Security Issues of 5th Generation Technology: A Review

In the 20th century, communication placed an important role in our life, whereas 5G technology is known to be the central area for future networking infrastructure. However, with the high pace of gigantic assaults and protection issues, users and other organizations are not quite sure of the security parameters. In this article, we spotlight the elementary security doubts of 5G Technology. A large portion of the data based on literature and studies released by famous networking giants. Consequently, the paper can illuminate it peruses on what is required from 5G Technology and what are fundamental issues in accomplishing those objects

Performance Enhancement of VNSIP approach, using MCAC algorithm

Ad Hoc Networks provide a real opportunity to design flexible networks, very simple to deploy. However they remain a particular computation environment, characterized by the deficiency of pre-existed and centralized infrastructure. In the other hand, SIP protocol, which knows a huge booming in internet networks, requires centralized entities, like proxy server, registrar server and location service; consequently SIP is not adapted to Ad Hoc networks. We have presented in a new technique VNSIP (Virtual Network for Session Initiation Protocol) to fix the problem related to constraints of SIP deployment in MANET (Mobile Ad Hoc Networks). In this paper we use a new algorithm which we have called MCAC (MANET Call Admission Control) to improve VNSIP Performances

Structural Analysis of Enhanced Performance Organic Light Emitting Diodes (OLEDs)

We present a detailed study on structure of Organic LEDs (OLEDs) that promise flexibility and enhanced performance. Ordinary LEDs fail when it comes to need of ultra-smart size, thin, flexible smart screens and high efficiency light sources. With electroluminescent layer made of organic compounds, OLEDs promise all such features. We did a comprehensive analysis to find what structural features distinguish OLEDs from semiconductor LEDs. We found that it is the special six layered structure with organic emissive layer and delocalized charges due to weak pi bonds that enable OLEDs to perform better. We dis-cuss a few limitations related to production and life of these LEDs and suggest possible solutions to overcome these challenges. A rigorous, in-depth analysis of this structure is imperative to further comprehend the working of this device in order to make future devices cheaper and more efficient

Threat Detection using Machine/Deep Learning in IOT Environments

The quality of human life is improving day by day and IOT plays a very important role in this improvement. Everything related to internet have some security concerns. This paper aims to improve the security in IOT environments. In any of the IOT networks the unknown and knows flaws can be a backdoor for any adversary. The increase use of such environment results in the increase of zero day cyber-attacks. This paper aims to focus on different models of DL in order to predict the attacks in IOT environments. The main aim of this research is to provide a very best solution for the detection of threats in order to improve the infrastructures of IOT. In this paper different experiments has been conducted and its results has been discussed in order to provide an effective solution

Neural Network Web-Based Human Resource Management System Model (NNWBHRMSM)

As business activities are becoming increasing globally and as numerous firms expand their operations into overseas markets, there is need for human resource management (HRM) to ensure that they hire and keep good employees. From ages, firms/organizations have been having great problems in getting the right professionals into appropriate jobs and training. This research focuses at exploiting information technology in order to overcome these problems. The system, which is a network of inter–related processes, collects data from applicants through a web-based interface and matches with appropriate jobs. This prevents the frustration and some other problems inherent in the manual method of job recruitment, which is the traditional unstructured interview and knowledge based method for matching applicants to jobs. The proposed system is a neural network web-based human resource management system model running on Internet Information (IIS) server with capabilities for Active Server Page (ASP) and Microsoft Access; while Hypertext Markup Language (HTML) are used for authoring web pages. Finally, the system can run on the minimum Pentium machines with Windows XP operating system

Energy Efficient Linear and Non-Linear Precoders for Massive MIMO Systems

The term Massive MIMO means, Massive multiple input multiple output also known as (large-scale antenna system, very large MIMO). Massive Multiple-Input-MultipleOutput (MIMO) is the major key technique for the future Fifth Generation (5G) of mobile wireless communication network due to its characteristics, elements and advantages. Massive MIMO will be comprised of five major elements; antennas, electronic components, network architectures, protocols and signal processing. We realize that precoding technique is a processing technique that utilizes Channel State Information Technique (CSIT) by operating on the signals before transmitting them. This technique varies base on the type of CSIT and performance criterion. Precoding technique is the last digital processing block at the transmitting side. In this paper, linear and non-linear Precoding technique was reviewed and we proposed two techniques under each that is Minimum Mean Square Error (MMSE), Block Diagonalization (BD), Tomlinson-Harashima (TH) and Dirty paper coding (DPC). Four Precoding techniques: MMSE, BD, DPC and TH were used in the studies to power consumption, energy efficiency and area throughput for single-cell and multi-cell scenarios. In comparing the proposed techniques, in terms of energy efficiency and area throughput, reuse factor (Reuse 4) performs better than other techniques when there is an imperfect CSI is used

Man in the Middle Attacks: Analysis, Motivation and Prevention

Computer systems and applications are improving day by day and with the advancement in such area it give birth to new cyber-attacks. Man in the Middle attacks (MITM) are one of those attacks. An attack where an outsider or third party enters in between two online users, where both of the users are unaware of it. The malware in such scenario mainly monitors and have the ability to change the information which is classified onsly to these two users. Mainly it is knows as a protocol to an unauthorized user within the system who can access as well as change the information of the system without leaving any trace to the existing users. This issue is critical. This paper aims to the understanding of the MITM and to understand its different categories. Finally this paper aims to present some of mechanism for the prevention of such attacks and to identify some of the future research directions in such area

Secure Virtualization for Cloud Environment Using Guest OS and VMM-based Technology

Cloud computing, the utility base computing, is going to become the mainstream of IT future. Governments and enterprises are realizing that by immigrating into the cloud they can significantly enhance their current infrastructure or application services with minimum cost and maximum elasticity. But securing cloud user digital assets and addressing privacy concerns of cloud costumers has become serious challenge. Providing security in cloud always has to consider performance. Employing high secure methods with massive complexity will increase overall service cost, to address this problem in this paper a two- tier security architecture is proposed. This architecture use multiple work mode for security components in guest level to decrease security process over-head and a security supervisory in hypervisor layer to make sure avoiding from false security alarms

Tampering Reveal Technique for Iris Images

Nowadays, many biometric based security systems depend on the iris images for authentication because of their features and ease of use. However, storing and sharing these sensitive images through open access networks will expose them to tampering. In order to ensure the safety of the iris images, this paper presents a new tampering reveal technique based on watermarking in the transform domain. In the proposed technique, the iris region is selected and isolated using interactive segmentation process (ISA). The authentication bits have been generated from the iris region (IR) and embedded in the Slantlet transform coefficients of the remaining part of the iris image which has been named as non-iris region (NIR). The use of ISA ensures the intactness of IR because it has been excluded from the embedding process. Several experiments have been conducted to test the visual quality, capacity, payload, and the tampering reveal performance. The experiments proved the ability of the proposed technique to reveal and localize any tampering in IR, in addition, the difference between the original iris image and the watermarked iris image is imperceptible

An Efficient Approach of Threat Hunting Using Memory Forensics

The capacity and occurrence of new cyber-attacks have shattered in recent years. Such measures have very complicated workflows and comprise multiple illegal actors and organizations. Threat hunting demonstrates the process of proactively searching through networks for threats based on zero-day attacks by repeating the hunting process again and again. Unlike threat intelligence, it uses different automated security tools to collect logs in order to provide a pattern for making new intelligence-based tools by following those logs. According to our research findings about “threat hunting tools” there’s a major flaw that the designed tools are limited to the collection of logs. It works completely on logs for generating new patterns avoiding system’s main memory. Codes written directly to memory fail this process to provide proactive hunting. To overcome this major challenge, we are proposing two distinct methods, either by generating malicious code alerts or by binding memory forensics processes with threat hunting tools to make active hunting possible