This paper describes how you can protect your system from Intrusion, which is the method of Intrusion Prevention and Intrusion Detection .The underlying premise of our Intrusion detection system is to describe attack as instance of ontology and its first need is to detect attack. In this paper, we propose a novel framework of autonomic intrusion detection that fulfills online and adaptive intrusion detection over unlabeled HTTP traffic streams in computer networks. The framework holds potential for self-governing: self-labeling, self-updating and self-adapting. Our structure employs the Affinity Propagation (AP) algorithm to learn a subject’s behaviors through dynamical clustering of the streaming data. It automatically labels the data and adapts to normal behavior changes while identifies anomalies.
Detecting Anomaly IDS in Network using Bayesian NetworkIOSR Journals
In a hostile area of network, it is a severe challenge to protect sink, developing flexible and adaptive
security oriented approaches against malicious activities. Intrusion detection is the act of detecting, monitoring
unwanted activity and traffic on a network or a device, which violates security policy. This paper begins with a
review of the most well-known anomaly based intrusion detection techniques. AIDS is a system for detecting
computer intrusions, type of misuse that falls out of normal operation by monitoring system activity and
classifying it as either normal or anomalous .It is based on Machine Learning AIDS schemes model that allows
the attacks analyzed to be categorized and find probabilistic relationships among attacks using Bayesian
network.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
An IDS (Intrusion detection system) is a device or software application that monitors network or system
activities for malicious activities or policy violations and produces reports to a management station. IDS
come in a variety of “flavors” and approach the goal of detecting suspicious traffic in different ways.
There are network based (NIDS) and host based (HIDS) intrusion detection systems. Some systems may
attempt to stop an intrusion attempt but this is neither required nor expected of a monitoring system.
Detecting Anomaly IDS in Network using Bayesian NetworkIOSR Journals
In a hostile area of network, it is a severe challenge to protect sink, developing flexible and adaptive
security oriented approaches against malicious activities. Intrusion detection is the act of detecting, monitoring
unwanted activity and traffic on a network or a device, which violates security policy. This paper begins with a
review of the most well-known anomaly based intrusion detection techniques. AIDS is a system for detecting
computer intrusions, type of misuse that falls out of normal operation by monitoring system activity and
classifying it as either normal or anomalous .It is based on Machine Learning AIDS schemes model that allows
the attacks analyzed to be categorized and find probabilistic relationships among attacks using Bayesian
network.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
An IDS (Intrusion detection system) is a device or software application that monitors network or system
activities for malicious activities or policy violations and produces reports to a management station. IDS
come in a variety of “flavors” and approach the goal of detecting suspicious traffic in different ways.
There are network based (NIDS) and host based (HIDS) intrusion detection systems. Some systems may
attempt to stop an intrusion attempt but this is neither required nor expected of a monitoring system.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Intrusion Detection Systems (IDSs) have become widely recognized as powerful tools for identifying, deterring and deflecting malicious attacks over the network. Intrusion detection systems (IDSs) are designed and installed to aid in deterring or mitigating the damage that can be caused by hacking, or breaking into sensitive IT systems. . The attacks can come from outsider attackers on the Internet, authorized insiders who misuse the privileges that have been given them and unauthorized insiders who attempt to gain unauthorized privileges. IDSs cannot be used in isolation, but must be part of a larger framework of IT security measures. Essential to almost every intrusion detection system is the ability to search through packets and identify content that matches known attacks. Space and time efficient string matching algorithms are therefore important for identifying these packets at line rate. In this paper we examine string matching algorithm and their use for Intrusion Detection. Keywords: System Design, Network Algorithm
Basic survey on malware analysis, tools and techniquesijcsa
The term malware stands for malicious software. It is a program installed on a system without the
knowledge of owner of the system. It is basically installed by the third party with the intention to steal some
private data from the system or simply just to play pranks. This in turn threatens the computer’s security,
wherein computer are used by one’s in day-to-day life as to deal with various necessities like education,
communication, hospitals, banking, entertainment etc. Different traditional techniques are used to detect
and defend these malwares like Antivirus Scanner (AVS), firewalls, etc. But today malware writers are one
step forward towards then Malware detectors. Day-by-day they write new malwares, which become a great
challenge for malware detectors. This paper focuses on basis study of malwares and various detection
techniques which can be used to detect malwares.
AN IMPROVED METHOD TO DETECT INTRUSION USING MACHINE LEARNING ALGORITHMSieijjournal
An intrusion detection system detects various malicious behaviors and abnormal activities that might harm
security and trust of computer system. IDS operate either on host or network level via utilizing anomaly
detection or misuse detection. Main problem is to correctly detect intruder attack against computer
network. The key point of successful detection of intrusion is choice of proper features. To resolve the
problems of IDS scheme this research work propose “an improved method to detect intrusion using
machine learning algorithms”. In our paper we use KDDCUP 99 dataset to analyze efficiency of intrusion
detection with different machine learning algorithms like Bayes, NaiveBayes, J48, J48Graft and Random
forest. To identify network based IDS with KDDCUP 99 dataset, experimental results shows that the three
algorithms J48, J48Graft and Random forest gives much better results than other machine learning
algorithms. We use WEKA to check the accuracy of classified dataset via our proposed method. We have
considered all the parameter for computation of result i.e. precision, recall, F – measure and ROC.
A Performance Analysis of Chasing Intruders by Implementing Mobile AgentsCSCJournals
An Intrusion Detection System in network fetches the intrusions information from systems by using Mobile Agents aid. Intrusion Detection System detects intrusions based on the collected information and routes the intrusion. The intelligent decisions on communications, permit agents to gain their goals more efficiently and provide more survivability and security of an agent system. The proposed model showed a formal representation of information assurance in agent messaging over a dynamic network by probability of redundant routes. The proposed Intrusion Detection System, chase intruders and collect information by the Mobile Agents. Our propose architecture is an information exchange method and chasing intrusion along with a method by implementing Mobile Agents.
Analysis and Design for Intrusion Detection System Based on Data MiningPritesh Ranjan
Reference:
Dyuanyang Zhao, Zhilin Feng, Qingxiang Xu, “Analysis and design for Intrusion detection system based on data mining” in proceedings of 2010 IEEE second international workshop on education technology and computer science
AN IMPROVED METHOD TO DETECT INTRUSION USING MACHINE LEARNING ALGORITHMSieijjournal1
An intrusion detection system detects various malicious behaviors and abnormal activities that might harm
security and trust of computer system. IDS operate either on host or network level via utilizing anomaly
detection or misuse detection. Main problem is to correctly detect intruder attack against computer
network. The key point of successful detection of intrusion is choice of proper features. To resolve the
problems of IDS scheme this research work propose “an improved method to detect intrusion using
machine learning algorithms”. In our paper we use KDDCUP 99 dataset to analyze efficiency of intrusion
detection with different machine learning algorithms like Bayes, NaiveBayes, J48, J48Graft and Random
forest. To identify network based IDS with KDDCUP 99 dataset, experimental results shows that the three
algorithms J48, J48Graft and Random forest gives much better results than other machine learning
algorithms. We use WEKA to check the accuracy of classified dataset via our proposed method. We have
considered all the parameter for computation of result i.e. precision, recall, F – measure and ROC.
An Efficient Classification Mechanism For Network Intrusion Detection System Based on Data Mining
Techniques:A Survey..........................................................................................................................1
Subaira A. S. and Anitha P.
Automated Biometric Verification: A Survey on Multimodal Biometrics ..............................................1
Rupali L. Telgad, Almas M. N. Siddiqui and Dr. Prapti D. Deshmukh
Design and Implementation of Intelligence Car Parking Systems ........................................................1
Ogunlere Samson, Maitanmi Olusola and Gregory Onwodi
Intrusion Detection Techniques for Mobile Ad Hoc and Wireless Sensor Networks..............................1
Rakesh Sharma, V. A. Athavale and Pinki Sharma
Performance Evaluation of Sentiment Mining Classifiers on Balanced and Imbalanced Dataset ...........1
G.Vinodhini and R M. Chandrasekaran
Demosaicing and Super-resolution for Color Filter Array via Residual Image Reconstruction and Sparse
Representation..................................................................................................................................1
Jie Yin, Guangling Sun and Xiaofei Zhou
Determining Weight of Known Evaluation Criteria in the Field of Mehr Housing using ANP Approach ..1
Saeed Safari, Mohammad Shojaee, Mohammad Tavakolian and Majid Assarian
Application of the Collaboration Facets of the Reference Model in Design Science Paradigm ...............1
Lukasz Ostrowski and Markus Helfert
Personalizing Education News Articles Using Interest Term and Category Based Recommender
Approaches .......................................................................................................................................1
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Intrusion Detection Systems (IDSs) have become widely recognized as powerful tools for identifying, deterring and deflecting malicious attacks over the network. Intrusion detection systems (IDSs) are designed and installed to aid in deterring or mitigating the damage that can be caused by hacking, or breaking into sensitive IT systems. . The attacks can come from outsider attackers on the Internet, authorized insiders who misuse the privileges that have been given them and unauthorized insiders who attempt to gain unauthorized privileges. IDSs cannot be used in isolation, but must be part of a larger framework of IT security measures. Essential to almost every intrusion detection system is the ability to search through packets and identify content that matches known attacks. Space and time efficient string matching algorithms are therefore important for identifying these packets at line rate. In this paper we examine string matching algorithm and their use for Intrusion Detection. Keywords: System Design, Network Algorithm
Basic survey on malware analysis, tools and techniquesijcsa
The term malware stands for malicious software. It is a program installed on a system without the
knowledge of owner of the system. It is basically installed by the third party with the intention to steal some
private data from the system or simply just to play pranks. This in turn threatens the computer’s security,
wherein computer are used by one’s in day-to-day life as to deal with various necessities like education,
communication, hospitals, banking, entertainment etc. Different traditional techniques are used to detect
and defend these malwares like Antivirus Scanner (AVS), firewalls, etc. But today malware writers are one
step forward towards then Malware detectors. Day-by-day they write new malwares, which become a great
challenge for malware detectors. This paper focuses on basis study of malwares and various detection
techniques which can be used to detect malwares.
AN IMPROVED METHOD TO DETECT INTRUSION USING MACHINE LEARNING ALGORITHMSieijjournal
An intrusion detection system detects various malicious behaviors and abnormal activities that might harm
security and trust of computer system. IDS operate either on host or network level via utilizing anomaly
detection or misuse detection. Main problem is to correctly detect intruder attack against computer
network. The key point of successful detection of intrusion is choice of proper features. To resolve the
problems of IDS scheme this research work propose “an improved method to detect intrusion using
machine learning algorithms”. In our paper we use KDDCUP 99 dataset to analyze efficiency of intrusion
detection with different machine learning algorithms like Bayes, NaiveBayes, J48, J48Graft and Random
forest. To identify network based IDS with KDDCUP 99 dataset, experimental results shows that the three
algorithms J48, J48Graft and Random forest gives much better results than other machine learning
algorithms. We use WEKA to check the accuracy of classified dataset via our proposed method. We have
considered all the parameter for computation of result i.e. precision, recall, F – measure and ROC.
A Performance Analysis of Chasing Intruders by Implementing Mobile AgentsCSCJournals
An Intrusion Detection System in network fetches the intrusions information from systems by using Mobile Agents aid. Intrusion Detection System detects intrusions based on the collected information and routes the intrusion. The intelligent decisions on communications, permit agents to gain their goals more efficiently and provide more survivability and security of an agent system. The proposed model showed a formal representation of information assurance in agent messaging over a dynamic network by probability of redundant routes. The proposed Intrusion Detection System, chase intruders and collect information by the Mobile Agents. Our propose architecture is an information exchange method and chasing intrusion along with a method by implementing Mobile Agents.
Analysis and Design for Intrusion Detection System Based on Data MiningPritesh Ranjan
Reference:
Dyuanyang Zhao, Zhilin Feng, Qingxiang Xu, “Analysis and design for Intrusion detection system based on data mining” in proceedings of 2010 IEEE second international workshop on education technology and computer science
AN IMPROVED METHOD TO DETECT INTRUSION USING MACHINE LEARNING ALGORITHMSieijjournal1
An intrusion detection system detects various malicious behaviors and abnormal activities that might harm
security and trust of computer system. IDS operate either on host or network level via utilizing anomaly
detection or misuse detection. Main problem is to correctly detect intruder attack against computer
network. The key point of successful detection of intrusion is choice of proper features. To resolve the
problems of IDS scheme this research work propose “an improved method to detect intrusion using
machine learning algorithms”. In our paper we use KDDCUP 99 dataset to analyze efficiency of intrusion
detection with different machine learning algorithms like Bayes, NaiveBayes, J48, J48Graft and Random
forest. To identify network based IDS with KDDCUP 99 dataset, experimental results shows that the three
algorithms J48, J48Graft and Random forest gives much better results than other machine learning
algorithms. We use WEKA to check the accuracy of classified dataset via our proposed method. We have
considered all the parameter for computation of result i.e. precision, recall, F – measure and ROC.
An Efficient Classification Mechanism For Network Intrusion Detection System Based on Data Mining
Techniques:A Survey..........................................................................................................................1
Subaira A. S. and Anitha P.
Automated Biometric Verification: A Survey on Multimodal Biometrics ..............................................1
Rupali L. Telgad, Almas M. N. Siddiqui and Dr. Prapti D. Deshmukh
Design and Implementation of Intelligence Car Parking Systems ........................................................1
Ogunlere Samson, Maitanmi Olusola and Gregory Onwodi
Intrusion Detection Techniques for Mobile Ad Hoc and Wireless Sensor Networks..............................1
Rakesh Sharma, V. A. Athavale and Pinki Sharma
Performance Evaluation of Sentiment Mining Classifiers on Balanced and Imbalanced Dataset ...........1
G.Vinodhini and R M. Chandrasekaran
Demosaicing and Super-resolution for Color Filter Array via Residual Image Reconstruction and Sparse
Representation..................................................................................................................................1
Jie Yin, Guangling Sun and Xiaofei Zhou
Determining Weight of Known Evaluation Criteria in the Field of Mehr Housing using ANP Approach ..1
Saeed Safari, Mohammad Shojaee, Mohammad Tavakolian and Majid Assarian
Application of the Collaboration Facets of the Reference Model in Design Science Paradigm ...............1
Lukasz Ostrowski and Markus Helfert
Personalizing Education News Articles Using Interest Term and Category Based Recommender
Approaches .......................................................................................................................................1
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Hybrid Intrusion Detection System using Weighted Signature Generation over An...Editor IJMTER
To provide security to network we use existing Intrusion Detection System(IDS) for
identification of known attack with low false alarm,but it is not working when unknown attacks
occurs so to identify unknown attacks we use Anomaly based IDS(ADS) with high false alarm.
HIDS is the combination of IDS and ADS with their advantages for identification of known as well
as unknown attack.IDS used signature based model to identify known attack and ADS used anomaly
based model for identification of unknown attack.HIDS used internet episode rules for identify
known as well as unknown attacks.
Optimized Intrusion Detection System using Deep Learning Algorithmijtsrd
A method and a system for the detection of an intrusion in a computer network compare the network traffic of the computer network at multiple different points in the network. In an uncompromised network the network traffic monitored at these two different points in the network should be identical. A network intrusion detection system is mostly place at strategic points in a network, so that it can monitor the traffic traveling to or from different devices on that network. The existing Software Defined Network SDN proposes the separation of forward and control planes by introducing a new independent plane called network controller. Machine learning is an artificial intelligence approach that focuses on acquiring knowledge from raw data and, based at least in part on the identified flow, selectively causing the packet, or a packet descriptor associated with the packet. The performance is evaluated using the network analysis metrics such as key generation delay, key sharing delay and the hash code generation time for both SDN and the proposed machine learning SDN. Prof P. Damodharan | K. Veena | Dr N. Suguna "Optimized Intrusion Detection System using Deep Learning Algorithm" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-2 , February 2019, URL: https://www.ijtsrd.com/papers/ijtsrd21447.pdf
Paper URL: https://www.ijtsrd.com/engineering/other/21447/optimized-intrusion-detection-system-using-deep-learning-algorithm/prof-p-damodharan
Survey on classification techniques for intrusion detectioncsandit
Intrusion detection is the most essential component
in network security. Traditional Intrusion
Detection methods are based on extensive knowledge
of signatures of known attacks. Signature-
based methods require manual encoding of attacks by
human experts. Data mining is one of the
techniques applied to Intrusion Detection that prov
ides higher automation capabilities than
signature-based methods. Data mining techniques suc
h as classification, clustering and
association rules are used in intrusion detection.
In this paper, we present an overview of
intrusion detection, KDD Cup 1999 dataset and detai
led analysis of different classification
techniques namely Support vector Machine, Decision
tree, Naïve Bayes and Neural Networks
used in intrusion detection.
An intrusion detection system (IDS) is an ad hoc security solution to protect flawed computer systems. It works
like a burglar alarm that goes off if someone tampers with or manages to get past other security mechanisms
such as authentication mechanisms and firewalls. An Intrusion Detection System (IDS) is a device or a software
application that monitors network or system activities for malicious activities or policy violations and produces
reports to a management station.Intrusion Detection System (IDS) has been used as a vital instrument in
defending the network from this malicious or abnormal activity..In this paper we are comparing host based and
network based IDS and various types of attacks possible on IDS.
Similar to Autonomic Anomaly Detection System in Computer Networks (20)
Due to availability of internet and evolution of embedded devices, Internet of things can be useful to contribute in energy domain. The Internet of Things (IoT) will deliver a smarter grid to enable more information and connectivity throughout the infrastructure and to homes. Through the IoT, consumers, manufacturers and utility providers will come across new ways to manage devices and ultimately conserve resources and save money by using smart meters, home gateways, smart plugs and connected appliances. The future smart home, various devices will be able to measure and share their energy consumption, and actively participate in house-wide or building wide energy management systems. This paper discusses the different approaches being taken worldwide to connect the smart grid. Full system solutions can be developed by combining hardware and software to address some of the challenges in building a smarter and more connected smart grid.
A Survey Report on : Security & Challenges in Internet of Thingsijsrd.com
In the era of computing technology, Internet of Things (IoT) devices are now popular in each and every domains like e-governance, e-Health, e-Home, e-Commerce, and e-Trafficking etc. Iot is spreading from small to large applications in all fields like Smart Cities, Smart Grids, Smart Transportation. As on one side IoT provide facilities and services for the society. On the other hand, IoT security is also a crucial issues.IoT security is an area which totally concerned for giving security to connected devices and networks in the IoT .As, IoT is vast area with usability, performance, security, and reliability as a major challenges in it. The growth of the IoT is exponentially increases as driven by market pressures, which proportionally increases the security threats involved in IoT The relationship between the security and billions of devices connecting to the Internet cannot be described with existing mathematical methods. In this paper, we explore the opportunities possible in the IoT with security threats and challenges associated with it.
In today’s emerging world of Internet, each and every thing is supposed to be in connected mode with the help of billions of smart devices. By connecting all the devises used in our day to day life, make our life trouble less and easy. We are incorporated in a world where we are used to have smart phones, smart cars, smart gadgets, smart homes and smart cities. Different institutes and researchers are working for creating a smart world for us but real question which we need to emphasis on is how to make dumb devises talk with uncommon hardware and communication technology. For the same what kind of mechanism to use with various protocols and less human interaction. The purpose is to provide the key area for application of IoT and a platform on which various devices having different mechanism and protocols can communicate with an integrated architecture.
Study on Issues in Managing and Protecting Data of IOTijsrd.com
This paper discusses variety of issues for preserving and managing data produced by IoT. Every second large amount of data are added or updated in the IoT databases across the heterogeneous environment. While managing the data each phase of data processing for IoT data is exigent like storing data, querying, indexing, transaction management and failure handling. We also refer to the problem of data integration and protection as data requires to be fit in single layout and travel securely as they arrive in the pool from diversified sources in different structure. Finally, we confer a standardized pathway to manage and to defend data in consistent manner.
Interactive Technologies for Improving Quality of Education to Build Collabor...ijsrd.com
Today with advancement in Information Communication Technology (ICT) the way the education is being delivered is seeing a paradigm shift from boring classroom lectures to interactive applications such as 2-D and 3-D learning content, animations, live videos, response systems, interactive panels, education games, virtual laboratories and collaborative research (data gathering and analysis) etc. Engineering is emerging with more innovative solutions in the field of education and bringing out their innovative products to improve education delivery. The academic institutes which were once hesitant to use such technology are now looking forward to such innovations. They are adopting the new ways as they are realizing the vast benefits of using such methods and technology. The benefits are better comprehensibility, improved learning efficiency of students, and access to vast knowledge resources, geographical reach, quick feedback, accountability and quality research. This paper focuses on how engineering can leverage the latest technology and build a collaborative learning environment which can then be integrated with the national e-learning grid.
Internet of Things - Paradigm Shift of Future Internet Application for Specia...ijsrd.com
In the world more than 15% people are living with disability that also include children below age of 10 years. Due to lack of independent support services specially abled (handicap) people overly rely on other people for their basic needs, that excludes them from being financially and socially active. The Internet of Things (IoT) can give support system and a better quality of life as well as participation in routine and day to day life. For this purpose, the future solutions for current problems has been introduced in this paper. Daunting challenges have been considered as future research and glimpse of the IoT for specially abled person is given in the paper.
A Study of the Adverse Effects of IoT on Student's Lifeijsrd.com
Internet of things (IoT) is the most powerful invention and if used in the positive direction, internet can prove to be very productive. But, now a days, due to the social networking sites such as Face book, WhatsApp, twitter, hike etc. internet is producing adverse effects on the student life, especially those students studying at college Level. As it is rightly said, something which has some positive effects also has some of the negative effects on the other hand. In this article, we are discussing some adverse effects of IoT on student’s life.
Pedagogy for Effective use of ICT in English Language Learningijsrd.com
The use of information and communications technology (ICT) in education is a relatively new phenomenon and it has been the educational researchers' focus of attention for more than two decades. Educators and researchers examine the challenges of using ICT and think of new ways to integrate ICT into the curriculum. However, there are some barriers for the teachers that prevent them to use ICT in the classroom and develop supporting materials through ICT. The purpose of this study is to examine the high school English teachers’ perceptions of the factors discouraging teachers to use ICT in the classroom.
In recent years usage of private vehicles create urban traffic more and more crowded. As result traffic becomes one of the important problems in big cities in all over the world. Some of the traffic concerns are traffic jam and accidents which have caused a huge waste of time, more fuel consumption and more pollution. Time is very important parameter in routine life. The main problem faced by the people is real time routing. Our solution Virtual Eye will provide the current updates as in the real time scenario of the specific route. This research paper presents smart traffic navigation system, based on Internet of Things, which is featured by low cost, high compatibility, easy to upgrade, to replace traditional traffic management system and the proposed system can improve road traffic tremendously.
Ontological Model of Educational Programs in Computer Science (Bachelor and M...ijsrd.com
In this work there is illustrated an ontological model of educational programs in computer science for bachelor and master degrees in Computer science and for master educational program “Computer science as second competence†by Tempus project PROMIS.
Understanding IoT Management for Smart Refrigeratorijsrd.com
Lately the concept of Internet of Things (IoT) is being more elaborated and devices and databases are proposed thereby to meet the need of an Internet of Things scenario. IoT is being considered to be an integral part of smart house where devices will be connected to each other and also react upon certain environmental input. This will eventually include the home refrigerator, air conditioner, lights, heater and such other home appliances. Therefore, we focus our research on the database part for such an IoT’ fridge which we called as smart Fridge. We describe the potentials achievable through a database for an IoT refrigerator to manage the refrigerator food and also aid the creation of a monthly budget of the house for a family. The paper aims at the data management issue based on a proposed design for an intelligent refrigerator leveraging the sensor technology and the wireless communication technology. The refrigerator which identifies products by reading the barcodes or RFID tags is proposed to order the required products by connecting to the Internet. Thus the goal of this paper is to minimize human interaction to maintain the daily life events.
DESIGN AND ANALYSIS OF DOUBLE WISHBONE SUSPENSION SYSTEM USING FINITE ELEMENT...ijsrd.com
Double wishbone designs allow the engineer to carefully control the motion of the wheel throughout suspension travel. 3-D model of the Lower Wishbone Arm is prepared by using CAD software for modal and stress analysis. The forces and moments are used as the boundary conditions for finite element model of the wishbone arm. By using these boundary conditions static analysis is carried out. Then making the load as a function of time; quasi-static analysis of the wishbone arm is carried out. A finite element based optimization is used to optimize the design of lower wishbone arm. Topology optimization and material optimization techniques are used to optimize lower wishbone arm design.
A Review: Microwave Energy for materials processingijsrd.com
Microwave energy is a latest largest growing technique for material processing. This paper presents a review of microwave technologies used for material processing and its use for industrial applications. Advantages in using microwave energy for processing material include rapid heating, high heating efficiency, heating uniformity and clean energy. The microwave heating has various characteristics and due to which it has been become popular for heating low temperature applications to high temperature applications. In recent years this novel technique has been successfully utilized for the processing of metallic materials. Many researchers have reported microwave energy for sintering, joining and cladding of metallic materials. The aim of this paper is to show the use of microwave energy not only for non-metallic materials but also the metallic materials. The ability to process metals with microwave could assist in the manufacturing of high performance metal parts desired in many industries, for example in automotive and aeronautical industries.
Web Usage Mining: A Survey on User's Navigation Pattern from Web Logsijsrd.com
With an expontial growth of World Wide Web, there are so many information overloaded and it became hard to find out data according to need. Web usage mining is a part of web mining, which deal with automatic discovery of user navigation pattern from web log. This paper presents an overview of web mining and also provide navigation pattern from classification and clustering algorithm for web usage mining. Web usage mining contain three important task namely data preprocessing, pattern discovery and pattern analysis based on discovered pattern. And also contain the comparative study of web mining techniques.
APPLICATION OF STATCOM to IMPROVED DYNAMIC PERFORMANCE OF POWER SYSTEMijsrd.com
Application of FACTS controller called Static Synchronous Compensator STATCOM to improve the performance of power grid with Wind Farms is investigated .The essential feature of the STATCOM is that it has the ability to absorb or inject fastly the reactive power with power grid . Therefore the voltage regulation of the power grid with STATCOM FACTS device is achieved. Moreover restoring the stability of the power system having wind farm after occurring severe disturbance such as faults or wind farm mechanical power variation is obtained with STATCOM controller . The dynamic model of the power system having wind farm controlled by proposed STATCOM is developed . To validate the powerful of the STATCOM FACTS controller, the studied power system is simulated and subjected to different severe disturbances. The results prove the effectiveness of the proposed STATCOM controller in terms of fast damping the power system oscillations and restoring the power system stability.
Making model of dual axis solar tracking with Maximum Power Point Trackingijsrd.com
Now a days solar harvesting is more popular. As the popularity become higher the material quality and solar tracking methods are more improved. There are several factors affecting the solar system. Major influence on solar cell, intensity of source radiation and storage techniques The materials used in solar cell manufacturing limit the efficiency of solar cell. This makes it particularly difficult to make considerable improvements in the performance of the cell, and hence restricts the efficiency of the overall collection process. Therefore, the most attainable maximum power point tracking method of improving the performance of solar power collection is to increase the mean intensity of radiation received from the source used. The purposed of tracking system controls elevation and orientation angles of solar panels such that the panels always maintain perpendicular to the sunlight. The measured variables of our automatic system were compared with those of a fixed angle PV system. As a result of the experiment, the voltage generated by the proposed tracking system has an overall of about 28.11% more than the fixed angle PV system. There are three major approaches for maximizing power extraction in medium and large scale systems. They are sun tracking, maximum power point (MPP) tracking or both.
A REVIEW PAPER ON PERFORMANCE AND EMISSION TEST OF 4 STROKE DIESEL ENGINE USI...ijsrd.com
In day today's relevance, it is mandatory to device the usage of diesel in an economic way. In present scenario, the very low combustion efficiency of CI engine leads to poor performance of engine and produces emission due to incomplete combustion. Study of research papers is focused on the improvement in efficiency of the engine and reduction in emissions by adding ethanol in a diesel with different blends like 5%, 10%, 15%, 20%, 25% and 30% by volume. The performance and emission characteristics of the engine are tested observed using blended fuels and comparative assessment is done with the performance and emission characteristics of engine using pure diesel.
Study and Review on Various Current Comparatorsijsrd.com
This paper presents study and review on various current comparators. It also describes low voltage current comparator using flipped voltage follower (FVF) to obtain the single supply voltage. This circuit has short propagation delay and occupies a small chip area as compare to other current comparators. The results of this circuit has obtained using PSpice simulator for 0.18 μm CMOS technology and a comparison has been performed with its non FVF counterpart to contrast its effectiveness, simplicity, compactness and low power consumption.
Reducing Silicon Real Estate and Switching Activity Using Low Power Test Patt...ijsrd.com
Power dissipation is a challenging problem for today's system-on-chip design and test. This paper presents a novel architecture which generates the test patterns with reduced switching activities; it has the advantage of low test power and low hardware overhead. The proposed LP-TPG (test pattern generator) structure consists of modified low power linear feedback shift register (LP-LFSR), m-bit counter, gray counter, NOR-gate structure and XOR-array. The seed generated from LP-LFSR is EXCLUSIVE-OR ed with the data generated from gray code generator. The XOR result of the sequence is single input changing (SIC) sequence, in turn reduces the switching activity and so power dissipation will be very less. The proposed architecture is simulated using Modelsim and synthesized using Xilinx ISE9.2.The Xilinx chip scope tool will be used to test the logic running on FPGA.
Defending Reactive Jammers in WSN using a Trigger Identification Service.ijsrd.com
In the last decade, the greatest threat to the wireless sensor network has been Reactive Jamming Attack because it is difficult to be disclosed and defend as well as due to its mass destruction to legitimate sensor communications. As discussed above about the Reactive Jammers Nodes, a new scheme to deactivate them efficiently is by identifying all trigger nodes, where transmissions invoke the jammer nodes, which has been proposed and developed. Due to this identification mechanism, many existing reactive jamming defending schemes can be benefited. This Trigger Identification can also work as an application layer .In this paper, on one side we provide the several optimization problems to provide complete trigger identification service framework for unreliable wireless sensor networks and on the other side we also provide an improved algorithm with regard to two sophisticated jamming models, in order to enhance its robustness for various network scenarios.
বাংলাদেশের অর্থনৈতিক সমীক্ষা ২০২৪ [Bangladesh Economic Review 2024 Bangla.pdf] কম্পিউটার , ট্যাব ও স্মার্ট ফোন ভার্সন সহ সম্পূর্ণ বাংলা ই-বুক বা pdf বই " সুচিপত্র ...বুকমার্ক মেনু 🔖 ও হাইপার লিংক মেনু 📝👆 যুক্ত ..
আমাদের সবার জন্য খুব খুব গুরুত্বপূর্ণ একটি বই ..বিসিএস, ব্যাংক, ইউনিভার্সিটি ভর্তি ও যে কোন প্রতিযোগিতা মূলক পরীক্ষার জন্য এর খুব ইম্পরট্যান্ট একটি বিষয় ...তাছাড়া বাংলাদেশের সাম্প্রতিক যে কোন ডাটা বা তথ্য এই বইতে পাবেন ...
তাই একজন নাগরিক হিসাবে এই তথ্য গুলো আপনার জানা প্রয়োজন ...।
বিসিএস ও ব্যাংক এর লিখিত পরীক্ষা ...+এছাড়া মাধ্যমিক ও উচ্চমাধ্যমিকের স্টুডেন্টদের জন্য অনেক কাজে আসবে ...
How to Build a Module in Odoo 17 Using the Scaffold MethodCeline George
Odoo provides an option for creating a module by using a single line command. By using this command the user can make a whole structure of a module. It is very easy for a beginner to make a module. There is no need to make each file manually. This slide will show how to create a module using the scaffold method.
A Strategic Approach: GenAI in EducationPeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
it describes the bony anatomy including the femoral head , acetabulum, labrum . also discusses the capsule , ligaments . muscle that act on the hip joint and the range of motion are outlined. factors affecting hip joint stability and weight transmission through the joint are summarized.
Executive Directors Chat Leveraging AI for Diversity, Equity, and InclusionTechSoup
Let’s explore the intersection of technology and equity in the final session of our DEI series. Discover how AI tools, like ChatGPT, can be used to support and enhance your nonprofit's DEI initiatives. Participants will gain insights into practical AI applications and get tips for leveraging technology to advance their DEI goals.
June 3, 2024 Anti-Semitism Letter Sent to MIT President Kornbluth and MIT Cor...Levi Shapiro
Letter from the Congress of the United States regarding Anti-Semitism sent June 3rd to MIT President Sally Kornbluth, MIT Corp Chair, Mark Gorenberg
Dear Dr. Kornbluth and Mr. Gorenberg,
The US House of Representatives is deeply concerned by ongoing and pervasive acts of antisemitic
harassment and intimidation at the Massachusetts Institute of Technology (MIT). Failing to act decisively to ensure a safe learning environment for all students would be a grave dereliction of your responsibilities as President of MIT and Chair of the MIT Corporation.
This Congress will not stand idly by and allow an environment hostile to Jewish students to persist. The House believes that your institution is in violation of Title VI of the Civil Rights Act, and the inability or
unwillingness to rectify this violation through action requires accountability.
Postsecondary education is a unique opportunity for students to learn and have their ideas and beliefs challenged. However, universities receiving hundreds of millions of federal funds annually have denied
students that opportunity and have been hijacked to become venues for the promotion of terrorism, antisemitic harassment and intimidation, unlawful encampments, and in some cases, assaults and riots.
The House of Representatives will not countenance the use of federal funds to indoctrinate students into hateful, antisemitic, anti-American supporters of terrorism. Investigations into campus antisemitism by the Committee on Education and the Workforce and the Committee on Ways and Means have been expanded into a Congress-wide probe across all relevant jurisdictions to address this national crisis. The undersigned Committees will conduct oversight into the use of federal funds at MIT and its learning environment under authorities granted to each Committee.
• The Committee on Education and the Workforce has been investigating your institution since December 7, 2023. The Committee has broad jurisdiction over postsecondary education, including its compliance with Title VI of the Civil Rights Act, campus safety concerns over disruptions to the learning environment, and the awarding of federal student aid under the Higher Education Act.
• The Committee on Oversight and Accountability is investigating the sources of funding and other support flowing to groups espousing pro-Hamas propaganda and engaged in antisemitic harassment and intimidation of students. The Committee on Oversight and Accountability is the principal oversight committee of the US House of Representatives and has broad authority to investigate “any matter” at “any time” under House Rule X.
• The Committee on Ways and Means has been investigating several universities since November 15, 2023, when the Committee held a hearing entitled From Ivory Towers to Dark Corners: Investigating the Nexus Between Antisemitism, Tax-Exempt Universities, and Terror Financing. The Committee followed the hearing with letters to those institutions on January 10, 202
How to Add Chatter in the odoo 17 ERP ModuleCeline George
In Odoo, the chatter is like a chat tool that helps you work together on records. You can leave notes and track things, making it easier to talk with your team and partners. Inside chatter, all communication history, activity, and changes will be displayed.
A workshop hosted by the South African Journal of Science aimed at postgraduate students and early career researchers with little or no experience in writing and publishing journal articles.
Autonomic Anomaly Detection System in Computer Networks
1. IJSRD - International Journal for Scientific Research & Development| Vol. 2, Issue 09, 2014 | ISSN (online): 2321-0613
All rights reserved by www.ijsrd.com 471
Autonomic Anomaly Detection System in Computer Networks
Professor Rahul. P. More1, Aniket V. Bagal2, Sangram P. Bajare3
, Abhilash S. Gaikawd4
Sameer S. Joshi5
1,2,3,4,5
Computer Engineering
1,2,3,4,5
DCOER, Pune, India
Abstract— This paper describes how you can protect your
system from Intrusion, which is the method of Intrusion
Prevention and Intrusion Detection .The underlying premise
of our Intrusion detection system is to describe attack as
instance of ontology and its first need is to detect attack. In
this paper, we propose a novel framework of autonomic
intrusion detection that fulfills online and adaptive intrusion
detection over unlabeled HTTP traffic streams in computer
networks. The framework holds potential for self-governing:
self-labeling, self-updating and self-adapting. Our structure
employs the Affinity Propagation (AP) algorithm to learn a
subject’s behaviors through dynamical clustering of the
streaming data. It automatically labels the data and adapts to
normal behavior changes while identifies anomalies.
Key words: Intrusion Prevention and Intrusion Detection,
ontology, Autonomic intrusion detection, Affinity
Propagation
I. INTRODUCTION
An Intrusion Detection System is Used to detect all types of
malicious network traffic and computer usage that can’t be
detected by a conventional firewall. This includes network
attacks against vulnerable services , data driven attacks
on applications , host based attacks such as privilege
escalation , unauthorized logins and access to sensitive
files and malware such as viruses , Trojan horses and
worms . While Signature-based Detection can only
recognize known attacks, anomaly detection holds great
potential for detecting unforeseen intrusion attempts. As
new attacks appear very frequently and signature-based
detection methods may be over-whelmed by
polymorphic attack , using anomaly detection sensors to
discover zero-day attacks has become a necessity rather than
an option.
A. Types of Intrusion Detection System
1) Current IDS fall into three Categories:
Network Based Intrusion Detection System
(NIDS’s): Identifies intrusions by examining
network traffic and monitors multiple hosts.
Network Intrusion Detection System gain access to
network traffic by connecting to a hub, network
switch configured for port mirroring or network
tap.
Example: SNORT
Once a NIDS detects an attack, the following
action may be taken:
Send email notification
Send an SNMP trap to a network
management system
Send a page (to a pager)
Block a TCP connection
Kill a TCP connection
Run a user defined script
Host-Based Intrusion Detection System (HIDS’s):
Consists of an agent on a host which identifies
intrusions by analyzing system calls, application
logs, file-system modification (binaries, password
files, and capability / acl databases) and other host
activities and state. In most cases, a HIDS
component is made up of two parts: a centralized
manager and server agent. The manager is used to
administer and store policies, download policies to
agents and store information received by agents.
The agent is installed onto each server and
registered with the manager. Agents use policies to
detect and respond to specific events and attacks.
Hybrid Intrusion Detection System: combines one
or more approaches. Host agent data is combined
with network information to form a comprehensive
view of the network. Example: Prelude.
II. SIGNATURE BASED DETECTION
In misuse detection, attacks follow well-defined patterns
that exploit system weakness and application software.
Since these attacks follow well-defined patterns and
signatures, they are usually encoded in advance and
thereafter used to match against the client conduct. It
suggests that abuse discovery requires specific knowledge of
given intrusive behavior. In a signature based detection a
predetermined attack patterns in the form of signatures and
these signatures are further used to determine the system
assaults. They typically analyze the system activity with
predefined signatures and each time database is updated. An
example of Signature Based Intrusion Detection System is
SNORT.
A worm is any malicious code that has the
capability to replicate and spread on its own. It works on the
scan, compromise and replicate principle. First it scans the
network to find hosts having vulnerabilities and then
exploits these vulnerabilities to compromise the target and
finally replicates itself on the target. Viruses, on other hand
can’t spread on their own. They attach to some other
programs and depend on these programs to spread in the
network. Every worm has a unique bit string which can be
used to identify the worm (i.e. all instances of the worm in
the network have the same bit string representation).
This Technique is not very effective because of the
following reasons.
A) Speed with which worm spreads: Worm can spread
at enormous speeds. Example. Sapphire / Slammer
worm infected more than 75,000 vulnerable hosts
in less than 10 minutes. Hence any technique which
2. Autonomic Anomaly Detection System in Computer Networks
(IJSRD/Vol. 2/Issue 09/2014/105)
All rights reserved by www.ijsrd.com 472
involves manual extraction of worms will fail to
match the speed at which worms spread. By the
time signature of the worm is identified, millions of
hosts would have been infected.
B) Zero day Worms: The above technique will fail
against zero day worms. Zero day worms are those
worms that exploit the vulnerabilities that have not
been declared yet or the worms that start spreading
as soon as (on the same day) some vulnerability is
made public.
III. ANOMALY BASED DETECTION
An Anomaly-Based Intrusion Detection System is a
system for detecting computer intrusions and misuse by
monitoring system activity and classifying it as either
normal or anomalous. The classification is based on
heuristics or rules, rather than patterns alternately mark, and
will catch any kind of abuse that differs significantly from
normal system operation. Earlier, IDS’s relied on some hand
coded rules designed by security experts and network
administrators. However, given the requirements and the
complexities of the today’s network environments, we need
a systematic and automated IDS development process rather
that the pure knowledge based and engineering approaches
which rely only on intuition and experience. This
encouraged us to study some Data Mining based
frameworks for Intrusion detection. These frameworks use
data mining algorithms to compute activity patterns for
system audit data and extract predictive features from the
patterns. Machine learning algorithms are then applied to the
audit records that are processed according to the feature
definitions to generate intrusion detection rules.
The most common way people approach network
intrusion detection is to detect statistical anomalies. The idea
behind this approach is to measure a “Baseline” of such stats
as CPU utilization, disc activity, user logins, file activity,
and so forth. Then, the system can trigger when there is
deviation from the baseline.
The benefit of this approach is that it can detect the
anomalies without having to understand the underlying
cause behind the anomalies. While most existing anomaly
detection methods classify events as either normal or
anomalous, as a mechanism for autonomic detection, we
define the third status of events as suspicious which is
between normal and anomalous.
Fig 1: Steps in IDS
IV. NEED FOR IDS
Internet Information Services (IIS) web servers – which host
web pages and serve them to users are highly popular
among business organizations, with over 6 million such
servers installed worldwide. Unfortunately, IIS web servers
are also popular among hackers and malicious fame-seekers
– as a prime target for attacks. As a result, every so often,
new exploits emerge which endanger your IIS web server’s
integrity and stability. Many administrators have a hard time
keeping up with the various security patches released for IIS
to cope with each new exploit, making it easy for malicious
users to find a vulnerable web server on the internet.
V. BENEFITS OF AUTONOMIC IDS
In today’s corporate market, the majority of businesses
consider the internet as a major tool for communication with
their customers, business partners and the corporate
community. this mentality is here to stay ; as a result
business need to consider the risk associated with using the
Internet as communication tool , and the methods available
to them to mitigate these risks . Many businesses are already
aware of the types of risks that they are facing, and have
implemented measures such as firewalls, Virus detection
software, access control mechanisms etc.
Determined hacker is just that “determined” and they
will find a way of penetrating your system, sometimes for
malicious intent but mostly because they can and it is a test
of skills. While the above mentioned tools are preventive
measures, an IDS is more of an analysis tool , that will give
you the following information:
Instance of attack
Method of attack
Source of attack
Signature of attack
3. Autonomic Anomaly Detection System in Computer Networks
(IJSRD/Vol. 2/Issue 09/2014/105)
All rights reserved by www.ijsrd.com 473
VI. LIMITATIONS OF IDS
Network Intrusion Detection systems are unreliable enough
that they should be considered only as secondary systems
designed to backup the primary security system.
Primary system such as firewalls, encryption and
authentication are rock solid. Bugs or misconfiguration.
Often lead to problems in these systems, but the
underlying concepts are “provably” accurate. Intrusion
detection system suffer from the two problems whereby
normal traffic causes many false positives (cry wolf) , and
careful hackers can evade or disable the intrusion detection
system. Indeed, there are many proofs that show how
network intrusion detection systems will never be accurate.
This doesn’t mean intrusion detection systems are
invalid. Hacking is so pervasive on today’s networks that
people are regularly astounded when they first install such
systems (both inside and outside firewall). Good intrusion
detection system can dramatically improve the security of a
site. It just needs to be remembered that intrusion detection
system are backup.
VII. CONCLUSION
The current generations of IDS (HIDS and NIDS) are quite
effective already as they continue to improve they will
become the backbone of more flexible security systems we
expect to see in the not-too-distant future. Online and
adaptive anomaly intrusion detection is difficult task
because no a priori knowledge (e.g. data distribution as well
as labeled information) can be provided to the learning
methods. The frameworks holds potential for self-
governing: self- labeling, self-adapting, self-updating.
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