A Data Mining Approach for Data Generation and Analysis for Digital Forensic Application

Bhat, Veena H.; Rao, Prasanth G.; Abhilash, R; Shenoy, P. Deepa; Venugopal, K. R.; Patnaik, L. M.

doi:10.7763/ijet.2010.v2.140

Cited by 21 publications

(10 citation statements)

References 4 publications

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“…Data mining techniques can extract implicit in where people are not known in advance, but is potentially useful information and knowledge from fuzzy, large, noisy, random, incomplete data. How to apply data mining techniques to analysis of electronic evidence in the massive data through computer forensics associate analysis and find evidence of computer crimes, assisting public security authorities for combating and prevention of computer crime [3], is the critic issue described in the research objectives. As technology advances, though some of the original crime will disappear and some new type of crime will continue to appear, the criminal record in the recordset will be constantly updated, and the relationship among the project also will be changed and continuous generation of new association rules, the outdated crime cannot be ignored because it maybe appear by the other form.…”

Section: Introductionmentioning

confidence: 99%

MapReduce-based frequent itemset mining for analysis of electronic evidence

Jiang

Sun

2013

2013 8th International Workshop on Systematic Approaches to Digital Forensics Engineering (SADFE)

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Association rules can mine the relevant evidence of computer crime from the massive data and association rules among data itemset, and further mine crime trends and connections among different crimes. They can help polices detect case and prevent crime with clues and criterions. Frequent itemset mining (FIM) plays a fundamental role in mining associations, correlations and many real-world data mining fields such as electronic evidence analysis area. FP-growth is the most famous FIM algorithm for discovering frequent patterns. As the data incrementing, the cost of time and space will be the bottleneck of FP-growth mining algorithms. One of the existing incremental frequent pattern mining algorithms called SPO-tree can perform incremental mining by a single scan for incremental mining. But how to apply this algorithm to the analysis of electronic evidence more effectively will become the focus of this paper. In the past research, little people take care of the item mined to the frequent item needing to update or inserted a little data. The past algorithms are not suit for this problem especially in forensic area. So, in this paper, we propose a novel parallelized algorithm called PISPO based on the cloud-computing framework MapReduce, which is widely used to cope with largescale data and captures both the content and state to be distributed to the changed and original of the transactions dataset to SPO-tree.

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Section: Introductionmentioning

confidence: 99%

MapReduce-based frequent itemset mining for analysis of electronic evidence

Jiang

Sun

2013

2013 8th International Workshop on Systematic Approaches to Digital Forensics Engineering (SADFE)

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“…Pandeya S.N and Usha L (23) et.al., Mannich condensation on 3-sulfadiazinylsarion in the presence of formaldehyde and secondary furnished 3-aminomethyl analogs which were evaluated as antimicrobial agents. (27) Bhat AR Shenoy G.G and have reported the synthesis, antibacterial and antiviral activities of isatin derivatives. Sridhar S.K 28 et.al., Isatins have been reacted with 3-(4-pyridyl)-4-amino-5-mercapto-4H-1,2,4-triazole to from Schiff bases and the N-Mannich bases of these compounds were synthesized by reacting them with formaldehyde and several secondary amines.…”

Section: Literature Reviewmentioning

confidence: 99%

Novel Synthesis and Anti-Microbial Activity Study of Innovative Mannich Bases Containing 2- Phenoxy-1, 3, 2-Dioxa Phospholanes And Indole Systems

Kanchana¹,

Burra²,

Nath³

2014

Orient. J. Chem

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In the present study, synthesis, characterization, antimicrobial activity on some novel pyrazolone derivatives has been taken up. The primary amines were diazotized with sodium nitrite and HCl mixture at 0-5 0 C which were further coupled with ethyl acetoacetic ester to afford phenyl diazonium acetoacetic esters (II). Condensation of 4-substituted aryl hydrazono acetoacetic ester, 4-hydrazinylbenzenamine in the presence of catalytic amount of DMF under microwave irradiation afforded (4Z)-4-(2-substituted aryl hydrazono)-1-(4-aminophenyl)-3-methyl-1H-pyrazol-5(4H)-one (III). Subjecting (III) to anhydrous K 2 CO 3 in DMF for 8 hours afforded 2-{4-[(4Z)-4-(2-substituted aryl hydrazono)-4, 5-dihydro-3-methyl-5-oxopyrazol-1-yl] phenyl amino} acetate( IV) which was further reacted with hydrazine hydrate to afford 2-{4-[(4Z)-4-(2-substituted aryl hydrazono)-4, 5-dihydro-3-methyl-5-oxopyrazol-1-yl] phenylamino} acetohydrazide (V). Reaction of (V) and Isatin (VI b) in DMF afforded (4Z)-2-(4-((15Z)-4-(2-phenylhydrazono)-4,5-dihydro-3-methyl-5 oxopyrazol-1-yl) phenylamino)-N'-(2-oxoindolin-3-ylidene)acetohydrazide (VII). Compound (VII) was subsequently subjected to Mannich reaction with cyclic secondary amines (piperidine/morpholine/N-methyl piperidine) in the presence of formaldehyde in DMF to afford (4Z)-2-(4-((15Z)-4-(2-substituted aryl hydrazono)-4,5-dihydro-3-methyl-5-oxopyrazol-1-yl)phenylamino)-N'-(2-oxo-1-((piperidin-1-yl)methyl) indolin-3-ylidene)acetohydrazide (VIII) which was characterized by I.R, 1 HNMR and Mass data. The anti-bacterial activity of synthesized compounds was studied by the disc diffusion method against pathogenic bacteria and fungi.

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“…Hao and Lizhu [10] defined a stopword list in Chinese language which was based on weighted Chi-squared statistic. Association rule mining using Genetic Algorithm is used in the papers [11], [12], [13].…”

Section: Related Workmentioning

confidence: 99%

HSRA: Hindi stopword removal algorithm

Jha

Manjunath

Shenoy

et al. 2016

2016 International Conference on Microelectronics, Computing and Communications (MicroCom)

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Abstract-In the last few years, electronic documents have been the main source of data in many research areas like Web Mining, Information Retrieval, Artificial Intelligence, Natural Language Processing etc.. Text Processing plays a vital role for processing structured or unstructured data from the web. Preprocessing is the main step in any text processing systems. One significant preprocessing technique is the elimination of functional words, also known as stopwords, which affects the performance of text processing tasks. An efficient stopword removal technique is required in all text processing tasks. In this paper, we are proposing a stopword removal algorithm for Hindi Language which is using the concept of a Deterministic Finite Automata (DFA). A large number of available works on stopword removal techniques are based on dictionary containing stopword lists. Then pattern matching techique is applied and the matched patterns, which is a stopword, is removed from the document. It is a time consuming task as searching process takes a long time. This makes the method inefficient and very expensive. In comparision of that, our algorithm has been tested on 200 documents and achieved 99% accuracy and also time efficient.

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A Data Mining Approach for Data Generation and Analysis for Digital Forensic Application

Cited by 21 publications

References 4 publications

MapReduce-based frequent itemset mining for analysis of electronic evidence

MapReduce-based frequent itemset mining for analysis of electronic evidence

Novel Synthesis and Anti-Microbial Activity Study of Innovative Mannich Bases Containing 2- Phenoxy-1, 3, 2-Dioxa Phospholanes And Indole Systems

HSRA: Hindi stopword removal algorithm

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