COMPUSOFT: An International Journal of Advanced Computer Technology <p>Computer Science Journals - COMPUSOFT is a monthly computer and engineering science journal that publishes innovative articles which contribute new theoretical results in all areas of engineering and Computer Science, Communication Network, Information Security issues, electrical engineering, electronics engineering etc. COMPUSOFT is high impact journal of information technology having Impact Factor of 4.44 (Self Calculated) with the rejection rate of around 90%. We invite research papers, review articles, thesis in all the fields of engineering &amp; computer science. We are indexed in many renowned indexing agencies. International Computer Science and Engineering Journals have devoted Staff, Reviewers, Editorial Board Members, Experts, and Adviser.</p> en-US <p>The submitter hereby warrants that the Work (collectively, the “Materials”) is original and that he/she is the author of the Materials. To the extent the Materials incorporate text passages, figures, data or other material from the works of others, the undersigned has obtained any necessary permissions. Where necessary, the undersigned has obtained all third party permissions and consents to grant the license above and has all copies of such permissions and consents.</p> <p>The submitter represents that he/she has the power and authority to make and execute this assignment. The submitter agrees to indemnify and hold harmless the COMPUSOFT from any damage or expense that may arise in the event of a breach of any of the warranties set forth above. For authenticity, validity and originality of the research paper the author/authors will be totally responsible.&nbsp;</p> (S.Porwal) (Technical Support) Fri, 31 Jul 2020 16:34:32 +0000 OJS 60 Blockchain-based Smart Energy Trading: Motivations and Challenges <p>The growing population and high demand of renewable energy leads to a decentralized solution to trade energy smartly. In an innovative energy market, consumers and prosumers are able to trade green energy locally and directly to balance the generation and consumption through decentralized community. In this paper, we present a comprehensive review of existing energy trading systems, their motivations and challenges. For this reason, new ICT technologies are investigated to consider their incredible affections on data transparency, energy trading and how energy consumer and producers are connected intelligently.&nbsp; The similarities, differences, and challenges in different energy trading projects are identified. The comparison analysis leads us to analyze the future scenario of energy trading that can offer high level of data transparency, low trading cost and less trading time.</p> Norziana Jamil, Ahmad Amini, Farah Aqilah Bohani Copyright (c) 2020 COMPUSOFT: An International Journal of Advanced Computer Technology Fri, 31 Jul 2020 00:00:00 +0000 A Review of ECG Data Acquisition for Driver Drowsiness Detection <p>Over the years, cases related to road accidents and road fatalities keeps increasing. Both cases have potential to put life of a person in risk. One of the factors that leads to accidents are drowsiness. Yet, several lives can be saved with accurate and reliable drowsiness detection system. Thus, many researchers take this issue seriously by developing drowsiness detection mechanism in reducing cases related to driver drowsiness. As drowsiness are strongly correlated with the heart activity, biosignal are the most preferable indicator to measure the drowsiness level. Reflection of electrical signal in the human body, known as Electrocardiogram (ECG) are widely used in monitoring human action and reaction to prevent the occurrence of these devastating incidents. Thus, this paper will review the drowsiness detection technique focusing in ECG data acquisition for driver drowsiness detection. As the first step plays an important role for the whole system, this paper discussed on some open issues in drowsiness mechanism. It is hope that this review will support and give some ideas to the future researchers in increasing the reliability of ECG measures towards driver drowsiness detection in reducing accident cases<strong>.</strong></p> Nur Shahirah Nor Shahrudin, Khairul Azami Sidek Copyright (c) 2020 COMPUSOFT: An International Journal of Advanced Computer Technology Fri, 31 Jul 2020 16:14:38 +0000 ARCHITECTURE BASED ON TOR NETWORK FOR SECURING THE COMMUNICATION OF NORTHBOUND INTERFACE IN SDN Software-defined networking (SDN) is an emerging technology that separated its architecture into three layers. Applications layer and Control layer communicates through the Northbound Interface (NBI), these communications can be targeted to fingerprinting even with the encryption applied. With the growth of cyber-attacks and zero-day vulnerabilities in network environments, SDN is more open to security issues than other technologies due to the isolation of its architecture. In this paper, we proposed a new architecture to add an extra layer of Tor network to anonymize the communication of NBI, the development of the combination of SDN and Tor experiment using VMware virtual machines for SDN controller, GNS3 networks and Wireshark for NBI traffic analysis. In the results of maximizing the security of SDN, anonymous communication can prevent NBI from the fingerprinting by allowing the requests and responses messages going through multiple nodes before reaching the destination comparing with the current SDN architecture that using direct communications. Lastly, we discussed the results towards the STRIDE model to show and ensure how the combination of SDN and Tor can provide the security and privacy to the SDN Network Osman Ahmed, Mohammad Hafiz Mohd Yusof Copyright (c) 2020 COMPUSOFT: An International Journal of Advanced Computer Technology Fri, 31 Jul 2020 16:20:30 +0000 Analysis of password protected Document <p>Nowadays documents are sent through electronics communications channels like email, WhatsApp, telegram etc., in which document protection plays major role. Passwords are used to encrypt the documents of different formats. For these documents, security is based on passwords. In this research paper, we analyzed the encryption process involved in word documents (Procedure involved in document protection). We also discussed various password cracking possibilities and steps involved in the attacks. Also discussed various password cracking tools for analysis of password of doc files and performed salt analysis on the same. We analyzed the randomness of the salt for the same key at different times, with different name and also based on the size of the documents. We focused on John the Ripper (JtR) tool with single mode, word list, and incremental mode to reduce the file and memory complexity of brute force attack. Discussed performance analysis of password cracking based on CPU and GPUs. We analyzed the randomness of the salt for the same key with same document with different time and same documents with different name and size of the documents. We focused on John the Ripper (JtR) tool reducing the file and memory complexity of brute force attacks. Discussed performance analysis of password cracking based on CPU and GPUswith and without writing the dictionaries.</p> Padmavathi Guddeti, Narendar Dharavath, Sriramudu, VenuNalla Copyright (c) 2020 COMPUSOFT: An International Journal of Advanced Computer Technology Fri, 31 Jul 2020 16:28:05 +0000 A review on recent advances in Deep learning for Sentiment Analysis: Performances, Challenges and Limitations <p>Nowadays&nbsp; by the horizons of social online media keep expanding, the impacts they have on people are huge. For example, many businesses are taking advantage on the input from social media to advertise to specific target market. This is done by detecting and analysing the sentiment (emotions, feelings, opinions) in social media about any topic or product from the texts. There are numerous machine learning as well as natural language processing methods used to examine public opinions with low time complexity. Deep learning techniques, however, have become widely popular in recent times because of their high efficiency and accuracy. This paper provides a complete overview of the common deep learning frameworks used in sentiment analysis in recent time. We offer a taxonomical study of text representations, learning model, evaluation, metrics, and implications of recent advances in deep learning architectures. We also added a special emphasis on deep learning methods, the key findings and limitations of different authors are discussed and this will hopefully help other researchers to do further development of deep learning methods in text processing especially for sentiment analysis. The research also presents the quick summaries of the most popular datasets, lexicons with their related research, performance and main features of the datasets.&nbsp; The aim of this survey is to emphasize the ability to solve text-based sentiment analysis challenges in deep learning architectures with successful achievement for accuracy, speed with context, syntactic and semantic meaning. This review paper analyses uniquely with the progress and recent advances in sentiment analysis based on recently advanced of existing methods and approach based on deep learning with their findings, performance comparisons and the limitations and others important features.</p> Md Shofiqul Islam Shofiqul, Ngahzaifa Ab Ghani, Md Manjur Ahmed Copyright (c) 2020 COMPUSOFT: An International Journal of Advanced Computer Technology Sat, 01 Aug 2020 00:00:00 +0000 A Novel Barcode Generation and Verification System for Fraud Prevention <p>Barcode technology is an automatic identification system that provides an effective means of collecting data to facilitate the automatic scanning of information. It is typically used in the sale of goods in supermarkets to make the checkout as fast as possible. However, several security issues have come to light, most notably barcode substitution fraud. This paper therefore proposes the use of a digital watermarking technique to create a barcode that cannot be regenerated. To read this barcode, a novel authentication system was introduced that used a neural network. The proposed barcode and its system were implemented and evaluated through experimental studies of 5000 barcode samples. The results were extremely promising as they showed that the proposed barcode can successfully be identified as legitimate or fake.</p> Suliman Alsuhibany, Ghadah Alhumud , Shahalel Almudaifer Copyright (c) 2020 COMPUSOFT: An International Journal of Advanced Computer Technology Tue, 04 Aug 2020 00:00:00 +0000