ISRL

https://www.theregister.com/2021/09/09/boffins_unveil_ssdinsider_promise_ransomware/

SSD-Insider (IEEE Trans on Computers) is on “The Register”, UK-based tech magazine!

You can take a look at the article titled “Boffins unveil SSD-Insider++, promise ransomware detection and recovery right in your storage” by Gareth Halfacree (Thank you Gareth!). Also, it is quite fun to read the readers’ comments in the article.

Also, ZDNet Korea interviewed me to introduce SSD-Insider, which can be found at

https://zdnet.co.kr/view/?no=20210916105104

“BlockTrail: A Service for Secure and Transparent Blockchain-Driven Audit Trails” by Ashar Ahmad, Muhammad Saad, Mohammed Al Ghamdi, DaeHun Nyang, David Mohaisen is accepted in IEEE Systems Journal. Congratulations to all!

In this paper, we introduce BlockTrail, a novel blockchain architecture that is prototyped on the PBFT protocol with a custom-built blockchain. BlockTrail is secure and efficient, while having low storage footprint.

“DL-FHMC: Deep Learning-based Fine-grained Hierarchical Learning Approach for Robust Malware Classification” by Ahmed Abusnaina, Mohammed Abuhamad, Hisham Alasmary, Afsah Anwar, Rhongho Jang, Saeed Salem, DaeHun Nyang, David Mohaisen is accepted for publication in IEEE Transactions on Dependable and Secure Computing. This paper deals with ML-based approach to robust malware classification under the existence of adversarial examples. Congrats to all.

A good news. “SHELLCORE: Automating Malicious IoT Software Detection by Using Shell Commands Representation” is accepted for publication in IEEE IoT Journal. This is the joint work with Hisham Alasmary, Afsah Anwar, Ahmed Abusnaina, Abdulrahman Alabduljabbar, Mohammed Abuhamad, An Wang, DaeHun Nyang, Amro Awad, and David Mohaisen.

This paper investigates shell commands abused by adversaries in IoT devices, and proposes a machine learning-based detection system. A large amount of dataset of shell commands were collected including malicious commands extracted from 2,891 IoT malware samples.

Congratulations!

“A Network-independent Tool-based Usable Authentication System for Internet of Things Devices” by Changhun, Jinchun, Rhongho, David and me is now accepted by Computers and Security. I am very pleased to see this paper has been published. This paper is about IoT authentication by a special hardware tool that makes authentication easy and fun as well as secure. Changhun designed and implemented the hardware prototype of the device.

Congratulations Changhun and all!

 Me, waiting for the award in NetSec-KR 2021 after keynote speech.

The vice-minister of science and ICT and me are pausing for photo taking.

The commendation certificate.

I was the awardee of Minister of Science and ICT’s commendation for best researchers.  The awarding ceremony was held in NetSec-KR 2021 at COEX today. I would like to share this honor with my colleagues and students, David, Jiyoo, Mohammed, Changhoon. Thank you for your support.

“Empirically Comparing the Performance of Blockchain’s Consensus Algorithms” by Ashar Ahmad, Abdulrahman Alabduljabbar, Muhammad Saad, Joongheon Kim, DaeHun Nyang, David Mohaisen is accepted by IET Blockchain.

Congratulations!

“Large-Scale and Robust Code Authorship Identification with Deep Feature Learning” by Mohammed Abuhamad (Loyola University Chicago), Tamer Abuhmed (Sungkyunkwan University), David Mohaisen (University of Central Florida), and DaeHun Nyang (Ewha Womans University) is accepted for publication in ACM Transactions on Privacy and Security today.

This paper is substantially extended from our previous work in ACM CCS 2018 by investigating binary code authorship identification using RNN with Random Forest as well as source code authorship identification.

Congratulations to all!

Congratulations to Jiyoo, Changhun, Kyunghee, and David!

Our paper on alphabet entry method for smartwatch is accepted for publication in TMC, of which title is “A One-Page Text Entry Method Optimized for Rectangle Smartwatches” by RhongHo Jang, Changhun Jung, David Mohaisen, Kyunghee Lee, DaeHun Nyang.

Hope that this work helps to make it easier to input alphabet in smartwatch.