Refine your search
Collections
Journals
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z All
Sathya Bama, S.
- Fast Mining of Maximal Web Navigation Patterns
Abstract Views :159 |
PDF Views:1
Authors
M. Thilagu
1,
S. Sathya Bama
1
Affiliations
1 VLB Janakiammal College of Engineering and Technology, Coimbatore, IN
1 VLB Janakiammal College of Engineering and Technology, Coimbatore, IN
Source
Data Mining and Knowledge Engineering, Vol 2, No 11 (2010), Pagination: 360-364Abstract
Discovering user navigation patterns in web log sessions has been an interesting problem and used with many applications including web site development, e-business, e-learning etc. Most of the proposed algorithms for mining web log patterns generate candidate sequences and test whether they are frequent or not, based on the given min-sup. In this paper, we present a fast method that aims at mining prefix based maximal contiguous sequence patterns without generating candidate sequences level-by-level. It first generates maximal potential sequences and mines only them in the database using minimized search space. Performance evaluation of the proposed algorithm is done by conducting experimental studies on a real dataset and found satisfactory when compared to previous approach.Keywords
Maximal Sequence Pattern, Sequence Pattern, Web Log Database, Web Usage Mining.
- Policy Approval Engine - A Framework for Securing Web Applications and Web User
Abstract Views :153 |
PDF Views:0
Authors
Affiliations
1 Department of MCA, Sri Krishna College of Technology, Coimbatore - 641008, Tamil Nadu, IN
1 Department of MCA, Sri Krishna College of Technology, Coimbatore - 641008, Tamil Nadu, IN
Source
Indian Journal of Science and Technology, Vol 9, No 4 (2016), Pagination:Abstract
Background/Objectives: Web applications face variety of new extortions related to injections. Securing the web applications becomes paramount and an intricate process with the current technologies. The objective of this paper is to protect the web application form injection attacks. Methods/Statistical Analysis: Web publishers frequently integrate third-party advertisements into web pages that also contain sensitive end-user personal data. This may expose sensitive page content to confidentiality and integrity attacks launched by advertisements. Thus web browser needs some simple security policy and enforcement which can alleviate basic attacks in order to guard the applications and user that resides on the web. Findings: The policy enforcement framework for addressing security threats and to protect against cross-site request forgery, cross-site scripting, and content stealing has been proposed. To do so, the framework observes all outgoing web requests within the browser and offers authorization and approval checks before the contents are embedded into a page. Additionally, the advertisements are restricted to the access the user data. Thus, the paper delivers better understanding about web application security policy enforcement which protects user data from interactive ads. The proposed framework is compared with existing methods like SOMA and RequestPolicy and the result shows that the proposed method improves better security against attacks. The proposed framework decreases the false positive rate and false negative rate when compared to the existing framework. The accuracy of the proposed method is above 90%. Applications/Improvements: The proposed framework can be used to protect the web against cross-site request forgery, cross-site scripting, and content stealing. The future work focuses on providing security against web site defacement and other attacks.Keywords
Injections, Policy Enforcement Framework, Security Policy, Security Threats, Web ApplicationsFull Text
- Performance Enhancement of Direct Torque Control of Induction Motor Using Fuzzy Logic
Abstract Views :150 |
PDF Views:0
Authors
Affiliations
1 Department of Electrical and Electronics Engineering, PSG College of Technology, Tamil Nadu, IN
1 Department of Electrical and Electronics Engineering, PSG College of Technology, Tamil Nadu, IN
Source
ICTACT Journal on Soft Computing, Vol 2, No 1 (2011), Pagination: 218-223Abstract
DTC is strategy of selecting proper stator voltage vectors to reduce torque error and flux error. DTC uses hysteresis band controller whose control action has no difference between large torque error and small one. This results in high torque ripple. In order to reduce the torque ripple and to improve the performance of DTC, DTC based on Fuzzy Logic is proposed in this paper. The simulations are carried out using MATLAB and comparison is made between conventional DTC and DTC using Fuzzy Logic and simulated results are shown.Keywords
DTC, Fuzzy Logic, Induction Motor, Switching Table.- A Review on Cyber Security and the Fifth Generation Cyberattacks
Abstract Views :253 |
PDF Views:0
Authors
Affiliations
1 Department of MCA, Sree Saraswathi Thyagaraja College, Pollachi, IN
2 483, Lawley Road, Coimbatore, Tamil Nadu, IN
1 Department of MCA, Sree Saraswathi Thyagaraja College, Pollachi, IN
2 483, Lawley Road, Coimbatore, Tamil Nadu, IN
Source
Oriental Journal of Computer Science and Technology, Vol 12, No 2 (2019), Pagination: 50-56Abstract
Cyberattacks has become quite common in this internet era. The cybercrimes are getting increased every year and the intensity of damage is also increasing. providing security against cyber-attacks becomes the most significant in this digital world. However, ensuring cyber security is an extremely intricate task as requires domain knowledge about the attacks and capability of analysing the possibility of threats. The main challenge of cyber security is the evolving nature of the attacks. This paper presents the significance of cyber security along with the various risks that are in the current digital era. The analysis made for cyber-attacks and their statistics shows the intensity of the attacks. Various cyber security threats are presented along with the machine learning algorithms that can be applied on cyberattacks detection. The need for the fifth generation cybersecurity architecture is discussed.Keywords
Cyberattacks, Cybersecurity, Fifth Generation, Machine Learning Algorithm, Security Threats.Full Text
References
- Trustwave Global Securi t y. Report retrieved from: https://www2.trustwave.com/rs/815-RFM693/ images/2015_TrustwaveGlobalSecurityReport.pdf
- International Organization for Standardization. ISO/IEC 27032:2012. Information technology—Security techniques— Guidelines for cybersecurity. 2012
- Chowdhury A. Recent cyber security attacks and their mitigation approaches–An Overview. In International conference on applications and techniques in information security, Springer, Singapore. 2016; pp 54-65.
- Passer i P. Cyber At tacks Stat ist ics Paolo Passeri, May 2016. http://www.hackmageddon.com/category/security/cyber-attacks-statistics/. Accessed 07 October 2016
- Fischer EA. Creating a national framework for cybersecurity: an analysis of issues and options. Technical report. Congressional Research Service. 2005.
- The Open Web Application Security Project (OWASP). 2018. Available online: https:// www.swascan.com/owasp/
- The Open Web Application Security Project OWASP Top 10—the ten most critical web application security risks. The OWASP Foundation. 2018.
- Check Point Research Survey of IT Security Professionals, sample size: 443 participants. 2018.
- Check Point Mobile Threat Research Publications. 2017. Available Online: https:// research.checkpoint.com/check-point-mobile-research-team-looks-back-2017/
- Cyber Attack Trends Analysis Key Insights to Gear Up for in 2019. Available Online: http://www.snt.hr/boxcontent/CheckPointSecurityReport2019_vol01.pdf
- Check Point C-Level Perspective Survey. 2017. sample size: 59 C-Level Executives. Available Online: https://www.checkpoint.com/downloads/product-related/report/2018-security-report.pdf
- Drucker H. Wu D. Vapnik VN. Support vector machines for spam categorization. IEEE Trans Neural Netw Publ IEEE Neural Netw Counc 1999; 10(5):1048–54
- Cranor LF. Lamacchia BA. Spam!. Commun ACM. 1998; 41(8):74–83
- SANS Institute. Top 15 Malicious Spyware Actions. 2018. Available Online: https://www.sans.org/security-resources/
- Wang Z.J., Liu Y., Wang Z.J. E-mail filtration and classification based on variable weights of the Bayesian algorithm. Appl Mech Mater. 2014; 513–517:2111–2114.
- Hsu W.C., Yu T.Y. E-mail spam filtering based on support vector machines with Taguchi method for parameter selection. J Converg Inf Technol 2010. 5(8):78–88.
- Caruana G., Li M., Qi M. A MapReduce based parallel SVM for large scale spam filtering. In: IEEE 2011 eighth international conference on fuzzy systems and knowledge discovery (FSKD), 2011; pp 2659–2662.
- Wu C.H. Behavior-based spam detection using a hybrid method of rule-based techniques and neural networks. Expert Syst Appl. 2009: 36(3):4321–4330.
- Hazza Z.M., Aziz N.A. A new efficient text detection method for image spam filtering. Int Rev Comput Softw. 2015; 10(1):1–8.
- Dhaya R., Poongodi M. Detecting software vulnerabilities in android using static analysis. 2015; pp 915–918.
- Markel Z., Bilzor M. Building a machine learning classifier for malware detection. In: Second workshop on anti-malware testing research (WATeR). IEEE. Canterbury. UK. 2015.
- Shijo P.V., Salim A. Integrated static and dynamic analysis for malware detection. Procedia Comput Sci. 2015; 46:804–811.
- Divya S., Padmavathi G. A novel method for detection of internet worm malcodes using principal component analysis and multiclass support vector machine. Int J Secur Appl. 2014; 8(5):391–402
- Akinyelu A.A., Adewumi A.O. Classification of phishing email using random forest machine learning technique. J Appl Math 2014; pp 1–6.
- Santhana Lakshmi V., Vijaya M.S. Efficient prediction of phishing websites using supervised learning algorithms. Procedia Eng. 2012; 30:798–805.
- Check point 2018 security report. 2018. Available Online: https://www.checkpoint.com/downloads/product-related/report/2018-security-report.pdf.