New Multi-step Worm Attack Model [ Full-Text ]
Y. Robiah, S. Siti Rahayu, S. Shahrin, M. A. Faizal, M. Mohd Zaki, and R. Marliza
The traditional worms such as Blaster, Code Red, Slammer and Sasser, are still infecting vulnerable machines on the internet. They will remain as significant threats due to their fast spreading nature on the internet. Various traditional worms attack pattern has been analyzed from various logs at different OSI layers such as victim logs, attacker logs and IDS alert log. These worms attack pattern can be abstracted to form worms’ attack model which describes the process of worms’ infection. For the purpose of this paper, only Blaster variants were used during the experiment. This paper proposes a multi-step worm attack model which can be extended into research areas in alert correlation and computer forensic investigation.
Role of Interestingness Measures in CAR Rule Ordering for Associative Classifier: An Empirical Approach [ Full-Text ]
S. Kannan and R. Bhaskaran
Associative Classifier is a novel technique which is the integration of Association Rule Mining and Classification. The difficult task in building Associative Classifier model is the selection of relevant rules from a large number of class association rules (CARs). A very popular method of ordering rules for selection is based on confidence, support and antecedent size (CSA). Other methods are based on hybrid orderings in which CSA method is combined with other measures. In the present work, we study the effect of using different interestingness measures of Association rules in CAR rule ordering and selection for associative classifier.
A Holistic Approach to Securing Web Applications [ Full-Text ]
Srdjan Stanković and Dejan Simić
Protection of Web applications is an activity that requires constant monitoring of security threats as well as looking for solutions in this field. Since protection has moved from the lower layers of OSI models to the application layer and having in mind the fact that 75% of all the attacks are performed at the application layer, special attention should be paid to the application layer. It is possible to improve protection of Web application on the level of the system architecture by introducing new components which will realize protection on higher levels of OSI models. This paper deals with Intrusion Detection Systems, Intrusion Prevention Systems, Web Application Firewall and gives a holistic approach to securing Web applications using aforementioned components.
Information criminality – a phenomenon met within the informatics field [ Full-Text ]
C. Filote and G. Nemţoi
The phenomenon described as “information criminality” has taken significant proportions in the last decade, fact that carried out towards an international legislative frame, by implementing judicial forms, which might stop its occurrences. As matter of fact, the information criminality represents an information technology aiming towards fraud and prejudicing the users of informational data, by various means to infringement of the law. In this way, some international organizations have dealt with performing a legislative framework, able to punish the phenomenon of information criminality and implicitly to protect the users of computers. The transnational expansions, extremely fast as concerns the computer networks, and extending the access to these networks, by means of mobile telephony, have brought the increasing of these systems’ vulnerability and the creating of opportunities of breaking the law. Considering these aspects, the world legislation is continuously changing, due to a more and more accelerated development of the information technology.
Randomness Testing of Compressed Data [ Full-Text ]
Weiling Chang, Binxing Fang, Xiaochun Yun, Shupeng Wang and Xiangzhan Yu
Random Number Generators play a critical role in a number of important applications. In practice, statistical testing is employed to gather evidence that a generator indeed produces numbers that appear to be random. In this paper, we reports on the studies that were conducted on the compressed data using 8 compression algorithms or compressors. The test results suggest that the output of compression algorithms or compressors has bad randomness, the compression algorithms or compressors are not suitable as random number generator. We also found that, for the same compression algorithm, there exists positive correlation relationship between compression ratio and randomness, increasing the compression ratio increases randomness of compressed data. As time permits, additional randomness testing efforts will be conducted.
Features Based Text Similarity Detection [ Full-Text ]
Chow Kok Kent and Naomie Salim
As the Internet help us cross cultural border by providing different information, plagiarism issue is bound to arise. As a result, plagiarism detection becomes more demanding in overcoming this issue. Different plagiarism detection tools have been developed based on various detection techniques. Nowadays, fingerprint matching technique plays an important role in those detection tools. However, in handling some large content articles, there are some weaknesses in fingerprint matching technique especially in space and time consumption issue. In this paper, we propose a new approach to detect plagiarism which integrates the use of fingerprint matching technique with four key features to assist in the detection process. These proposed features are capable to choose the main point or key sentence in the articles to be compared. Those selected sentence will be undergo the fingerprint matching process in order to detect the similarity between the sentences. Hence, time and space usage for the comparison process is reduced without affecting the effectiveness of the plagiarism detection.
A Model for Mining Multilevel Fuzzy Association Rule in Database [ Full-Text ]
Pratima Gautam, Neelu Khare and K. R. Pardasani
The problem of developing models and algorithms for multilevel association mining pose for new challenges for mathematics and computer science. These problems become more challenging, when some form of uncertainty like fuzziness is present in data or relationships in data. This paper proposes a multilevel fuzzy association rule mining models for extracting knowledge implicit in transactions database with different support at each level. The proposed algorithm adopts a top-down progressively deepening approach to derive large itemsets. This approach incorporates fuzzy boundaries instead of sharp boundary intervals. An example is also given to demonstrate that the proposed mining algorithm can derive the multiple-level association rules under different supports in a simple and effective manner.
Applying MVC and PAC patterns in mobile applications [ Full-Text ]
D. Plakalović and D. Simić
Additional requirements are set for mobile applications in relation to applications for desktop computers. These requirements primarily concern the support to different platforms on which such applications are performed, as well as the requirement for providing more modalities of input/output interaction. These requirements have influence on the user interface and therefore it is needed to consider the usability of MVC (Model-View-Controller) and PAC (Presentation-Abstraction-Control) design patterns for the separation of the user interface tasks from the business logic, specifically in mobile applications. One of the questions is making certain choices of design patterns for certain classes of mobile applications. When using these patterns the possibilities of user interface automatic transformation should be kept in mind. Although the MVC design pattern is widely used in mobile applications, it is not universal, especially in cases where there are requirements for heterogeneous multi-modal input-output interactions.
Particle Swarm Optimization Based Reactive Power Optimization [ Full-Text ]
P. R. Sujin, T. Ruban Deva Prakash and M. Mary Linda
Reactive power plays an important role in supporting the real power transfer by maintaining voltage stability and system reliability. It is a critical element for a transmission operator to ensure the reliability of an electric system while minimizing the cost associated with it. The traditional objectives of reactive power dispatch are focused on the technical side of reactive support such as minimization of transmission losses. Reactive power cost compensation to a generator is based on the incurred cost of its reactive power contribution less the cost of its obligation to support the active power delivery. In this paper an efficient Particle Swarm Optimization (PSO) based reactive power optimization approach is presented. The optimal reactive power dispatch problem is a non¬linear optimization problem with several constraints. The objective of the proposed PSO is to minimize the total support cost from generators and reactive compensators. It is achieved by maintaining the whole system power loss as minimum thereby reducing cost allocation. The purpose of reactive power dispatch is to determine the proper amount and location of reactive support. Reactive Optimal Power Flow (ROPF) formulation is developed as an analysis tool and the validity of proposed method is examined using an IEEE-14 bus system.
Chaos Models in Economics [ Full-Text ]
Sorin Vlad, Paul Pascu and Nicolae Morariu
The paper discusses the main ideas of the chaos theory and presents mainly the importance of the nonlinearities in the mathematical models. Chaos and order are apparently two opposite terms. The fact that in chaos can be found a certain precise symmetry (Feigenbaum numbers) is even more surprising. As an illustration of the ubiquity of chaos, three models among many other existing models that have chaotic features are presented here: the nonlinear feedback profit model, one model for the simulation of the exchange rate and one application of the chaos theory in the capital markets.
Posynomial Geometric Programming Problems with Multiple Parameters [ Full-Text ]
A. K. Ojha and K. K. Biswal
Geometric programming problem is a powerful tool for solving some special type non-linear programming problems. It has a wide range of applications in optimization and engineering for solving some complex optimization problems. Many applications of geometric programming are on engineering design problems where parameters are estimated using geometric programming. When the parameters in the problems are imprecise, the calculated objective value should be imprecise as well. In this paper we have developed a method to solve geometric programming problems where the exponent of the variables in the objective function, cost coefficients and right hand side are multiple parameters. The equivalent mathematical programming problems are formulated to find their corresponding value of the objective function based on the duality theorem. By applying a variable separable technique the multi-choice mathematical programming problem is transformed into multiple one level geometric programming problem which produces multiple objective values that helps engineers to handle more realistic engineering design problems.
Proposing a New Method for Query Processing Adaption in DataBase [ Full-Text ]
Mohammad-Reza Feizi-Derakhshi, Hasan Asil and Amir Asil
This paper proposes a multi agent system by compiling two technologies, query processing optimization and agents which contains features of personalized queries and adaption with changing of requirements. This system uses a new algorithm based on modeling of users’ long-term requirements and also GA to gather users’ query datas. Experimented Result shows more adaption capability for presented algorithm in comparison with classic algorithms.
Expert System Models in the Companies’ Financial and Accounting Domain [ Full-Text ]
D. Mates, E. Iancu, I. Bostan, and V. Grosu
The present paper is based on studying, analyzing and implementing the expert systems in the financial and accounting domain of the companies, describing the use method of the informational systems that can be used in the multi-national companies, public interest institutions, and medium and small dimension eco-nomical entities, in order to optimize the managerial decisions and render efficient the financial-accounting functionality. The purpose of this paper is aimed to identifying the economical exigencies of the entities, based on the already used accounting instruments and the management software that could consent the control of the economical processes and patrimonial assets.
Spatial Domain Watermarking Scheme for Colored Images Based on Log-average Luminance [ Full-Text ]
Jamal A. Hussein
In this paper a new watermarking scheme is presented based on log-average luminance. A colored-image is divided into blocks after converting the RGB colored image to YCbCr color space. A monochrome image of 1024 bytes is used as the watermark. To embed the watermark, 16 blocks of size 8X8 are selected and used to embed the watermark image into the original image. The selected blocks are chosen spirally (beginning form the center of the image) among the blocks that have log-average luminance higher than or equal the log-average luminance of the entire image. Each byte of the monochrome watermark is added by updating a luminance value of a pixel of the image. If the byte of the watermark image represented white color (255) a value α is added to the image pixel luminance value, if it is black (0) the α is subtracted from the luminance value. To extract the watermark, the selected blocks are chosen as the above, if the difference between the luminance value of the watermarked image pixel and the original image pixel is greater than 0, the watermark pixel is supposed to be white, otherwise it supposed to be black. Experimental results show that the proposed scheme is efficient against changing the watermarked image to grayscale, image cropping, and JPEG compression.
Mapping of SOA and RUP: DOA as Case Study [ Full-Text ]
Shahid Hussain, Sheikh Muhammad Saqib, Bashir Ahmad and Shakeel Ahmad
SOA (Service Oriented Architecture) is a new trend towards increasing the profit margins in an organization due to incorporating business services to business practices. Rational Unified Process (RUP) is a unified method planning form for large business applications that provides a language for describing method content and processes. The well defined mapping of SOA and RUP leads to successful completion of RUP software projects to provide services to their users. DOA (Digital Office Assistant) is a multi user SOA type application that provides appropriate viewer for each user to assist him through services. In this paper authors proposed the mapping strategy of SOA with RUP by considering DOA as case study.
Interestingness Measure for Mining Spatial Gene Expression Data using Association Rule [ Full-Text ]
M. Anandhavalli, M. K. Ghose, and K. Gauthaman
The search for interesting association rules is an important topic in knowledge discovery in spatial gene expression databases. The set of admissible rules for the selected support and confidence thresholds can easily be extracted by algorithms based on support and confidence, such as Apriori. However, they may produce a large number of rules, many of them are uninteresting. The challenge in association rule mining (ARM) essentially becomes one of determining which rules are the most interesting. Association rule interestingness measures are used to help select and rank association rule patterns. Besides support and confidence, there are other interestingness measures, which include generality reliability, peculiarity, novelty, surprisingness, utility, and applicability. In this paper, the application of the interesting measures entropy and variance for association pattern discovery from spatial gene expression data has been studied. In this study the fast mining algorithm has been used which produce candidate itemsets and it spends less time for calculating k-supports of the itemsets with the Boolean matrix pruned, and it scans the database only once and needs less memory space. Experimental results show that using entropy as the measure of interest for the spatial gene expression data has more diverse and interesting rules.
Mathematical Modeling to Study the Dynamics Of A Diatomic Molecule N2 in Water [ Full-Text ]
Nitin Sharma and Madhvi Shakya
In the present work an attempt has been made to study the dynamics of a diatomic molecule N2 in water. The proposed model consists of Langevin stochastic differential equation whose solution is obtained through Euler’s method. The proposed work has been concluded by studying the behavior of statistical parameters like variance in position, variance in velocity and covariance between position and velocity. This model incorporates the important parameters like acceleration, intermolecular force, frictional force and random force.
3D Skull Recognition Using 3D Matching Technique [ Full-Text ]
Hamdan O. Alanazi, B. B. Zaidan, and A. A. Zaidan
Biometrics has become a “hot” area. Governments are funding research programs focused on biometrics. In this paper the problem of person recognition and verification based on a different biometric application has been addressed. The system is based on the 3DSkull recognition using 3D matching technique, in fact this paper present several bio-metric approaches in order of assign the weak point in term of used the biometric from the authorize person and insure the person who access the data is the real person. The feature of the simulate system shows the capability of using 3D matching system as an efficient way to identify the person through his or her skull by match it with database, this technique grantee fast processing with optimizing the false positive and negative as well .
Hybrid Medical Image Classification Using Association Rule Mining with Decision Tree Algorithm[ Full-Text ]
P. Rajendran and M. Madheswaran
The main focus of image mining in the proposed method is concerned with the classification of brain tumor in the CT scan brain images. The major steps involved in the system are: pre-processing, feature extraction, association rule mining and hybrid classifier. The pre-processing step has been done using the median filtering process and edge features have been extracted using canny edge detection technique. The two image mining approaches with a hybrid manner have been proposed in this paper. The frequent patterns from the CT scan images are generated by frequent pattern tree (FP-Tree) algorithm that mines the association rules. The decision tree method has been used to classify the medical images for diagnosis. This system enhances the classification process to be more accurate. The hybrid method improves the efficiency of the proposed method than the traditional image mining methods. The experimental result on prediagnosed database of brain images showed 97% sensitivity and 95% accuracy respectively. The physicians can make use of this accurate decision tree classification phase for classifying the brain images into normal, benign and malignant for effective medical diagnosis.
A Noise Addition Scheme in Decision Tree for Privacy Preserving Data Mining [ Full-Text ]
Mohammad Ali Kadampur and Somayajulu D.V.L.N.
Data mining deals with automatic extraction of previously unknown patterns from large amounts of data. Organizations all over the world handle large amounts of data and are dependent on mining gigantic data sets for expansion of their enterprises. These data sets typically contain sensitive individual information, which consequently get exposed to the other parties. Though we cannot deny the benefits of knowledge discovery that comes through data mining, we should also ensure that data privacy is maintained in the event of data mining. Privacy preserving data mining is a specialized activity in which the data privacy is ensured during data mining. Data privacy is as important as the extracted knowledge and efforts that guarantee data privacy during data mining are encouraged. In this paper we propose a strategy that protects the data privacy during decision tree analysis of data mining process. We propose to add specific noise to the numeric attributes after exploring the decision tree of the original data. The obfuscated data then is presented to the second party for decision tree analysis. The decision tree obtained on the original data and the obfuscated data are similar but by using our method the data proper is not revealed to the second party during the mining process and hence the privacy will be preserved.
Simultaneous SNR up gradation, blind channel equalization and phase recovery of transmitted signals using Autocorrelation Matching method [ Full-Text ]
Sunita Panda, S. M. Rout, M. Singh, U. Mishra, S. K. Routray and S. P. Panigrahi
The Autocorrelation Matching (AM) method is a second order statistics-based blind MIMO FIR channel equalization technique designed for wireless communication systems using multiple receiving antennas. This paper presents a new cost function and an algorithm for up gradation of SNR in blind channel equalization as well as phase recovery of QAM signals at the same time. Extensive simulation results show that SNR upgraded from the existing methods and at the same time phase of received signal recovered properly.