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Sachdeva, A., Kapoor, R., Sharma, A., Mishra, A..  2017.  Categorical Classification and Deletion of Spam Images on Smartphones Using Image Processing and Machine Learning. 2017 International Conference on Machine Learning and Data Science (MLDS). :23–30.

We regularly use communication apps like Facebook and WhatsApp on our smartphones, and the exchange of media, particularly images, has grown at an exponential rate. There are over 3 billion images shared every day on Whatsapp alone. In such a scenario, the management of images on a mobile device has become highly inefficient, and this leads to problems like low storage, manual deletion of images, disorganization etc. In this paper, we present a solution to tackle these issues by automatically classifying every image on a smartphone into a set of predefined categories, thereby segregating spam images from them, allowing the user to delete them seamlessly.

Goyal, Y., Sharma, A..  2019.  A Semantic Machine Learning Approach for Cyber Security Monitoring. 2019 3rd International Conference on Computing Methodologies and Communication (ICCMC). :439—442.
Security refers to precautions designed to shield the availability and integrity of information exchanged among the digital global community. Information safety measure typically protects the virtual facts from unauthorized sources to get a right of entry to, disclosure, manipulation, alteration or destruction on both hardware and software technologies. According to an evaluation through experts operating in the place of information safety, some of the new cyber-attacks are keep on emerging in all the business processes. As a stop result of the analyses done, it's been determined that although the level of risk is not excessive in maximum of the attacks, it's far a severe risk for important data and the severity of those attacks is prolonged. Prior safety structures has been established to monitor various cyber-threats, predominantly using a gadget processed data or alerts for showing each deterministic and stochastic styles. The principal finding for deterministic patterns in cyber- attacks is that they're neither unbiased nor random over the years. Consequently, the quantity of assaults in the past helps to monitor the range of destiny attacks. The deterministic styles can often be leveraged to generate moderately correct monitoring.
Goel, N., Sharma, A., Goswami, S..  2017.  A way to secure a QR code: SQR. 2017 International Conference on Computing, Communication and Automation (ICCCA). :494–497.

Now a day, need for fast accessing of data is increasing with the exponential increase in the security field. QR codes have served as a useful tool for fast and convenient sharing of data. But with increased usage of QR Codes have become vulnerable to attacks such as phishing, pharming, manipulation and exploitation. These security flaws could pose a danger to an average user. In this paper we have proposed a way, called Secured QR (SQR) to fix all these issues. In this approach we secure a QR code with the help of a key in generator side and the same key is used to get the original information at scanner side. We have used AES algorithm for this purpose. SQR approach is applicable when we want to share/use sensitive information in the organization such as sharing of profile details, exchange of payment information, business cards, generation of electronic tickets etc.