Assistant Professor Khodakhast Bibak receives raving reviews on new book detailing security and AI

Khodakhast Bibak is an Assistant Professor in the Computer Science and Software Engineering department at Miami University and has recently received top ratings on his newest book, Statistical Trend Analysis of Physically Unclonable Functions: An Approach via Text Mining.

This book is a collaboration featuring Bibak alongside Behrouz Zolfaghari, Takeshi Koshiba, Hamid R. Nemati and Pinaki Mitra and was published by CRC Press in 2021. This book has received top stats based on lists made on a website called BookAuthority, which recommends and rates the best books for any subject based on expert and leader opinions.

“BookAuthority is used by millions of book lovers from all around the world, and has been featured on CNN, Forbes and Inc.,” the website says, giving readers a description about BookAuthority and its purposes.

Bibak’s book is ranked highly on the site’s lists, being ranked No. 1 in 8 Best Cryptographic Hardware eBooks of All Time, No. 5 in 45 Best Text Mining Books of All Time, and is No. 2 among 11 Best New Cryptography eBooks To Read In 2022.

When it comes to collaboration, Bibak has always enjoyed working with other people and has benefited a lot from it. He feels like some projects are interdisciplinary in nature and says that collaboration with others is a must due to no one truly knowing everything.

 “When you collaborate with other people on a project you see various perspectives and ideas which can be very helpful,” Bibak said.

When describing the book, Bibak provides this summary:

“Physically Unclonable Functions (PUFs) translate unavoidable variations in certain parameters of materials, waves, or devices into random and unique signals. They have found many applications in the Internet of Things (IoT), authentication systems, FPGA industry, several other areas in communications and related technologies, and many commercial products. In our book we first study cryptographic hardware and hardware-assisted cryptography. Our study highlights PUF as a mega trend in research on cryptographic hardware design. Afterwards, we present a novel approach, using text mining, for trend analysis that can be applied to any technology or research area (in fact, the trend analysis on PUFs is presented just as a case study). The results are used to present an evolution study as well as a trend analysis and develop a roadmap for future research in this area. This method gives an automatic popularity-based statistical trend analysis which eliminates the need for passing personal judgments about the direction of trends, and provides concrete evidence to the future direction of research on PUFs. Another advantage of this method is the possibility of studying a whole lot of existing research works (more than 700 in this book). Applying our text mining approach for trend analysis to other technologies or research areas in cybersecurity is a great project that we would like to do in future.”

Bibak was very excited to see that their project had so many positive reviews, but was also surprised. He said it was a bit unexpected initially, as there are already many other excellent books pertaining to this subject, but he sees it as a great honor to be critically acclaimed.

By Gabby Benedict, CEC Reporter