Volume 1 Number 3 December 2011
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A Modified Algorithm for Generating Single Dimensional Fuzzy Itemset Mining Abstract: Mining frequent itemsets from transaction database is a fundamental task for Association Rules. Apriori algorithm is an influential algorithm for mining frequent itemsets using Boolean values. There are different motivations for a fuzzy approach to Association Rule Mining. An Algorithm for Generating Single Fuzzy Association Rule Mining is based on human intuitive such as the larger number of items purchased in a transaction means that the degree of association among the items in the transaction may be lowered. The proposed approach modifies the above said Fuzzy Association Rule Mining algorithm and compares Apriori and the mentioned Fuzzy Association Rule Mining algorithm. The proposed approach calculates the support value based on fuzzy t-norm namely intersection and finds the subsets of a frequent itemset partially. Therefore, it reduces the complexion of finding each subset of a frequent itemset. |
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Area Compactness Architecture for Elliptic Curve Cryptography Abstract: Elliptic curve cryptography (ECC) is an alternative to traditional public key cryptographic systems. Even though, RSA (Rivest-Shamir-Adleman) was the most prominent cryptographic scheme, it is being replaced by ECC in many systems. This is due to the fact that ECC gives higher security with shorter bit length than RSA. In Elliptic curve based algorithms elliptic curve point multiplication is the most computationally intensive operation. Therefore implementing point multiplication using hardware makes ECC more attractive for high performance servers and small devices. This paper gives the scope of Montgomery ladder computationally. Montgomery ladder algorithm is effective in computation of Elliptic Curve Point Multiplication (ECPM) when compared to Elliptic Curve Digital Signature Algorithm (ECDSA). Compactness is achieved by reducing data paths by using multipliers and carry-chain logic. Multiplier performs effectively in terms of area/time if the word size of multiplier is large. A solution for Simple Power Analysis (SPA) attack is also provided. In Montgomery modular inversion 33% of saving in Montgomery multiplication is achieved and a saving of 50% on the number of gates required in implementation can be achieved. |
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Neural Network Based Steganalysis Framework to Detect Stego-Content in Corporate Emails Abstract: Today, email management is not only a filing and storage challenge. Because law firms and attorneys must be equipped to take control of litigation, email authenticity must be unquestionable with strong chains of custody, constant availability, and tamper-proof security. Information Security and integrity are becoming more important as we use email for personal communication and business. Email is insecure. This steganalysis framework checks the inbox content of the corporate mails by improving the S-DES algorithm with the help of neural network approach. A new filtering algorithm is also developed which will used to extract only the JPG images from the corporate emails. This frame work developed a new steganalysis algorithm based on neural network to get statistical features of images to identify the underlying hidden data. The Experimental results indicate this method is valid in steganalysis. This method will be used for Internet/network security, watermarking and so on. |
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Clustering of datasets using PSO-K-Means and PCA-K-means Abstract: Cluster analysis plays indispensable role in obtaining knowledge from data, being the first step in data mining and knowledge discovery. The purpose of data clustering is to reveal the data patterns and gain some initial insights regarding data distribution. K-means is one of the widely used partitional clustering algorithms and it is more sensitive to outliers and do not work well with high dimensional data. In this paper, K-means has been integrated with other approaches to overcome the shortcomings hereby improving the accuracy of clustering. In this paper, basic k-means and the combination of k-means with PCA and PSO are applied on various datasets from UCI repository. The experimental results of this paper show that PSO-K-means and PCA-K-Means improves the performance of basic K-means in terms of accuracy and computational time. |
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A Team Multicast Routing Protocol for Mobile Ad Hoc Networks Abstract: Team multicast identifies clusters of nodes with same affinity as teams and manages the multicast membership information using the unit of team rather than dealing with individual node members. The source propagates a data packet to each subscribed team’s leader and each leader forwards the data to the entire team. But none of the existing work on team multicasting consider the QoS metrics of the team leader like power, bandwidth etc. In this paper, we propose a QoS-aware team multicast protocol for MANETs, which gives a better solution to the above said problems. In our proposed protocol, the team leaders are selected based on the QoS metrics like bandwidth, residual energy and stability. Thus, the problem of link breakage can be reduced proactively. In case of link breakage occurring at any place of the network, a new team leader is selected in reactive basis. This avoids the delay in route repair mechanism. By simulation results, we show that the proposed protocol achieves better packet delivery ratio with reduced delay and overhead. |
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Image processing technique for the Evaluation of Biological specimen using Laser speckle pattern Abstract: This work presents a study of biospeckle image correlation for the assessment of lemon fruit. This is a non-destructive and non-invasive optical technique. The study was carried out recording the temporal history of the speckle pattern obtained by illuminating the surface of the fruit with a laser beam. The biological activity of biomaterial has been inferred from the changes of intensity fluctuations with respect to time. These changes have been measured through correlation functions. Biospeckle analysis using Digital image correlation reflects the state of the investigated object. |
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Decentralized Computation of Attack Discovery using Relational Databases Abstract: Intrusion detection system for relational database is responsible for issuing a suitable response to an anomalous request. We propose the notion of database response policies to support our intrusion response system tailored for a DBMS. Our interactive response policy language makes it very easy for the database administrators to specify appropriate response actions for different circumstances depending upon the nature of the anomalous request. The two main issues that we address in context of such response are that of data matching, and data administration. We propose a novel Joint Threshold Administration Model (JTAM) that is based on the principle of separation of duty. The key idea in JTAM is that a policy object is jointly administered by at least k database administrator (DBAs), that is, any modification made to a policy object will be invalid unless it has been authorized by at least k DBAs. We present design details of JTAM which is based on a cryptographic threshold signature scheme, and show how JTAM prevents malicious modifications to policy objects from authorized users. We also implement JTAM in the PostgreSQL DBMS, and report experimental results on the efficiency of our techniques. |
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Multiple Task Migration in Mesh Network on Chips over virtual Point-to-Point connections Abstract: Multiple task migration is a process in network on chips are able to transfer the data from one cluster to another cluster, while transfer the data from one cluster to another cluster message latency, migration latency, Network latency and power consumption are problem encountered. New techniques are introduced likehybrid scheme, virtual point to point Connections (VIPs) has been introduced that dedicates low power and low latency heavy communication flow created by multiple task migration mechanism. The proposed system scheme reduces total message latency, total migration latency, total network latency, power saving is achieved compared to the previously proposed task migration strategy for mesh multicomputer. Analyzing the results show that the proposed scheme reduces message latency by 16% and migration latency by 15%, while 13% power savings can be achieved. |
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Recent Developments in Signal Encryption – A Critical Survey Abstract: In digitally modern world, the fundamental issue of multimedia data security (such as digital audio signals, images, and videos) is becoming a major concern due to the rapid development of digital communications and networking technologies. The methods and algorithms which are currently available for data protection uses cryptographic primitives for secure data transmission and reception by assuming that both sides must trust on each other. Nowadays, the range of cryptography applications have been expanded a lot in the modern area after the development of communication means; cryptography is essentially required to ensure that data are protected against penetrations and to prevent espionage. The major two conceptual blocks of cryptography is encryption and decryption. This is achieved by sending encrypted version of the data to the untrusted computers to process. Once when the computation process is completed on the encrypted data, the results will be sent back and the decryption is applied to extract the original data content. To ensure the decrypted result to be equal to the intended computed value, a structural method of encryption should be followed. Encryption is a technique which maintains confidentiality while sending and receiving data or storing the information. The principle of Kerckoffs’ on the encryption states that the security must not rely on the obfuscation of code, but only on the secrecy of the decryption key. In this paper detailed description of symmetric and asymmetric encryption are given to provide a wider view of encryption techniques. The field of secure signal processing poses significant challenges for both signal processing and cryptography research; only few ready-to-go fully integrated solutions are available. |
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Analysis and Implementation of a Low Power/High Speed 64 point pipeline FFT/IFFT Processor Abstract: For hardware implementations, the various FFT processors available are mainly classified into memory-based and pipeline architecture. A pipelined FFT/IFFT processor is efficiently implemented in this paper. The pipelined FFT is viewed as the leading architecture for real time applications. The design adopts a single-path delay feedback style as the proposed hardware architecture, since the single delay feedback (SDF) pipeline FFT is good in its requiring less memory space (about N-1 delay elements) and its easy multiplication computation and the ease of design of control unit. Thus a pipelined FFT architecture accounts for both low power consumption and high speed of operation. To eliminate the read-only memories (ROM’s) used to store the twiddle factors, the proposed architecture applies a reconfigurable complex multiplier and bit-parallel multipliers to achieve a ROM-less FFT/IFFT processor, thus consuming lower power than the existing works. This proposed architecture is suited for the power-of-2 radix style of FFT/IFFT processors. |
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Thermal Instability of Non-Newtonian Fluid with uniform Magnetic field in a NON-Rotating Medium Abstract: The thermal instability of a Non-Newtonian fluid in the presence of uniform magnetic field in a non-rotating medium is considered. For the case of stationary convection, fluid behaves like a Newtonian fluid. It is found that the magnetic field has both stabilizing and destabilizing effects. |
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PSO Aided Adaptive Multiscale Products Thresholding for Magnetic Resonance Images Abstract: Edge-preserving denoising is an important task in medical image processing. In this paper a wavelet-based multiscale products thresholding scheme for noise suppression of magnetic resonance images optimized by PSO algorithm has been proposed. To exploit the wavelet inter scale dependencies, adjacent wavelet subbands are multiplied to enhance edge structures while weakening noise. In the multiscale products, edges can be effectively distinguished from noise and an adaptive threshold is calculated and imposed on the products, instead on the wavelet coefficients, to identify an important feature which is optimized by PSO algorithm. Experiments show that the proposed scheme is better optimized and suppresses noise and preserves edges than other wavelet-thresholdingdenoising methods. |