Neelam saleem Khan
@nitsri.ac.in
Research Scholar Department of Computer Science Engineering
national institute of technology srinagar
Scopus Publications
Scopus Publications
Neelam Saleem Khan, Mohammad Ahsan Chishti, and Mahreen Saleem
Springer Singapore
The aim of this review is to acquaint the researcher with the knowledge of cyber-crime. Cyber-crimes are offenses that are carried out against individuals or groups of individuals using computers and networks to commit the crimes. These crimes are carried out intentionally to damage the reputation of a victim or harm the victim physically and psychologically; using modern internet-based communication like emails, chat rooms, notice boards, websites, cell phones, etc. This paper analyzes risk perception in students and precautionary behavior in their use of the internet. It also analyzes various fields that are affected by cyber-crimes that include cyber-bullying in adolescents, cyber-crime in government organizations, and Internet of Things (IoT) and provides an insight into mitigating these hazards. It also provides a mind-map of various network security issues that needs to be considered to avoid cyber-crime.
Vandana Saini, Rama Krishna Challa, and Neelam S. Khan
Springer Singapore
Cloud computing is a paradigm for large-scale distributed computing. The sensitive data should be outsourced to the cloud and stored in an encrypted format to keep it confidential. The existing search schemes do not suggest keywords consequently making the retrieving of documents difficult if user forgets the keyword. In this paper, we propose a multi-keyword synonym based fuzzy ranked search (MSFRS) scheme over outsourced encrypted cloud data which provides efficient search results retaining the security features of the existing schemes. It supports multi-keyword, suggests synonyms if user forgot keyword and returns results after evaluating relevance scores based on frequency of keyword in the documents bearing same rank. The performance analysis of the proposed scheme on the dataset concluded that time taken to update the index file has been reduced up to 45 % over outsourced encrypted cloud data.
Neelam S. Khan, C. Rama Krishna, and Anu Khurana
IEEE
As the power of cloud computing became prevalent in the recent years, more and more sensitive information is being now shifted to the cloud. The cloud is a computing service that charges the user according to usage of the computing resources. This pay-as-you-use feature is the hallmark in cloud computing. Security of data is a matter of concern and especially when cloud storage service is used. Encryption is the most effective way to achieve data security. Sensitive data have to be encrypted before outsourcing in spite of the fact that, retrieval of encrypted data becomes an intriguing task. Although various searching techniques are used for retrieving the encrypted cloud data through keywords and these techniques retrieve the files in a ranked order but they either support rank based single keyword search or multi-keyword search with static keyword dictionary. There is a greater overhead in updating the index file or the keyword dictionary when new files need to be uploaded. Also, efficient data discovery and user searching experience needs to be enhanced. In this paper, for the first time we formulize and solve the problem of effective Secure ranked Fuzzy multi-keyword search over outsourced encrypted cloud data (RFMS). RFMS enhances user searching experience by returning the matching files when user's input query either exactly matches the predefined keyword dictionary or closest possible keywords in the dictionary based on similarity semantics when exact match fails. Information discovery has been made efficient by searching with multiple keywords with ranking so as to eliminate false positives. Keyword dictionary has been made dynamic. Overhead of updating the dictionary when new files need to be uploaded has been minimized. Also, by using one-to-many mapping between plaintext and cipher text, the method guarantees security.