Papers by sarika choudhary
Research Square (Research Square), Jun 3, 2021
The advancements of technology are playing a significant role in protecting the data from intrude... more The advancements of technology are playing a significant role in protecting the data from intruders. In this paper, a robust network intrusion detection system (IDS) is proposed for Internet of Things (IoT) using deep learning approaches. The type of intrusions we adopted in this work are distributed denial of service (DDoS) and replay attack. Our proposed work is divided into three sections, namely, node deployment, threat detection modelling, and prevention modelling. For detection, ensemble algorithm has been used, i.e., deep neural network (DNN) and support vector machine (SVM). SVM is used to identify the suspected route and DNN is used to identify the suspected node out of suspected routes. The chosen route ensures that it is prevented from attackers by incorporating the throughput and packet delivery ratio (PDR). The simulation results are obtained on the basis of accuracy, recall, precision, and F-measure to determine the effectiveness of the proposed approach. The precision, recall, F-measure, and accuracy of correctly identified intruders are 98.12%, 98.04%, 94.88%, and 98.68%, respectively, which is an improvement over the previous studies. The efficacy of the designed model for IoT is compared with the existing approaches.
Detection and Prevention of Routing Attacks in Internet of Things
Internet of things (IoT) is the smart network which connects smart objects over the Internet. The... more Internet of things (IoT) is the smart network which connects smart objects over the Internet. The Internet is untrusted and unreliable network and thus IoT network is vulnerable to different kind of attacks. Conventional encryption and authentication techniques sometimes fail on IoT based network and intrusion may succeed to destroy the network. So, it is necessary to design intrusion detection system for such network. In our paper, we detect routing attacks such as sinkhole and selective forwarding. We have also tried to prevent our network from these attacks. We designed detection and prevention algorithm, i.e., KMA(Key Match Algorithm) and CBA(Cluster- Based Algorithm) in MatLab simulation environment. We gave two intrusion detection mechanisms and compared their results as well. True positive intrusion detection rate for our work is between 50% to 80% with KMA and 76% to 96% with CBA algorithm.
Internet of Things: Protocols, Applications and Security Issues
Procedia Computer Science, 2022
Cluster-Based Intrusion Detection Method for Internet of Things
Internet of Things (IoT) is an advanced network which joins intelligent devices with the internet... more Internet of Things (IoT) is an advanced network which joins intelligent devices with the internet. Most of IoT devices are having sensors, and their work is to monitor the behavior near us. As all the "things" are connected, it also increases the susceptibility of the network. Security attacks may happen at any time in the network and may adversely affect the network. One such attack that we have tried to address in this paper is intrusion detection. We proposed an intrusion detection algorithm in our paper. We worked on the detection of selective forwarding and sinkhole attack in the 6LoWPAN environment using routing protocol RPL. It consists of a hybrid intrusion detection method for detecting two routing attacks. The experimental results of our algorithm showed that it achieved a true positive rate of 96.3% and false positive rate of 6.1% when routing attacks (sinkhole and selective-forwarding) were launched simultaneously.
Analysis of KDD-Cup’99, NSL-KDD and UNSW-NB15 Datasets using Deep Learning in IoT
Procedia Computer Science, 2020
Abstract Internet of Things (IoT) network is the latest technology which is used to connect all t... more Abstract Internet of Things (IoT) network is the latest technology which is used to connect all the objects near us. Implementation of IoT technology is latest and growing day-by-day, it is coming with risk itself. So, it required the most efficient model to detect malicious activities as fast as possible and accurate. In our paper, we considered Deep Neural Network (DNN) for identifying the attacks in IoT. Intelligent intrusion detection system can only be built if there is availability of an effective dara set. Performance of DNN to correctly identify the attack has been evaluated on the most used data sets, i.e., KDD-Cup’99, NSL-KDD, and UNSW-NB15. Our experimental results showed the accuracy rate of the proposed method using DNN. It showed that accuracy rate is above 90% with each dataset.
A Survey
International Journal of Information Security and Privacy, 2019
The latest buzzword in internet technology nowadays is the Internet of Things. The Internet of Th... more The latest buzzword in internet technology nowadays is the Internet of Things. The Internet of Things (IoT) is an ever-growing network which will transform real-world objects into smart or intelligent virtual objects. IoT is a heterogeneous network in which devices with different protocols can connect with each other in order to exchange information. These days, human life depends upon the smart things and their activities. Therefore, implementing protected communications in the IoT network is a challenge. Since the IoT network is secured with authentication and encryption, but not secured against cyber-attacks, an Intrusion Detection System is needed. This research article focuses on IoT introduction, architecture, technologies, attacks and IDS. The main objective of this article is to provide a general idea of the Internet of Things, various intrusion detection techniques, and security attacks associated with IoT.
The study of this paper will describe the perspective view of legal issues and propose the altern... more The study of this paper will describe the perspective view of legal issues and propose the alternative approaches to protecting software. Some legal issues like copyright, patent and trademark are used for providing the security to the data and computer software. The main motive of this paper is to aware all the authors about the protection of data and their programs.
The advancements of technology are playing a significant role in protecting the data from intrude... more The advancements of technology are playing a significant role in protecting the data from intruders. In this paper, a robust network intrusion detection system (IDS) is proposed for Internet of Things (IoT) using deep learning approaches. The type of intrusions we adopted in this work are distributed denial of service (DDoS) and replay attack. Our proposed work is divided into three sections, namely, node deployment, threat detection modelling, and prevention modelling. For detection, ensemble algorithm has been used, i.e., deep neural network (DNN) and support vector machine (SVM). SVM is used to identify the suspected route and DNN is used to identify the suspected node out of suspected routes. The chosen route ensures that it is prevented from attackers by incorporating the throughput and packet delivery ratio (PDR). The simulation results are obtained on the basis of accuracy, recall, precision, and F-measure to determine the effectiveness of the proposed approach. The precision...
Internet of Things: Protocols, Applications and Security Issues
Procedia Computer Science
Journal of Scientific & Industrial Research
With the increase in number of IoT devices, the capabilities to provide reliable security and det... more With the increase in number of IoT devices, the capabilities to provide reliable security and detect the malicious activities within the IoT network have become quite challenging. We propose a hybrid classification approach to detect multi-class attacks in the IoT network. In the proposed model, Principle Component Analysis (PCA) is used to extract the useful features and Linear Discriminant Analysis (LDA) is used to reduce the high dimension data set into lower dimension space by keeping less number of important features. This was assisted by use of a combination of neural network and Support Vector Machine (SVM) classifiers to improve the detection rate and decrease the false alarm rate. The neural network, a multi-class classifier, is used to classify the intruders in the network with more accuracy. The SVM is an efficient and fast learner classifier which is used to classify the unmatched behavior. The proposed method needs less computation complexity for intrusion detection. The performance of the proposed model was evaluated on two benchmark datasets for intrusion detection, i.e., NSL-KDD and UNSW-NB15. Results show that our model outperforms existing models.
This Paper gives an introduction of Data Mining System and development of different data mining s... more This Paper gives an introduction of Data Mining System and development of different data mining systems. How many data mining tools or systems really exist? What are different platform under which these tools or systems has been designed? What are different areas for which these data mining system has been devised or developed. After doing study and research on data mining system. we have to decide which platform is best for the development of Data Mining System and to understand the importance of data mining system and platform on which it has been developed. As we know what is importance of data mining system for big and large organization, when the company is working in different parts of country and producing large amount of data then it very important to analyze that data which account for productivity and cost benefits from that data. Now it is important to understand that which part of the organization is giving benefit and where the organization is losing. So to take any dec...
Understanding Captcha: Text and Audio Based Captcha with its Applications
CAPTCHAs are short for Completely Automated Public Turing test to tell Computer and Humans Apart.... more CAPTCHAs are short for Completely Automated Public Turing test to tell Computer and Humans Apart. The purpose of a CAPTCHA is to block form submissions from spam bots - automated scripts that harvest email addresses from publicly available web forms. The term "CAPTCHA" was coined in 2000 by Luis Von Ahn, Manuel Blum, Nicholas J. Hopper (all of Carnegie Mellon University, and John Langford (then of IBM). CAPTCHAs are used because of the fact that it is difficult for the computers to extract the text from such a distorted image, whereas it is relatively easy for a human to understand the text hidden behind the distortions. Therefore, the correct response to a CAPTCHA challenge is assumed to come from a human and the user is permitted into the website. The CAPTCHA test helps identify which users are real human beings and which ones are computer programs.
Review of Sockets Used for Communication Purpose
Study of this paper will represent a perspective view on sockets which are used for communication... more Study of this paper will represent a perspective view on sockets which are used for communication purpose between two processes. In this paper we will discuss on types of sockets and their functions. Aim of brief discussion about TCP and UDP protocol sockets and functions.
Cluster-Based Intrusion Detection Method for Internet of Things
2019 IEEE/ACS 16th International Conference on Computer Systems and Applications (AICCSA), 2019
Internet of Things (IoT) is an advanced network which joins intelligent devices with the internet... more Internet of Things (IoT) is an advanced network which joins intelligent devices with the internet. Most of IoT devices are having sensors, and their work is to monitor the behavior near us. As all the "things" are connected, it also increases the susceptibility of the network. Security attacks may happen at any time in the network and may adversely affect the network. One such attack that we have tried to address in this paper is intrusion detection. We proposed an intrusion detection algorithm in our paper. We worked on the detection of selective forwarding and sinkhole attack in the 6LoWPAN environment using routing protocol RPL. It consists of a hybrid intrusion detection method for detecting two routing attacks. The experimental results of our algorithm showed that it achieved a true positive rate of 96.3% and false positive rate of 6.1% when routing attacks (sinkhole and selective-forwarding) were launched simultaneously.
The study of this paper will describe the perspective view of legal issues and propose the altern... more The study of this paper will describe the perspective view of legal issues and propose the alternative approaches to protecting software. Some legal issues like copyright, patent and trademark are used for providing the security to the data and computer software. The main motive of this paper is to aware all the authors about the protection of data and their programs.
Security is the primary concern in the modern world. The main focus of this paper is the security... more Security is the primary concern in the modern world. The main focus of this paper is the security of our information and its supporting infrastructure. By keeping the computer system secure we can provide the security to the computerized information and vital to that is the operating system. In order to have a secure operating system it must be supported by the suitable computer architecture. If the technology from which the OS is built and on which it is supported is not secure then there is no confidentiality in the security of the OS and of the information it maintains for the users. This is the short overview of OS Security. In this paper we will discuss about the security policies that can be supported by the system. Keywords-OS, infrastructure, integrity, scheduling, security
The problems start during data acquisition, when the bulk data requires us to make decisions, cur... more The problems start during data acquisition, when the bulk data requires us to make decisions, currently in an ad hoc manner, about what data to keep and what to discard, and how to store what we keep reliably with the right metadata. Many data today is not natively in structured format, for e.g.: blogs and tweets are weakly structured pieces of text, while images and video are structured for storage and display, but not for semantic content and search, so transforming such content into a structured format for later study is a major test. The objective of this paper is to discuss the characteristics of big data as well as the challenges and opportunities for big data analytics – the process of extracting knowledge from sets of big data. However, it is hard, requiring us to rethink data analysis systems in fundamental ways. A major speculation in Big Data, properly directed, can result not only in major scientific advances, but also place the foundation for the next generation of adva...
Detection and Prevention of Routing Attacks in Internet of Things
2018 17th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/ 12th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE), 2018
Internet of things (IoT) is the smart network which connects smart objects over the Internet. The... more Internet of things (IoT) is the smart network which connects smart objects over the Internet. The Internet is untrusted and unreliable network and thus IoT network is vulnerable to different kind of attacks. Conventional encryption and authentication techniques sometimes fail on IoT based network and intrusion may succeed to destroy the network. So, it is necessary to design intrusion detection system for such network. In our paper, we detect routing attacks such as sinkhole and selective forwarding. We have also tried to prevent our network from these attacks. We designed detection and prevention algorithm, i.e., KMA(Key Match Algorithm) and CBA(Cluster- Based Algorithm) in MatLab simulation environment. We gave two intrusion detection mechanisms and compared their results as well. True positive intrusion detection rate for our work is between 50% to 80% with KMA and 76% to 96% with CBA algorithm.
Saliency Detection in Text Documents using Policy-Driven Reinforcement Learning Methodologies
IOP Conference Series: Materials Science and Engineering, 2021
As the amount of information grows, it is challenging to find concise information. Thus it is nec... more As the amount of information grows, it is challenging to find concise information. Thus it is necessary to build a system that could present human quality summaries. Saliency detection is a tool that provides abstracts or keywords of a given document. In this paper, three different approaches have been implemented for saliency detection. In all these three approaches, sentences are represented as a feature vector. In the first approach, features like root words, vocabulary intersections, words, and inclusion of numerical data use. This model is trained by using general Algorithms, Like Porter’s Stemmer, Spell check. In the second approach, apart from the features used in the first approach, TF-IDF scores, Mean, Standard Deviation, and a Threshold value of a word is also used as features. In the third approach, Maximal Marginal Relevance (MMR) algorithm is used to generate a summary.
Analysis of KDD-Cup’99, NSL-KDD and UNSW-NB15 Datasets using Deep Learning in IoT
Procedia Computer Science, 2020
Abstract Internet of Things (IoT) network is the latest technology which is used to connect all t... more Abstract Internet of Things (IoT) network is the latest technology which is used to connect all the objects near us. Implementation of IoT technology is latest and growing day-by-day, it is coming with risk itself. So, it required the most efficient model to detect malicious activities as fast as possible and accurate. In our paper, we considered Deep Neural Network (DNN) for identifying the attacks in IoT. Intelligent intrusion detection system can only be built if there is availability of an effective dara set. Performance of DNN to correctly identify the attack has been evaluated on the most used data sets, i.e., KDD-Cup’99, NSL-KDD, and UNSW-NB15. Our experimental results showed the accuracy rate of the proposed method using DNN. It showed that accuracy rate is above 90% with each dataset.
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Papers by sarika choudhary