Friday, October 30, 2020

SECURE STRATEGY FOR OPTICAL IMAGE ENCRYPTION SYSTEM BASED ON AMPLITUDE MODULATION, PHASE MODULATION AND MODIFIED LOGISTIC MAP

Author :  Ahmed M. Elshamy

Affiliation :  Department of Network and Security, College of Information Technology, Fujairah University

Country :  Egypt

Category :  Computer Science & Information Technology

Volume, Issue, Month, Year :  8, 18, February, 2018

Abstract :

This paper presents an optical image encryption system based completely on amplitude modulation, phase modulation in the discrete Fourier transform and modified chaotic logistic map. Amplitude modulation and phase modulation are accomplished by the use of spatial light modulator (SLM). SLMs are normally used to control incident light in amplitude-best, phasebest or the mixture (amplitude-phase). The random amplitude modulation based on a chaotic Baker map is carried out in time domain, while the random phase modulation is accomplished in the frequency domain. In this paper, we proposed a technique to regulate and enhance protection in a chaotic logistic map method leading to increased variety of key space of the logistic map. This causes our encryption system to become exceptionally sturdy against brute pressure. An exhaustive analysis of the proposed encryption system is undergone and shows positive results in encryption metrics when compared to several different photo encryption techniques. The analysis demonstrates the highly valued security and immunity to noise of the photograph encryption. The proposed modified logistic map with amplitude and phase modulation is suitable for real-time application.

Keyword :  Image Encryption, Fourier Transform, Security, Chaotic Logistic Map, Chaotic Baker Map

For More Detailshttps://airccj.org/CSCP/vol8/csit89808.pdf


Thursday, October 29, 2020

PREDICTING SECURITY CRITICAL CONDITIONS OF CYBER PHYSICAL SYSTEMS WITH UNOBSERVABLES AND OBSERVATION TIMES

 Author :  Alessio Coletta

Affiliation :  Security and Trust Unit, Bruno Kessler Foundation

Country :  Italy

Category :  Computer Science & Information Technology

Volume, Issue, Month, Year :  8, 18, February, 2018

Abstract :

Cyber Physical Systems (CPS), like IoT and industrial control systems, are typically vulnerable to cyber threats due to a lack of cyber security measures and hard change management. Security monitoring is aimed at improving the situational awareness and the resilience to cyber attacks. Solutions tailored to CPS are required for greater effectiveness. This work proposes a monitoring framework that leverages the knowledge of the system to monitor in order to specify, check, and predict known critical conditions. This approach is particularly suitable to CPS, as they are designed for a precise purpose, well documented, and predictable to a good extent. The framework uses a formal logical language to specify quantitative critical conditions and an optimisation SMT-based engine that checks observable aspects from network traffic and logs. The framework computes a quantitative measure of the criticality of the current CPS system: checking how criticality changes in time enables to predict whether the system is approaching to a critical condition or reaching back a licit state. An important novelty of the approach is the capability of expressing conditions on the time of the observations and of dealing with unobservable variables. This work presents the formal framework, a prototype, a testbed, and first experimental results that validate the feasibility of the approach.

Keyword :  Security Monitoring, Detection and Prevention Systems, Critical Infrastructures, Cyber Physical Systems, SMT.

For More Detailshttps://airccj.org/CSCP/vol8/csit89807.pdf

CAMOUFLAGED WITH SIZE: A CASE STUDY OF ESPIONAGE USING ACQUIRABLE SINGLE-BOARD COMPUTERS

 Author :  Kiavash Satvat

Affiliation :  University of Illinois at Chicago

Country :  USA

Category :  Computer Science & Information Technology

Volume, Issue, Month, Year :  8, 18, February, 2018

Abstract :

Single-Board Computers (SBC) refer to pocket-sized computers built on a single circuit board. A number of studies have explored the use of these highly popular devices in a variety of domains, including military, agriculture, healthcare, and more. However, no attempt was made to signify possible security risks that misuse of these devices may bring to organizations. In this study, we perform a series of experiments to validate the possibility of using SBCs as an espionage gadget. We show how an attacker can turn a Raspberry Pi device to an attacking gadget and benefit from short-term physical access to attach the gadget to the network in order to access unauthorized data or perform other malicious activities. We then provide experimental results of placing such tools in two real-world networks. Given the small size of SBCs, traditional physical security measures deployed in organizations may not be sufficient to detect and restrict the entrance of SBCs to their premises. Therefore, we reiterate possible directions for network administrators to deploy defensive mechanisms for detecting and preventing such attacks

Keyword :  Espionage, Single-Board Computer (SBC), Physical Security, Network Security, Raspberry Pi

For More Detailshttps://airccj.org/CSCP/vol8/csit89806.pdf

Monday, October 26, 2020

DATA MANAGEMENT PLATFORM SUPPORTING VOLUNTEER OCCUPATION SERVICES

 Author :  Damien Nicolas

Affiliation :  LIST: Luxembourg Institute of Science and Technology

Country :  Luxembourg

Category :  Computer Science & Information Technology

Volume, Issue, Month, Year :  8, 18, February, 2018

Abstract :

This paper deals with the Data Management Services, which acts as a link between the User Requirements, the System Requirements and the development of the core IT software components supporting the occupation services performed during the Sponsor project. This gives an overview of the main services provided by the platform, the chosen architecture model including the relationships between the different conceptual models and the data models implemented within the platform. As a result, the outcomes of this deliverable will constitute an input for the development of the platform as a services-oriented platform providing and publishing a complete API for managing organizations, opportunities and volunteers.

Keyword :  Data Model, SOA, RESTful Web Services, IT service platform, Ambient Assisted Living, Graph Database, Volunteering Services.

For More Details https://airccj.org/CSCP/vol8/csit89805.pdf

Thursday, October 22, 2020

VIRTUAL AIS GENERATION MANAGEMENT SYSTEM FOR WATERWAY RISK ASSESSMENT

Author :  Jun Sik Kim

Affiliation :  Division of Computer Engineering, Dongseo University

Country :  Korea

Category :  Computer Science & Information Technology

Volume, Issue, Month, Year :  8, 18, February, 2018

Abstract :

The virtual Automatic Identification System (AIS) generation management system is a system for analysing waterway risk by generating virtual AIS data which contains location information of a specific area. The system uses the data as an input data of the IALA Waterway Risk Assessment (IWRAP).

Keyword : Shipwreck, waterway risk assessment

URLhttps://airccj.org/CSCP/vol8/csit89804.pdf

Tuesday, October 20, 2020

FUZZY BOOLEAN REASONING FOR DIAGNOSIS OF DIABETES

 Author :  Mohamed Benamina

Affiliation :  Laboratoire d’Informatique d’Oran (LIO) University of Oran 1 Ahmed Ben Bella BP 1524, El M'Naouer Es Senia

Country :  Algeria

Category :  Computer Science & Information Technology

Volume, Issue, Month, Year :  8, 18, February, 2018

Abstract :

The classification by inductive learning finds its originality in the fact that humans often use it to resolve and to handle very complex situations in their daily lives. However, the induction in humans is often approximate rather than exact. Indeed, the human brain is able to handle imprecise, vague, uncertain and incomplete information. Also, the human brain is able to learn and to operate in a context where uncertainty management is indispensable. In this paper, we propose a Boolean model of fuzzy reasoning for indexing the monitoring sub-plans, based on characteristics of the classification by inductive learning. Several competing motivations have led us to define a Boolean model for CBR knowledge base systems. Indeed, we have not only desired experiment with a new approach to indexing of cases by fuzzy decision tree, but we also wanted to improve modelling of the vague and uncertain of the natural language concepts, optimize response time and the storage complexity.

Keyword :  Boolean Modelling, Cellular Machine, Case-Based Reasoning, Diabetes Diagnosis, Fuzzy Reasoning, Planning.

For More Detailshttps://airccj.org/CSCP/vol8/csit89803.pdf

Sunday, October 18, 2020

AN ONTOLOGY-BASED HIERARCHICAL BAYESIAN NETWORK CLASSIFICATION MODEL TO PREDICT THE EFFECT OF DNA REPAIRS GENES IN HUMAN AGEING PROCESS

 Author :  Hasanein Alharbi

Affiliation :  Department of Computer Engineering Techniques, Al-Mustaqbal University College

Country :  Iraq

Category :  Computer Science & Information Technology

Volume, Issue, Month, Year :  8, 18, February, 2018

Abstract :

Conventional Data Mining (DM) algorithms treated data simply as numbers ignoring the semantic relationships among them. Consequently, recent researches claimed that ontology is the best option to represent the domain knowledge for data mining use because of its structural format. Additionally, it is reported that ontology can facilitate different steps in the Bayesian Network (BN) construction task. To this end, this paper investigates the advantages of consolidating the Gene Ontology (GO) and the Hierarchical Bayesian Network (HBN) classifier in a flexible framework, which preserves the advantages of both, ontology and Bayesian theory. The proposed Semantically Aware Hierarchical Bayesian Network (SAHBN) is tested using data set in the biomedical domain. DNA repair genes are classified as either ageing-related or nonageing-related based on their GO biological process terms. Furthermore, the performance of SAHBN was compared against eight conventional classification algorithms. Overall, SAHBN has outperformed existing algorithms in eight experiments out of eleven.

Keyword :  Semantic Data Mining, Hierarchical Bayesian Network, Gene Ontology, DNA Repair Gene, Human Ageing Process

For More Details  :  https://airccj.org/CSCP/vol8/csit89802.pdf


Thursday, October 15, 2020

ANDROID UNTRUSTED DETECTION WITH PERMISSION BASED SCORING ANALYSIS

Author :  JACKELOU SULAPAS MAPA

Affiliation :  College of Information Technology Saint Joseph Institute of Technology

Country :  Philippines

Category :  Computer Science & Information Technology

Volume, Issue, Month, Year :  8, 18, February, 2018

Abstract :

Android smart phone is one of the fast growing mobile phones and because of these it the one of the most preferred target of malware developer. Malware apps can penetrate the device and gain privileges in which it can perform malicious activities such reading user contact, misusing of private information such as sending SMS and can harm user by exploiting the users private data which is stored in the device. The study is about detecting untrusted on android applications, which would be the basis of all future development regarding malware detection. The smartphone users worldwide are not aware of the permissions as the basis of all malicious activities that could possibly operate in an android system and may steal personal and private information. Android operating system is an open system in which users are allowed to install application from any unsafe sites. However permission mechanism of and android system is not enough to guarantee the invulnerability of the application that can harm the user. In this paper, the permission scoring-based analysis that will scrutinized the installed permission and allows user to increase the efficiency of Android permission to inform user about the risk of the installed Android application, in this paper, the framework that would classify the level of sensitivity of the permission access by the application. The framework uses a formula that will calculate the sensitivity level of the permission and determine if the installed application is untrusted or not. Our result show that, in a collection of 26 untrusted application, the framework is able to correct and determine the application's behavior consistently and efficiently.

Keyword :  Permission, permission scoring-based, malware Android phone, Security, Internet, malware.

For More Detailshttp://airccj.org/CSCP/vol8/csit89801.pdf

Tuesday, October 13, 2020

ENSEMBLE LEARNING BASED VOTING MODEL FOR DYNAMIC PROFILE CLASSIFICATION AND PROJECT ALLOTMENT

 Author :  Suhas Tangadle Gopalakrishna

Affiliation :  Infosys Limited, Bengaluru

Country :  India

Category :  Computer Science & Information Technology

Volume, Issue, Month, Year :  8, 16, February, 2018

Abstract :

Every year, lakhs of students right from college enter professional life through various recruitment activities conducted by the organization. The allotment of projects to the new recruits, carried out by the HR team of the organization is usually a manual affair. It is a time consuming and a tedious process as it involves manually opening each resume and analysing it one by one in order to assign a project. Companies round the globe are leveraging the power of artificial intelligence and machine learning to increase their productivity. In this paper, we present one such use case wherein artificial intelligence is leveraged by the organisation in allotment of projects to the new recruits. Current machine learning tools help in the allotment of projects to a few known popular domains on which the classifier has been trained explicitly. We tackle the problem with an ensemble learning based voting classifier consisting of 5 individual machine learning classifiers, voting to classify the profile of the candidate into the relevant domain. The knowledge extracted from the profiles for which there is no majority consensus among the individual classifiers is used to retrain the model. The proposed model achieves a higher accuracy in classifying resumes to proper domains than a standard machine learning classifier which is solely dependent on the training set for classification. Overall, emphasis is laid out on building a dynamic machine learning automation tool which is not solely dependent on the training data in allotment of projects to the new recruits.

Keyword :  Ensemble learning based voting classifier, Dynamic classification, Artificial Intelligence, Resume classifier, Association Rule Learning, Latent Dirichlet Allocation

For More Details https://airccj.org/CSCP/vol8/csit89607.pdf

Monday, October 12, 2020

OBJECT LOCALIZATION AND ACTIVITIES IDENTIFICATION USING ATTRIBUTE DETAILS IN SMART MEETING ROOMS

 Author :  Dian Andriana

Affiliation :  Research Center for Informatics, Indonesian Institute of Sciences

Country :  Indonesia

Category :  Computer Science & Information Technology

Volume, Issue, Month, Year :  8, 16, February, 2018

Abstract :

This paper is concerned with the development of interactive systems for smart meeting rooms. Automated recognition of video events is an important research area. We present an LTL (Linear Temporal Logic) model of basic objects and activities recognition in smart meeting rooms using object attribute details. There are still problems of misrecognizing objects in existing visual recognition methods because lack of enough feature attributive information details. This paper investigates morphological approach to increase recognition accuracy using variability in a limited area of moving object using object attribute details. The proposed methods are also compared to popular and recent methods of visual object and event recognition.

Keyword :  Events Recognition and Tracking, Morphological Feature Characteristics

For More Details :  https://airccj.org/CSCP/vol8/csit89606.pdf

Sunday, October 11, 2020

A PAPR REDUCTION TECHNIQUE IN OFDM SYSTEMS WITH A LARGE NUMBER OF SUBCARRIERS

Author :  Yasuhiro Shimazu

Affiliation :  Department of Electrical Engineering, Tokyo University of Science

Country :  Japan

Category :  Computer Science & Information Technology

Volume, Issue, Month, Year :  8, 16, February, 2018

Abstract :

A major drawback of orthogonal frequency division multiplexing (OFDM) signals is extremely high peak-to-average power ratio (PAPR). Signals with high PAPR lead to a lowering of the energy efficiency of power amplifiers and the shortened operation time causes a serious problem in battery-powered wireless terminals. We have found the CAZAC precoding makes the PAPR of M-array quadrature amplitude modulation (M-QAM) OFDM signals into the PAPR of M-QAM single-carrier signals. Therefore, it can dramatically improve the PAPR of OFDM signals. However, to satisfy the 3GPP-LTE specification of frequency spectrum, severe bandpass filtering of CAZAC-OFDM signal lead to unacceptable regrowth of the PAPR. The paper provides available control procedure for PAPR and spectrum managements. It is confirmed that the CAZAC-OFDM signal controlled by our procedure maintains enough low PAPR and can provide comparable spectral specifications in the downlink channel of 3GPPLTE standard.

Keyword :  OFDM, CAZAC, PAPR, spectral specifications

For More Detailshttps://airccj.org/CSCP/vol8/csit89605.pdf

Friday, October 9, 2020

IOT-BASED HOME APPLIANCE SYSTEM (SMART FAN)

Author :  Mehran Ektesabi

Affiliation :  Swinburne University of Technology

Country :  Thailand

Category :  Computer Science & Information Technology

Volume, Issue, Month, Year :  8, 16, February, 2018

Abstract :

Smart home appliances such as smart fridge, smart lighting, and smart air conditioner are getting popular for home end users. Smart fans as one of those smart devices are a part of a smart home that can be assumed as a factor of comfort, which may also reduce the electricity cost due to its high efficiency. Hence, this project aims to develop an alternative smart fan tackled from a comfort and cost perspectives. This project is done using as minimum budget as possible by using a combination of the already-available parts of the market. It is expected to develop a prototype of a cheap smart fan, which in turn becomes the starting point to allow further development of other smart home appliances

Keyword :  Internet of Things, Smart Fan, Motor Control, Cost Analysis, Cloud Infrastructure

For More Detailshttps://airccj.org/CSCP/vol8/csit89604.pdf

TIME-DOMAIN SIGNAL MANAGEMENT FOR OFDM SIGNALS

 Author :  Takuya Kazama

Affiliation :  2Faculty of Engineering, Tokyo University of Science

Country :  Japan

Category :  Computer Science & Information Technology

Volume, Issue, Month, Year :  8, 16, February, 2018

Abstract :

We have found out that the CAZAC- OFDM accords the amplitude of IFFT output signal with the amplitude of input DATA and the time ordering of IFFT output signal is unambiguously determined. That is, the OFDM time-domain signals, which are composed of many sinewaves, can be shaped by CAZAC precoder. As one application example that can use this characteristic of CAZAC precoder, we propose a new technique of symbol timing estimation, which enable to avoid the use of the preambles and guard-intervals. Conventional OFDM systems introduce guard-intervals for symbol timing estimation and reduction of multipath effect. Visible light communications (VLCs), which are one kind of line-of–sight communications, does not require consideration of the multipath channel. Therefore, if we embed null data at a fixed position in time-domain, we will easily estimate the symbol timing in the receiver side.

Keyword :  OFDM; CAZAC sequence; Zadoff-Chu sequence; Symbol Timing Estimation; VLC.

For More Details https://airccj.org/CSCP/vol8/csit89603.pdf

Wednesday, October 7, 2020

TIME-DOMAIN SIGNAL MANAGEMENT FOR OFDM SIGNALS

 Author :  Takuya Kazama

Affiliation :  Faculty of Engineering, Tokyo University of Science

Country :  Japan

Category :  Computer Science & Information Technology

Volume, Issue, Month, Year :  8, 16, February, 2018

Abstract :

We have found out that the CAZAC- OFDM accords the amplitude of IFFT output signal with the amplitude of input DATA and the time ordering of IFFT output signal is unambiguously determined. That is, the OFDM time-domain signals, which are composed of many sinewaves, can be shaped by CAZAC precoder. As one application example that can use this characteristic of CAZAC precoder, we propose a new technique of symbol timing estimation, which enable to avoid the use of the preambles and guard-intervals. Conventional OFDM systems introduce guard-intervals for symbol timing estimation and reduction of multipath effect. Visible light communications (VLCs), which are one kind of line-of–sight communications, does not require consideration of the multipath channel. Therefore, if we embed null data at a fixed position in time-domain, we will easily estimate the symbol timing in the receiver side.

Keyword :  OFDM; CAZAC sequence; Zadoff-Chu sequence; Symbol Timing Estimation; VLC.

For More Detailshttps://airccj.org/CSCP/vol8/csit89603.pdf


Monday, October 5, 2020

IMPROVED BLOCK STAGEWISE REGULARIZED ORTHOGONAL MATCHING PURSUIT IMAGE RECONSTRUCTION METHOD

 Author :  Xiong-yong Zhu

Affiliation :  Department of Computer Science, Guangdong University of Education Guangzhou

Country :  China

Category :  Computer Science & Information Technology

Volume, Issue, Month, Year :  8, 16, February, 2018

Abstract :

Traditional methods to signal acquisition need to collect large amounts of redundant data, and then compress the data to extract useful information, which is inefficient and requires large amount of storage resources. Compressed sensing (CS) can avoid sampling the redundant data; it obtains the discrete signals at the sampling rate that is lower than the Nyquist sampling rate, and reconstructs the original signal with high probability. Based on CS, Block Stagewise Regularized Orthogonal Matching Pursuit (StROMP) is proposed in this paper to reconstruct images. Simulation results show that the proposed algorithm can effectively reduce the required storage storages and computational complexity, which improves the quality of reconstructed images in the premise of ensuring a shorter reconstruction time.

Keyword :  Compressive Sensing; Matching Pursuit; Image Reconstruction

For More Detailshttps://airccj.org/CSCP/vol8/csit89602.pdf

AN INTELLIGENT BUSINESS INVENTORY MANAGEMENT APPLICATION USING ARTIFICIAL INTELLIGENCE AND VOICE RECOGNITION

 Author :  Zehao Li

Affiliation :  1University High School

Country :  USA

Category :  Computer Science & Information Technology

Volume, Issue, Month, Year :  8, 16, February, 2018

Abstract :

Virtual Enterprise, a class that simulates real-world business world, is designed for high school students to improve their experience in buying and selling. In Virtual Enterprise, various virtual products are created by classes. Each class is trying to sell products to students from different class in exhibitions. However, in trading, thousands of different types of handwritings made the salesperson in exhibitions are too difficult to be organized by administrator. To solve this problem, this paper develops an application, called Easy Exhibition, using Artificial Intelligence technology, which uses voice recognition technology to automatically complete the sales order by voice instead of by handwriting. The experiments show that AI-assisted solution improves both accuracy and efficiency in transaction processing.

Keyword :  Virtual Enterprise, Artificial Intelligence, Voice Recognition

For More Detailshttps://airccj.org/CSCP/vol8/csit89601.pdf

Friday, October 2, 2020

HOLISTIC APPROACH FOR CHARACTERIZING THE PERFORMANCE OF WIRELESS SENSOR NETWORKS

Author :  Amar Jaffar

Affiliation :  Electrical and Computer Engineering Department

Country :  USA

Category :  Computer Science & Information Technology

Volume, Issue, Month, Year :  8, 15, February, 2018

Abstract :

Researchers are actively investigating wireless sensor networks (WSNs) with respect to node design, architecture, networking protocols, and processing algorithms. However, few researchers consider the impact of deployments on the performance of a system. As a result, an appropriate deployment simulator that estimates the performance of WSNs concerning several deployment variables is needed. This paper presents a holistic deployment framework that assists decision makers in making optimum WSN deployment choices by considering the terrain of their region of interest and type of deployment. This framework employs empirical propagation models to predict the performance of the deployment in terms of connectivity, coverage, lifetime, and throughput for stochastic and deterministic deployments in dense tree, tall grass, and short grass environments. The outlined framework can serve as a useful prototype for creating deptaloyment simulators that optimize WSN deployments by considering terrain factors and type of deployment.

Keyword :  Wireless Sensor Networks, Stochastic Deployment, Deterministic Deployment & Terrain

For More Details https://airccj.org/CSCP/vol8/csit89510.pdf