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6th International Conference on Contemporary Computing and Informatics, IC3I 2023

作者： Madala, Ravikiran Amardeep, Rashmi Sowmya, S.R. Supriya, R.K. Nikshepa, T. Surabhi, K.R. University of Cumberlands Network and Data Center Engineer Ph.D Information Technology DurhamNC United States Dayananda Sagar Academy of Technology and Management Department of Information Science and Engineering Karnataka Bengaluru India

ISBN: (纸本)9798350304480

Cyber security tactics must be more potent and cunning due to the complexity of cybercrimes, which is always expanding. This will enable guard components to make real-time decisions that successfully counter sophisticated threats. The two scientists and professionals should be familiar with current methods for ensuring cyber security in order to aid in this. Implementing automated and expert cycles for recognizing cyber threats is one of the key aspects of cyber security. In light of artificial brain association, we describe an artificial intelligence (AI) cyber risk detection method in this analysis. They gave arrangement utilizes progressed learning-based detection procedures to improve cyber danger distinguishing proof and completely changes countless gathered security occasions into individual occasion profiles. The innovation centers around recognizing valid and bogus positive alerts with the goal those security reviewers can rapidly answer cyber attacks. The exploratory consequences of this study affirm the reasonableness of our proposed approach as a learning-based model for network shortcoming detection, and in any event, when this show is applied to real-world applications;it isn't equivalent to regular AI. It shows that it is better than the technique. © 2023 IEEE.

关键词： AI Artificial Intelligence Automated Cyber Attack detection Real-Time Security System

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Real-Time Cyber Attack detection Based on Automated Ai Security System

Real-Time Cyber Attack Detection Based on Automated Ai Secur...

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International Conference on Contemporary Computing and Informatics (IC3I)

作者： Ravikiran Madala Rashmi Amardeep Sowmya. S. R Supriya R. K Nikshepa. T K. R. Surabhi Network and Data Center Engineer Ph.D Information Technology University of Cumberlands Durham North Carolina United States Department of Information Science and Engineering Dayananda Sagar Academy of Technology and Management Bengaluru Karnataka India

Cyber security tactics must be more potent and cunning due to the complexity of cybercrimes, which is always expanding. This will enable guard components to make real-time decisions that successfully counter sophisticated threats. The two scientists and professionals should be familiar with current methods for ensuring cyber security in order to aid in this. Implementing automated and expert cycles for recognizing cyber threats is one of the key aspects of cyber security. In light of artificial brain association, we describe an artificial intelligence (AI) cyber risk detection method in this analysis. They gave arrangement utilizes progressed learning-based detection procedures to improve cyber danger distinguishing proof and completely changes countless gathered security occasions into individual occasion profiles. The innovation centers around recognizing valid and bogus positive alerts with the goal those security reviewers can rapidly answer cyber attacks. The exploratory consequences of this study affirm the reasonableness of our proposed approach as a learning-based model for network shortcoming detection, and in any event, when this show is applied to real-world applications; it isn't equivalent to regular AI. It shows that it is better than the technique.

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Automated AI Research on Cyber Attack Prediction and Security design 6

Automated AI Research on Cyber Attack Prediction and Securit...

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6th International Conference on Contemporary Computing and Informatics, IC3I 2023

作者： Madala, Ravikiran Vijayakumar, N. Nandini, N. Verma, Shanti Chandvekar, Samidha devendra Singh, devesh Pratap Network and Data Center Engineer Ph.D Information Technology University of Cumberlands DurhamNC United States Karpagam College of Engineering Department of Computer Science and Technology Coimbatore India Dr. Ambedkar Institute of Technology Department of Computer Science and Engineering Karnataka Bengaluru India L J University Department of Computer Application Gujarat Ahmedabad India Department of Information Technology Maharashtra New Panvel India Graphic Era Deemed to Be University Department of Computer Science and Engineering Uttrakhand Dehradun India

ISBN: (纸本)9798350304480

A fast expanding topic of study on automated AI is focused on the prediction and prevention of cyber-attacks using machine learning algorithms. In this study, we examined the research on applying machine learning algorithms to the problems of strategic cyber defense and attack forecasting. We also provided a technique for assessing and choosing the best machine learning models for anticipating cyber-attacks. Our findings show that machine learning methods, especially random forest and neural network models, are very accurate in predicting cyber-attacks. Additionally, we discovered a number of crucial characteristics, such as source IP, packet size, and malicious traffic that are strongly associated with the likelihood of cyber-attacks. Our results imply that automated AI research on cyber-attack prediction and security planning has tremendous promise for enhancing cyber-security and averting cyber-attacks. © 2023 IEEE.

关键词： automated AI research cyber-attack prediction feature correlation machine learning neural network random forest security design

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Research and Innovation in Next Generation Security and Privacy in Industry 5.0 Iot 6

Research and Innovation in Next Generation Security and Priv...

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6th International Conference on Contemporary Computing and Informatics, IC3I 2023

作者： Navale, Geeta S. Madala, Ravikiran Managuli, Manjunath Jayalakshmi, N. Kadiravan, G. Rawat, Ruchira Sinhgad Institute of Technology and Science Department of Computer Engineering Maharashtra Pune India Ph.D Information Technology Network and Data Center Engineer University of Cumberlands DurhamNC United States KLS Gogte Institute of Technology Department of Electronics and Communication Engineering Karnataka Belagavi India PSNA College of Engineering and Technology Master of Computer Applications Tamilnadu Dindigul India KL Deemed to Be University Department of Computer Science and Information Technology Andhra Pradsh India Graphic Era Deemed to Be University Department of Computer Science and Engineering Uttrakhand Dehradun India

ISBN: (纸本)9798350304480

The objective of the newest manufacturing paradigm, known as 'Industry 5.0,'is to combine human intelligence with cutting-edge technology like the Internet of Things (IoT), artificial intelligence (AI), and robots to develop production systems that are incredibly effective and adaptable. But as we rely more on these technologies, we face additional privacy and security issues that might affect how dependable and trustworthy these systems are. In this report, we examine the most recent advancements in security and privacy for Industry 5.0 IoT and pinpoint the newest trends, obstacles, and possibilities. We also cover how these changes may affect manufacturing in the future and provide advice to scholars, practitioners, and policymakers. © 2023 IEEE.

关键词： artificial intelligence cyber-physical systems human-machine collaboration Industry 5.0 Internet of Things IoT manufacturing privacy robotics security

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Research and Innovation to Market development: Artificial Intelligence in Business

Research and Innovation to Market Development: Artificial In...

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International Conference on Science technology engineering and Management (ICONSTEM)

作者： Nikitha Yathiraju P. Raman Ravikiran Madala Prashant Surgonda Patil Ashok Kumar S. Ashwin Ph. D in Information Technology University of Cumberlands Kentucky USA Department of Management Studies Panimalar Engineering College Poonamallee Chennai TamilNadu India Network and Data Center Engineer Ph.D Information Technology University of Cumberlands Durham North Carolina United States Department of Management Bharati Vidyapeeths IMRDA Sangli Sangli Maharashtra India Department of Mechanical Engineering New Horizon College of Engineering Bangalore Karnataka India

Showcasing has become complicated over the most recent multi decade with the presentation of Artificial Intelligence. Artificial Intelligence Promoting is a strategy of ideally using technology to upgrade client's insight. Nowadays, it has become really important for firms to recognise and understand the needs of their customers. Machine intelligence Nd their assumptions regarding items as well as administrations. The deductions acquired from the exploration will give a better comprehension of the developments and the effect of computer-based intelligence on businesses and society overall. It will likewise give a superior comprehension of how simulated intelligence can change the business tasks and hence the worldwide economy. We have dissected the information utilizing different recurrence table and diagrams and one way ANOVA strategy. Four distinct business boundaries are seen as necessary for the examination in order to understand how computer-based intelligence affects business. Artificial intelligence will assist the businesses with preparing themselves for confronting the difficulties because of the fast mechanical progressions in human existence and business. Man-made intelligence has been demonstrated to affect all the business activities decidedly, as it upgrades supportability and market administration.

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Cognitive defense Cyber Attack Prediction and Security design in Machine Learning Model 6

Cognitive Defense Cyber Attack Prediction and Security Desig...

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6th International Conference on Contemporary Computing and Informatics, IC3I 2023

作者： devadarshini, P.T. Chandrashekar, B. Pundir, Sumit Tiwari, Mohit Madala, Ravikiran Indhuma, E. Easwari Engineering College Department of Artificial Intelligence and Data Science TamilNadu Chennai India St. Martin's Engineering College Department of Computer Science and Engineering Kompalli Telangana Secunderabad India Graphic Era Deemed to Be University Department of Computer Science and Engineering Uttrakhand Dehradun India Bharati Vidyapeeth's College of Engineering Department of Computer Science and Engineering Delhi India Network and Data Center Engineer Ph.D Information Technology University of Cumberlands DurhamNC United States St.Martln's Engineering College Department of Computer Science and Engineering Telangana Secunderabad India

ISBN: (纸本)9798350304480

Companies of all sizes in today's linked digital world are susceptible to cyber dangers. In this study, we provide a novel approach to cyber defence that integrates machine learning with cognitive defensive techniques to identify and prevent cyber attacks in their tracks. We built three ML models that use cognitive defensive strategies and other cutting-edge security measures like encryption and intrusion detection. A 95% accuracy rate was reached by our models, which is far greater than where things stand right now models. Our work has the potential to have a huge effect since the models we've developed may one day help businesses take a more preventative stance against cyber threats. Our findings may potentially be used to fields outside than cyber security. Overall, our study shows that machine learning and cognitive defense are useful for foreseeing and stopping cyber threats, and points the way toward fruitful future study in this area. © 2023 IEEE.

关键词： Accuracy Advanced security features Cognitive defense Cyber security Cyber-attacks Encryption Intrusion detection Machine learning Prediction Prevention Proactive approach Threat landscape

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Research and Innovation In Next Generation Security and Privacy In Industry 5.0 Iot

Research and Innovation In Next Generation Security and Priv...

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International Conference on Contemporary Computing and Informatics (IC3I)

作者： Geeta S. Navale Ravikiran Madala Manjunath Managuli N. Jayalakshmi G. Kadiravan Ruchira Rawat Department of Computer Engineering Sinhgad Institute of Technology and Science Pune Maharashtra India Network and Data Center Engineer Ph.D Information Technology University of Cumberlands Durham North Carolina United States Department of Electronics and Communication Engineering KLS Gogte Institute of Technology Belegavi Karnataka India Master of Computer Applications PSNA College of Engineering and Technology Dindigul Tamilnadu India Department of Computer Science and Information Technology KL Deemed to be University Andhra Pradsh India Department of Computer Science and Engineering Graphic Era Deemed to be University Dehradun Uttrakhand India

The objective of the newest manufacturing paradigm, known as “Industry 5.0,” is to combine human intelligence with cutting-edge technology like the Internet of Things (IoT), artificial intelligence (AI), and robots to develop production systems that are incredibly effective and adaptable. But as we rely more on these technologies, we face additional privacy and security issues that might affect how dependable and trustworthy these systems are. In this report, we examine the most recent advancements in security and privacy for Industry 5.0 IoT and pinpoint the newest trends, obstacles, and possibilities. We also cover how these changes may affect manufacturing in the future and provide advice to scholars, practitioners, and policymakers.

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Automated AI Research On Cyber Attack Prediction And Security design

Automated AI Research On Cyber Attack Prediction And Securit...

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International Conference on Contemporary Computing and Informatics (IC3I)

作者： Ravikiran Madala N. Vijayakumar Nandini N Shanti Verma Samidha devendra Chandvekar devesh Pratap Singh Network and Data Center Engineer Ph.D Information Technology University of Cumberlands Durham North Carolina United States Department of Computer Science and Technology Karpagam College of Engineering Coimbatore India Department of Computer Science and Engineering Dr. Ambedkar Institute of Technology Bengaluru Karnataka India Department of Computer Application L J University Ahmedabad Gujarat India Department of Information Technology Changu Kana Thakur Arts Commerce and Science College New Panvel (Autonomous) New Panvel Maharashtra India Department of Computer Science and Engineering Graphic Era Deemed to be University Dehradun Uttrakhand India

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Cognitive defense Cyber Attack Prediction and Security design in Machine Learning Model

Cognitive Defense Cyber Attack Prediction and Security Desig...

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International Conference on Contemporary Computing and Informatics (IC3I)

作者： P.T. devadarshini B Chandrashekar Sumit Pundir Mohit Tiwari Ravikiran Madala E. Indhuma Department of Artificial Intelligence and Data Science Easwari Engineering College Chennai TamilNadu India Department Of Computer Science and Engineering St. Martin's Engineering College Kompalli Secunderabad Telangana Department of Computer Science and Engineering Graphic Era Deemed to be University Dehradun Uttrakhand India Department of Computer Science and Engineering Bharati Vidyapeeth's College of Engineering Delhi Network and Data Center Engineer Ph.D Information Technology University of Cumberlands Durham North Carolina US Department of Computer Science and Engineering St.Martln's Engineering College Secunderabad Telangana India

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HYBRId SATELLITE ANd TERRESTRIAL networkS

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INTERNATIONAL JOURNAL OF SATELLITE COMMUNICATIONS 1994年第3期12卷 313-327页

作者： CHITRE, dM SHYY, dJ EphREMIdES, A GUPTA, S COMSAT Laboratories 22300 Comsat Drive Clarksburg MD 20871–9475 USA. Received his B.Sc. from the University of Bombay India an M.A. in mathematics from the University of Cambridge U.K. and a Ph.D. in physics from the University of Maryland. He is currently an Associate Executive Director of the Network Technology Division at COMSAT Laboratories. He has been involved in research and development activities in ISDN VSAT networks data communications and network systems and architectures. Prior to his current positions Dr. Chitre was a Principal Scientist in the Network Technology Division at COMSAT Laboratories. Dr. Chitre joined COMSAT Laboratories in 1980. He has made major contributions to the analysis and architecture of data communication ISDN and BISDN via satellite. Dr. Chitre directs and participates in the international and national standards activities in ISDN BISDN and data communication as they apply to satellite communication. He was Chairman of the Working Group on Protocols and Network Timing Function of the CCIR/CCITT Joint Ad Hoc Group on ISDN/Satellite Matters during 1990–1992. Currently he is the Chairman of the Working Group on New Technologies in the ITU Intersector Coordinating Group (ICG) on Satellite Matters. Dr. Chitre was a programme manager during 1990 and 1991 on a contract from INTELSAT on systems studies on satellite communications systems architectures for ISDN and broadband ISDN systems. Currently he is the technical manager of the DoD Contract on ATM via satellite demonstration and the programme manager for the INTELSAT contract on analysis and top-level specification of INTELSAT ISDN subnetworks and SDH compatible transport network. Received the B.S. degree in electrical engineering from national Chiao-Tung University Hsin-Chu Taiwan in 1983 and the M.S. and Ph.D. degrees in electrical engineering from Georgia Institute of Technology Atlanta GA in 1986 and 1990 respectively. From June 1987 to October 1987 he worked for the Department of Neurology Emory Univers

The role of satellite communications in networks that provide new services, such as frame relay and multimedia, is investigated. Both passive and active (on-board switching/processing) satellite systems are considered. Novel techniques are developed for each system to demonstrate, via detailed analysis and simulation, how the communications bandwidth agility of multipoint/broadcast satellite channels, and the on-board switching/processing, makes it feasible to provide these new services via hybrid satellite and terrestrial networks in a resource-efficient manner.

关键词： HYBRId networkS ON-BOARd PROCESSING FRAME RELAY

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