A STATE OF THE ART SURVEY ON POLYMORPHIC MALWARE ANALYSIS AND DETECTION TECHNIQUES

Nowadays, systems are under serious security threats caused by malicious software, commonly known as malware. Such malwares are sophisticatedly created with advanced techniques that make them hard to analyse and detect, thus causing a lot of damages. Polymorphism is one of the advanced techniques by which malware change their identity on each time they attack. This paper presents a detailed systematic and critical review that explores the available literature, and outlines the research efforts that have been made in relation to polymorphic malware analysis and their detection

Towards a robust and affordable Automatic Weather Station

The frequency and severity of extreme weather events have increased over the last 30 years, making predictability of weather a challenge. Weather extreme events often cause adverse impacts to lives and property. Thus, accurate and timely provision of weather data is becoming crucial to improve the skill of weather prediction and to strengthen resilience to the impacts of the adverse weather conditions. Uganda and many developing countries have challenges in acquiring accurate and timely weather data due to their sparse weather observation networks. The sparse weather observation networks are in part attributed to the high cost of acquiring an Automatic Weather Station (AWS) and limited funding to national meteorological services of the respective countries. The inability of developing countries to manufacture their own AWSs leads to high recurring costs accruing from importation and maintenance. In this study, we propose an AWS based on Wireless Sensor Networks. We plan to design three generations of the AWS prototype, the first being the subject of this paper. The purpose of this paper is therefore to evaluate the first-generation AWS prototype and to propose improvements for the second-generation, based on needs and requirements. Results from the AWS prototype data suggest improving non-functional requirements such as reliability, data accuracy, power consumption and data transmission in order to have an operational AWS. The non-functional requirements combined with cost reduction produces a robust and affordable AWS. Therefore, developing countries like Uganda will be able to acquire the AWSs in reasonable quantities, hence improvement in weather forecasts

A Joint Power, Delay and Rate Optimization Model for Secondary Users in Cognitive Radio Sensor Networks

To maximize the limited spectrum among primary users and cognitive Internet of Things (IoT) users as we save the limited power and energy resources available, there is a need to optimize network resources. Whereas it is quite complex to study the impact of transmission rate, transmission power or transmission delay alone, the complexity is aggravated by the simultaneous consideration of all these three variables jointly in addition to a channel selection variable, since it creates a non-convex problem. Our objective is to jointly optimize the three major variables; transmission power, rate and delay under constraints of Bit Error Rate (BER), interference and other channel limitations. We analyze how total power, rate and delay vary with packet size, network size, BER and interference. The resulting problem is solved using a branch-and-cut polyhedral approach. For simulation of results, we use MATLAB together with the state-of-the-art BARON software. It is observed that an increase in packet size generally leads to an increase in total rate, total power and total transmission delay. It is also observed that increasing the number of secondary users on the channel generally leads to an increased power, delay and rate