arXiv subjects

Dhananjoy Dey

Publications and source records attributed to Dhananjoy Dey.

4 recordsLinked to original sources

arXiv2022

Near Lossless Time Series Data Compression Methods using Statistics and Deviation

The last two decades have seen tremendous growth in data collections because of the realization of recent technologies, including the internet of things (IoT), E-Health, industrial IoT 4.0, autonomous vehicles, etc. The challenge of data transmission and storage can be handled by utilizing state-of-the-art data compression methods. Recent data compression methods are proposed using deep learning methods, which perform better than conventional methods. However, these methods require a lot of data and resources for training. Furthermore, it is difficult to materialize these deep learning-based solutions on IoT devices due to the resource-constrained nature of IoT devices. In this paper, we propose lightweight data compression methods based on data statistics and deviation. The proposed method performs better than the deep learning method in terms of compression ratio (CR). We simulate and compare the proposed data compression methods for various time series signals, e.g., accelerometer, gas sensor, gyroscope, electrical power consumption, etc. In particular, it is observed that the proposed method achieves 250.8\%, 94.3\%, and 205\% higher CR than the deep learning method for the GYS, Gactive, and ACM datasets, respectively. The code and data are available at https://github.com/vidhi0206/data-compression .

cs.IT↗

arXiv2018

How vulnerable are the Indian banks: A cryptographers' view

With the advent of e-commerce and online banking it has become extremely important that the websites of the financial institutes (especially, banks) implement up-to-date measures of cyber security (in accordance with the recommendations of the regulatory authority) and thus circumvent the possibilities of financial frauds that may occur due to vulnerabilities of the website. Here, we systematically investigate whether Indian banks are following the above requirement. To perform the investigation, recommendations of Reserve Bank of India (RBI), National Institute of Standards and Technology (NIST), European Union Agency for Network and Information Security (ENISA) and Internet Engineering Task Force (IETF) are considered as the benchmarks. Further, the validity and quality of the security certificates of various Indian banks have been tested with the help of a set of tools (e.g., SSL Certificate Checker provided by Digicert and SSL server test provided by SSL Labs). The analysis performed by using these tools and a comparison with the benchmarks, have revealed that the security measures taken by a set of Indian banks are not up-to-date and are vulnerable under some known attacks.

cs.CR↗

arXiv2011

GB-hash : Hash Functions Using Groebner Basis

In this paper we present an improved version of HF-hash, viz., GB-hash : Hash Functions Using Groebner Basis. In case of HF-hash, the compression function consists of 32 polynomials with 64 variables which were taken from the first 32 polynomials of hidden field equations challenge-1 by forcing last 16 variables as 0. In GB-hash we have designed the compression function in such way that these 32 polynomials with 64 variables form a minimal Groebner basis of the ideal generated by them with respect to graded lexicographical (grlex) ordering as well as with respect to graded reverse lexicographical (grevlex) ordering. In this paper we will prove that GB-hash is more secure than HF-hash as well as more secure than SHA-256. We have also compared the efficiency of our GB-hash with SHA-256 and HF-hash.

cs.CR↗

arXiv2009

HF-hash : Hash Functions Using Restricted HFE Challenge-1

Vulnerability of dedicated hash functions to various attacks has made the task of designing hash function much more challenging. This provides us a strong motivation to design a new cryptographic hash function viz. HF-hash. This is a hash function, whose compression function is designed by using first 32 polynomials of HFE Challenge-1 with 64 variables by forcing remaining 16 variables as zero. HF-hash gives 256 bits message digest and is as efficient as SHA-256. It is secure against the differential attack proposed by Chabaud and Joux as well as by Wang et. al. applied to SHA-0 and SHA-1.

cs.CR↗