Gwang-Jo Kim

Deep learning techniques are famous due to Its capability to cope with large-scale data these days. They have been investigated within various of applications e.g., language, graphical modeling, speech, audio, image recognition, video, natural language and signal processing areas. In addition, extensive researches applying machine-learning methods in Intrusion Detection System (IDS) have been done in both academia and industry. However, huge data and difficulties to obtain data instances are hot

We deal with two claws of Zhou-Gollmann's fair non-repudiation protocol. Firstly, their protocol divides a message into 2 parts, i.e., a key K and a ciphertext C. Then, C is delivered to the recipient, while K is submitted to TTP (Trusted Third Party). If the originator doesn't submit K to TTP, then the protocol appears to have no dispute between the originator and the recipient. However the protocol depends on his action on whether the originator really submits K to TTP or not. We show that the

We have designed an Internet voting system applicable for worldwide voting which is based on Ohkubo et. al.'s scheme [23] combined with Public Key Infrastructure (PKI). To the best of our knowledge, this is the first trial to serve secure Internet voting system to the world. In our system, voter's privacy is guaranteed by using blind signature and mix-net, and robustness is provided through the threshold encryption scheme. By employing Java technology, we propose a way of typic

In this paper, we propose an expanded set of design criteria for the generation of DES-like Sboxes which enable DES being immunized against three known robust cryptanalysis, i.e., differential, Improved Davies' and linear cryptanalysis and we also suggest a set of new 8 DES-like S-boxes generated by our proposed design criteria in order to replace with the current 8 DES S-boxes. The computer simulation leads us to conclude that the breaking complexity of the strengthened DES (we call s

At Crypto'92, L.R. Knudsen[7] showed that s²DES is insufficient to assure against differential attack. In this paper, we propose a provable design criterion to strengthen s²DES against differential attack without disturbing its cryptographic structure. We show that new s²DES S-boxes can be constructed with our new design criteria and suggest new 8 s²DES S-boxes for replacing the current DES S-boxes. Simply called this algorithm as s³DES, the result of our estimation and Knudsen&apos

Deep learning is gaining more and more lots of attractions and better performance in implementing the Intrusion Detection System (IDS), especially for feature learning. This paper presents the state-of-the-art advances and challenges in IDS using deep learning models, which have been achieved the big performance enhancements in the field of computer vision, natural language processing, and image/audio processing than the traditional methods. After providing a systematic and methodical descriptio