Researcher of Innopolis University presented results of the study on cyber security and estimation of diabetes cases. 

International Conference on Recent Advances in Computer Systems (RACS), hosted by Hail University, Saudi Arabia, has become a great opportunity for academics in the areas of Computer Science, Engineering, Bioinformatics and Cyber Security to present their work and meet experts in their field.

Junaid Chaudhry, research fellow of Innopolis University delivered a speech on “Crypto, non-crypto-based Steganography and their Applications in VANET”, prepared in cooperation with Rasheed Hussain, another researcher of the Russian IT university.

Prof. Chaudhry chaired one of the conference sessions on Recent Advances in Cyber Security where he delivered results of three joint research studies carried out in collaboration with his colleagues from South Korea, Oman and Saudi Arabia.

The first study was devoted to secure calls and caller ID spoofing countermeasures (spoofing is a hacker attack), analysis of existing methods to prevent the caller ID spoofing along with possible consequences and models for caller ID verification that may be used to verify the caller identity.

In another study, Junaid Chaudhry reviewed alternative methods of authentication in comparison to traditional method and application fields.

Researcher of Innopolis University in collaboration with colleagues from Sarawak University, Malaysia, and Prince Sultan University, Saudi Arabia, presented a study “Estimating Diabetic Cases in KSA through search trends and Creating Cyber Diabetic Community” with further creation of Internet communities for diabetics in terms of received data.

“This study tends to create a diabetic prediction system that will gather information from multiple sources (news, health care records, social media, news feeds, search trends and tweets) in multiple languages to answer a number of questions”, - said Junaid Chaudhry, researcher of Innopolis University.

The study revealed a correlation between the analysis-based cyber data and real-time online data. Besides, it has been discovered that search requests commonly contain general symptoms and names of diseases and therefore allow creation of a cyber diabetic community intended to be used by government agencies and health institutions.