick algorithm reduce repeated pattern matching. It stores the 
previous results. Parallel processing provides High speed. The 
existing algorithms are efficient for single-pattern matching, but 
are not suitable for matching multiple patterns. The AC algorithm 
pre-processes the patterns builds a finite automation that can match 
multiple pattern simultaneously, but may require a huge amount 
of memory space to do so. However, even with the linear-time 
worst- case performance guarantee, the throughput of the AC 
algorithm cannot keep up with transmission speeds in high-speed 
networks. The proposed verification engine, which is modification 
of the ac automation, checks all candidate patterns simultaneously 
rather than sequentially. Proposed stateful pre-filter is suitable for 
pattern of moderate or large lengths. The stateful pre-filter concept 
and present an AC-based verification engine that can check all 
candidate patterns simultaneously.
II. Related Work
The existing algorithms are efficient for single-pattern matching, 
but are not suitable for matching multiple patterns. The AC 
algorithm pre-processes the patterns builds a finite automation 
that can match multiple pattern simultaneously, but may require 
a huge amount of memory space to do so.however, even with the 
linear-time worst- case performance guarantee, the throughput 
of the AC algorithm cannot keep up with transmission speeds in 
high-speed networks.
Abstract
Pattern matching is one of the most critical elements because it allows for the system to make decisions based not just on the headers, 
but the actual content flowing through the network. Network Intrusion detection and Prevention systems have emerged as one of 
the most effective ways of providing security to those connected to the network, and at the heart of almost every modern intrusion 
detection system is a pattern matching algorithm. I have developed an approach that relies on a special purpose architecture that 
executes novel pattern matching algorithms specially optimized for implementation in our design.
Keywords
Pattern Matching, Hash Key, Resource allocation, Auction, Utility Computing
 ISSN : 2347 - 8446 (Online)
 ISSN : 2347 - 9817 (Print)
www.ijarcst.com
International Journal of Advanced Research in
Computer Science & Technology (IJARCST 2014)
© All Rights Reserved, IJARCST 201449
Vol. 2   Issue Special 1  Jan-March 2014 
A. Literature Review
Bremler-Barr,Y.Harchol,etal(2011) has presented “Space-time 
tradeoffs in software-based Deep packet inspection”. In this paper 
the state elimination procedure is proposed state elimination 
procedure is following if:1)it is a single-child state.2)there is no 
incoming failure transition to it.Another effective compression 
technique called leaf compression, eliminates leaf states with 
two modification;1)Pushing the indication of the match to the 
penultimate state.2) Copying the failure transitions of leaf states to 
the corresponding penultimate states as their new goto transitions. 
This compression technique use to reduces the transition table 
section and achieving 60% comparable throughput.
Y.E.Yang,H.Le et al(2010)has presented “High performance 
dictionary-based string matching for deep packet inspection”. 
This paper describes about throughput of pattern matching.AC 
algorithm cannot keep up with transmission speeds in high speed 
networks in WM(Hash-AV Clam-AV)algorithm pre-filter was 
implemented as a shift table, and the verification engine checks all 
candidate pattern sequentially when a potential starting position 
is identified. The proposed architecture consists of pre-filter and 
verification engine. Once a suspicious starting position is found, 
the verification engine conform true pattern occurrence.
N.S.Artan and H.I.Chao et al(2008)has presented”Boundary Hash 
for Memory-Efficient Deep Packet Inspection Network Intrusion 
Detection and Prevention Systems(NIDPS)are critical for network 
security”. Deep Packet Inspection (DPI) is at the heart of these 
NIDPSs.DPI is the detection of malicious packets by comparing 
the packet payloads against excerpts from known intrusion packet. 
I refer this paper for signature verification process.
K.Sinkar,J.Patel,et al(2007)has presented ”Aggregated bloom 
filter for intrusion detection and prevention hardware”.Aggregated 
Bloom Filter(ABFs) to increase the throughput and scalability 
of BFs. The proposed ABF has two methods to improve average 
speed and scalability. First, to remove redundancy, the hash 
functions for each query are calculated sequentially. As soon 
as I have a no match in any of the hash results, the query is 
immediately abandoned. I refer this paper for our proposed Pre-
filter construction. 
III. Proposed System
The proposed verification engine, which is modification of the 
ac automation, checks all candidate patterns simultaneously 
rather than sequentially. Proposed stateful pre-filter is suitable 
for pattern of moderate or large lengths. The stateful pre-filter 
concept and present an AC-based verification engine that can 
check all candidate patterns simultaneously.
A. Resource Allocation
In the efficient and responsive economic resource allocation in 
high-performance computing environments. While economic 
resource allocation provides a well-studied and efficient means 
of scalable decentralized allocation it has been stereotyped as a low 
performance solution due to the resource commitment overhead 
and latency in the allocation process. The high utilization strategies 
proposed in this paper are designed to minimize the impact of these 
factors to increase occupancy and improve system utilization.
B. Utility Computing  
Utility computing models have long been the focus of academic 
research, and with the recent success of commercial cloud 
providers, computation and storage is finally being realized as 
the fifth utility. Computational economies are often proposed as 
an efficient means of resource allocation. However adoption has 
been limited due to a lack of performance and high overheads. 
In this paper, we address the performance limitations of existing 
economic allocation models by defining strategies to reduce the 
failure and reallocation rate, increase occupancy and thereby 
increase the obtainable utilization of the system.
C. Auction
Reducing the duration of the auction. The problem with this 
approach is that there is minimal time for providers to discover 
the auction and to compute their bids.. Bid as late as possible. 
The advantage with this approach is that providers can compute 
their bids with the most up to date resource state and resources 
are reserved for a shorter time. The primary problem with this 
approach is time sensitivity, the auction can be missed if the bid 
is too late or experiences unexpected network delays.
Existing Architecture System
Fig. 3.1 existing architecture
Proposed Architecture System
Fig. 3.2 proposed architecture
IV. Performance Evolution
This graph shows the packet delivery ratio. The packet delivery 
ratio graph consists of time as X axis and delivery ratio as a Y 
axis. In existing system, when the time is increase the delivery 
ratio is said to be reduces. In the proposed system, when the time 
is increase the delivery ratio is said to be increases. So in the 
proposed system the delivery of packet is said to be faster and 
 ISSN : 2347 - 8446 (Online)
 ISSN : 2347 - 9817 (Print)
www.ijarcst.com
International Journal of Advanced Research in
Computer Science & Technology (IJARCST 2014)
© 2014, IJARCST All Rights Reserved 50
Vol. 2   Issue Special 1  Jan-March 2014 
higher than the existing system.
Fig. 4.1 packet delivery ratio
Fig 4.2 security
This graph shows the security performance. The security graph 
consists of time as X axis and security valve as a Y axis. In existing 
system, when the time increase the security is said to be reduces. 
In the proposed system, when the time is increases the security 
is also said to be increases. So in the proposed system the data is 
said to be well secured than the existing system.
Fig 4.3 Throughput
This graph shows the security throughput performance. The 
throughput graph consists of time as X axis and throughput 
valve as a Y axis. In existing system, when the time increase the 
throughput is said to be reduces. In the proposed system, when 
the time is increases the throughput is also said to be increases. 
So in the proposed system the throughput is said to be higher than 
the existing system.
Packet delivery Security Throughput
Fig. 4.4 Comparison between Proposed and Existing system
Table 1. Comparison between Proposed and Existing System
System Packet Delivery Security Throughput
Existing 22.5 20.4 34.2
Proposed 38.7 52.3 79.8
V. Conclusion
In my paper,I propose a pattern- matching framework in that, 
requirement of memory is low and throughput of my system is 
high. In my framework, I introduce the concept named as stateful 
pre-filter and I introduce an AC-based verification engine, its 
used to verify all applicant patterns concurrently. The stateful 
framework performs the finest in both memory requirement and 
throughput. The Proposed stateful framework is the favoriteresult 
for both memory requirements and throughput. A well throughput 
performance is offered by larger search window. The length of 
the shortest pattern is used to increase the length of the search 
window. 
VI. Future Enhancement
In future the throughput is said to increase and even the memory 
is low the message is easily transferred by using the hash key 
algorithm. Hash key used for encrypt and decrypt. In this 
attackers are not able to easily access the data. The individual 
strategy, and the combination of the different strategies, was 
shown to dramatically improve occupancy and utilization in a 
high performance situation.  The increase in allocation rate was 
shown to be up to 286 percent for the dynamic workloads and 
109 percent for the batch model.
VII. Acknowledgement
References
[1] A.Bremler-Barr,Y.Harchol,”Space-time tradeoffs in 
software-based deep packet inspection” in Proc.IEEE 
 ISSN : 2347 - 8446 (Online)
 ISSN : 2347 - 9817 (Print)
www.ijarcst.com
International Journal of Advanced Research in
Computer Science & Technology (IJARCST 2014)
© All Rights Reserved, IJARCST 201451
Vol. 2   Issue Special 1  Jan-March 2014 
HPSR,2011,pp.1-8.
[2] Y.Yang,H.Le”Highperformance dictionary-based string 
matching for deep packet inspection,”inProc.IEEE 
INFOCOM,2010,pp.1-5.
[3] N.S.Artan,M.Bando,”Boundary hash for memory 
efficient deep packet inspection,”in Proc. IEEE ICC,May 
2008,pp.1732-1737.
[4] M.Bando,H.J.Chao,“Highlymemory-efficient loglog 
hash for deep packet inspection,”inProc.IEEE 
GLOBECOM,2008,pp.1-6.
[5] Y.Haowei and H.J.Chao,”A dynamic load balanced 
hashing scheme for networking applications,”inProc.IEEE 
GLOBECOM,2008,pp.1-6.
[6] K.Sinkar,J.Patel,”Aggregated bloom filters for intrusion 
detection and prevention hardware,”inProc.IEEE 
GLOBECOM,Nov.2007,pp.349-354.
[7] N.S.Artan and H.J.Chao,”Trie bitmap content analyzer 
for high-speed network intrusion detection,”inProc.
IEEEINTOCOM,May 2007,pp125-133.
[8] S.Dharmapurikar and J.Lockwood,”fast and scalable pattern 
matching for network intrusion detection systems,”IEEE 
Oct.2006,pp1781-1792.
[9] L.Tan and T. Sherwood”A high throughput string matching 
architecture for intrusion detection and prevention,”in Proc.
IEEE,2005,pp.112-122.
[10] R.Ghosh and G.Yanchuan,”A 10-Gbps high speed single-chip 
network intrusion detection and prevention system,”inProc.
IEEE GLOBECOM,Nov.2007,pp.343-348.
[11] N.S.Artan and H,J.Chao,”Multi-packet signature 
detection using prefix bloom filters,”inProc.IEEE 
GLOBECOM,2005,pp.1811-1816.
Author’s Profile and Image
V.Viswanathan received his Bachelor 
of Technology degree in Information 
Technology from Anna University, 
Chennai. He is currently pursuing his 
Master degree in Computer Science 
and Engineering from Sethu Institute of 
Technology, Under the control of Anna 
university Chennai. My area of interest 
includes networking.
P.Sureshreceived his Master degree in 
Computer Science and Engineering 
from Anna University. He is currently 
pursuing his PhD degree. He currently 
is working as an Associate Professor in 
Sethu Institute of Technology. His area 
of interest includes data structures and 
programming languages. 


A Systemfor High Throughput Performanceand Reduce Low Memoryusing Pattern Matching with Hash Key

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A Systemfor High Throughput Performanceand Reduce Low Memoryusing Pattern Matching with Hash Key

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