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Dabas, K., Madaan, N., Arya, V., Mehta, S., Chakraborty, T., Singh, G..  2019.  Fair Transfer of Multiple Style Attributes in Text. 2019 Grace Hopper Celebration India (GHCI). :1—5.

To preserve anonymity and obfuscate their identity on online platforms users may morph their text and portray themselves as a different gender or demographic. Similarly, a chatbot may need to customize its communication style to improve engagement with its audience. This manner of changing the style of written text has gained significant attention in recent years. Yet these past research works largely cater to the transfer of single style attributes. The disadvantage of focusing on a single style alone is that this often results in target text where other existing style attributes behave unpredictably or are unfairly dominated by the new style. To counteract this behavior, it would be nice to have a style transfer mechanism that can transfer or control multiple styles simultaneously and fairly. Through such an approach, one could obtain obfuscated or written text incorporated with a desired degree of multiple soft styles such as female-quality, politeness, or formalness. To the best of our knowledge this work is the first that shows and attempt to solve the issues related to multiple style transfer. We also demonstrate that the transfer of multiple styles cannot be achieved by sequentially performing multiple single-style transfers. This is because each single style-transfer step often reverses or dominates over the style incorporated by a previous transfer step. We then propose a neural network architecture for fairly transferring multiple style attributes in a given text. We test our architecture on the Yelp dataset to demonstrate our superior performance as compared to existing one-style transfer steps performed in a sequence.

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Gupta, M. K., Govil, M. C., Singh, G., Sharma, P..  2015.  XSSDM: Towards detection and mitigation of cross-site scripting vulnerabilities in web applications. 2015 International Conference on Advances in Computing, Communications and Informatics (ICACCI). :2010–2015.

With the growth of the Internet, web applications are becoming very popular in the user communities. However, the presence of security vulnerabilities in the source code of these applications is raising cyber crime rate rapidly. It is required to detect and mitigate these vulnerabilities before their exploitation in the execution environment. Recently, Open Web Application Security Project (OWASP) and Common Vulnerabilities and Exposures (CWE) reported Cross-Site Scripting (XSS) as one of the most serious vulnerabilities in the web applications. Though many vulnerability detection approaches have been proposed in the past, existing detection approaches have the limitations in terms of false positive and false negative results. This paper proposes a context-sensitive approach based on static taint analysis and pattern matching techniques to detect and mitigate the XSS vulnerabilities in the source code of web applications. The proposed approach has been implemented in a prototype tool and evaluated on a public data set of 9408 samples. Experimental results show that proposed approach based tool outperforms over existing popular open source tools in the detection of XSS vulnerabilities.

Gupta, M.K., Govil, M.C., Singh, G..  2014.  Static analysis approaches to detect SQL injection and cross site scripting vulnerabilities in web applications: A survey. Recent Advances and Innovations in Engineering (ICRAIE), 2014. :1-5.

Dependence on web applications is increasing very rapidly in recent time for social communications, health problem, financial transaction and many other purposes. Unfortunately, presence of security weaknesses in web applications allows malicious user's to exploit various security vulnerabilities and become the reason of their failure. Currently, SQL Injection (SQLI) and Cross-Site Scripting (XSS) vulnerabilities are most dangerous security vulnerabilities exploited in various popular web applications i.e. eBay, Google, Facebook, Twitter etc. Research on defensive programming, vulnerability detection and attack prevention techniques has been quite intensive in the past decade. Defensive programming is a set of coding guidelines to develop secure applications. But, mostly developers do not follow security guidelines and repeat same type of programming mistakes in their code. Attack prevention techniques protect the applications from attack during their execution in actual environment. The difficulties associated with accurate detection of SQLI and XSS vulnerabilities in coding phase of software development life cycle. This paper proposes a classification of software security approaches used to develop secure software in various phase of software development life cycle. It also presents a survey of static analysis based approaches to detect SQL Injection and cross-site scripting vulnerabilities in source code of web applications. The aim of these approaches is to identify the weaknesses in source code before their exploitation in actual environment. This paper would help researchers to note down future direction for securing legacy web applications in early phases of software development life cycle.

Gupta, M.K., Govil, M.C., Singh, G..  2014.  A context-sensitive approach for precise detection of cross-site scripting vulnerabilities. Innovations in Information Technology (INNOVATIONS), 2014 10th International Conference on. :7-12.

Currently, dependence on web applications is increasing rapidly for social communication, health services, financial transactions and many other purposes. Unfortunately, the presence of cross-site scripting vulnerabilities in these applications allows malicious user to steals sensitive information, install malware, and performs various malicious operations. Researchers proposed various approaches and developed tools to detect XSS vulnerability from source code of web applications. However, existing approaches and tools are not free from false positive and false negative results. In this paper, we propose a taint analysis and defensive programming based HTML context-sensitive approach for precise detection of XSS vulnerability from source code of PHP web applications. It also provides automatic suggestions to improve the vulnerable source code. Preliminary experiments and results on test subjects show that proposed approach is more efficient than existing ones.

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Singh, G., Garg, S..  2020.  Fuzzy Elliptic Curve Cryptography based Cipher Text Policy Attribute based Encryption for Cloud Security. 2020 International Conference on Intelligent Engineering and Management (ICIEM). :327–330.

Cipher Text Policy Attribute Based Encryption which is a form of Public Key Encryption has become a renowned approach as a Data access control scheme for data security and confidentiality. It not only provides the flexibility and scalability in the access control mechanisms but also enhances security by fuzzy fined-grained access control. However, schemes are there which for more security increases the key size which ultimately leads to high encryption and decryption time. Also, there is no provision for handling the middle man attacks during data transfer. In this paper, a light-weight and more scalable encryption mechanism is provided which not only uses fewer resources for encoding and decoding but also improves the security along with faster encryption and decryption time. Moreover, this scheme provides an efficient key sharing mechanism for providing secure transfer to avoid any man-in-the-middle attacks. Also, due to fuzzy policies inclusion, chances are there to get approximation of user attributes available which makes the process fast and reliable and improves the performance of legitimate users.