Research Cell: An International Journal of Engineering Sciences

Pardeep Bhandari ¹, Manpreet Singh ²

Affiliations
1 Doaba College, Jalandhar, IN
2 Punjabi University, Patiala, IN

Abstract

As the computer network has evolved to provide the user many services, the attacks on these networks to disrupt the services and to gain access to resources has also evolved. New entities in form of services, hardware, network protocols etc. are being added to the network, which is leading to new ways to attack the network. The complexity of the system is increasing so fast that it is becoming increasingly difficult for network administrator to comprehend the situation and react in an appropriate manner. Situation becomes more complex as there is not uniform terminology. Though serious efforts in form of Common Vulnerability Enumeration (CVE), Common Weakness Enumeration (CWE), Common Attack Pattern Enumeration and Classification(CAPEC) etc. has been made, still a long way is to go. In this paper we model a computer network by modelling its components i.e. hardware, software, services using ontology. Also vulnerabilities and attacks on these computers are modelled. We populate our ontology with various instances of vulnerabilities, CVSS scores, attacks and possible services in the network. Knowledge representation methods are used in order to provide Description Logic reasoning and inference over network security status concept. Secondly we propose an ontology based system which predicts probable attacks using inference and information provided by the environment. Results show that proposed method is scalable for large systems and also flexible to incorporate new evolutions in the field of study.

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Manpreet Singh ¹, Sandeep Singh Gill ²

Affiliations
1 University College of Engineering, Punjabi University, Patiala, IN
2 Guru Nanak Dev Engineering College, Ludhiana, IN

Abstract

Quadratic Rotation decomposition (QRD) based recursive least squares (RLS) algorithm can be used in variety of communication applications and its low complexity implementation can be of interest. In this paper we have presented FPGA implementation of QRD based RLS algorithm using Coordinate Rotation by Digital Computer (CORDIC) operator. FPGA resource estimates along with actual implementation results illustrating the weight calculation delays have also been presented presented.

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Pardeep Bhandari ¹, Manpreet Singh ²

Affiliations
1 Doaba College, Jalandhar, Punjab, IN
2 Punjabi University, Patiala, Punjab, IN

Abstract

Traditionally network security deals with maintaining the confidentiality of information, authenticating the user and making the resources available reliably to the intended user, but now apart from these concerns which are at the stake in public networks other important factors are availability and survivability of services which are available on the computer networks. The current generation network security means like intrusion detection system, firewalls, virus detection system etc. present only one of the dimensions of a multidimensional problem of overall network security status. These tools provide detailed information about one aspect of the network security. The task of correlating the events happening in the network and being reported by these tools is left to network administrator. The number of services being made available through these networks is increasing exponentially and so is the number of users of these networks. This paper explores a new concept Network Security Situational Awareness (NSSA). Network Security Situational Awareness is a discipline which focuses on perception, evaluation, projection and resolution of the security risk to computer networks. In this paper the term situational Awareness is explained in context of computer network security. So the ischolar_main of the term NSSA is explored. Various techniques employed to achieve NSSA have been explored in this survey paper. The conceptual model for NSSA and its functional requirements are also discussed.

Keywords

Situational Awareness, NSSA, Multi Sensor Data.

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Arshdeep Kaur ¹, Manpreet Singh ¹

Affiliations
1 Dept. of Information Technology, Guru Nanak Dev Engineering College, Ludhiana, Punjab, IN

Abstract

Bioinformatics is a platform that developing a framework that supports the existing and upcoming technologies for decision making. Bioinformatics main motive is to develop tools that analyzes and execute biological data for better results. Major Focus of research is on the practices that understand and utilize data from innovative technologies and translate these to real application. The branch of science which deals with the study of relationship among different group of organisms and their evolutionary history is called Phylogenetic. These relationships are evaluated by different methods that analyses the observed values of different species or population such as DNA sequences. The result is known as Phylogency. The dataset varies from living to non living population. POWER, Delign, BLAST, HMM (Hidden Markov Model), ClustalW, MEGA6 were analyzed on different data ranges. R and RAXML tools are open source are capable of handling huge data in less space and time. POWER and CVTree3 (Third version of CVTree) tools also provide Web services. ClustalW tool performs well with similar length of sequences. HMM use series of successive instances of data and information of previous state that can be presented sequentially. PHYLIP tool is appropriate for prediction purpose. BLAST is effective in low to medium biological data. Handle Biological data efficiently with in limited resources and time is the main focus of research. R tool is more efficient in handling millions of observations. The comparison of different methods is discussed further in the table.

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Ankurdeep Kaur ¹, Manpreet Singh ², Priyanka Arora ¹

Affiliations
1 CSE Department, GNDEC, Ludhiana, IN
2 IT Department, GNDEC, Ludhiana, IN

Abstract

In an agricultural country like India, farmers have a wide range of diversity to select the appropriate fruit or vegetable for cultivation. However, then cultivation of crops for optimum yield and quality produce needs the aid of technological support. The most challenging task for a farmer is to differentiate between a diseased and non-diseased plant and to cure the diseased plant well in time. Thus, there are different techniques which can identify the diseased leaf on the basis of parameters like color, shape and texture. Pixel-to-pixel and similarity measure methods are used to distinguish between a healthy and an unhealthy leaf. These techniques when applied extensively to agricultural science proves to be significantly effective in the field of plant protection. The comparison of these techniques has been done further in the paper, which accounts for disease identification.

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