Advanced Smart Computing Technologies in Cybersecurity and Forensics
portes grátis
Advanced Smart Computing Technologies in Cybersecurity and Forensics
Bhardwaj, Akashdeep; Tayal, Shubham; Kumar, Manoj; Kaushik, Keshav
Taylor & Francis Ltd
12/2021
242
Dura
Inglês
9780367686505
15 a 20 dias
489
Descrição não disponível.
1. Detection of Cross-Site Scripting and Phishing Website Vulnerabilities Using Machine Learning.
2. A Review: Security and Privacy Defensive Techniques for Cyber Security Using Deep Neural Networks (DNNs).
3. DNA-Based Cryptosystem for Connected Objects and IoT Security.
4. A Role of Digital Evidence: Mobile Forensics Data.
5. Analysis of Kernel Vulnerabilities Using Machine Learning.
6. Cyber Threat Exploitation and Growth during COVID-19 Times.
7. An Overview of the Cybersecurity in Smart Cities in the Modern Digital Age.
8. The Fundamentals and Potential for Cyber Security of Machine Learning in the Modern World.
9. Qualitative and Quantitative Evaluation of Encryption Algorithms.
10. Analysis and Investigation of Advanced Malware Forensics.
11. Network Intrusion Detection System Using Naive Bayes Classification Technique for Anomaly Detection.
12. Data Security Analysis in Mobile Cloud Computing for Cyber Security.
13. A Comprehensive Review of Investigations of Suspects of Cyber Crimes.
14. Fault Analysis Techniques in Lightweight Ciphers for IoT Devices.
2. A Review: Security and Privacy Defensive Techniques for Cyber Security Using Deep Neural Networks (DNNs).
3. DNA-Based Cryptosystem for Connected Objects and IoT Security.
4. A Role of Digital Evidence: Mobile Forensics Data.
5. Analysis of Kernel Vulnerabilities Using Machine Learning.
6. Cyber Threat Exploitation and Growth during COVID-19 Times.
7. An Overview of the Cybersecurity in Smart Cities in the Modern Digital Age.
8. The Fundamentals and Potential for Cyber Security of Machine Learning in the Modern World.
9. Qualitative and Quantitative Evaluation of Encryption Algorithms.
10. Analysis and Investigation of Advanced Malware Forensics.
11. Network Intrusion Detection System Using Naive Bayes Classification Technique for Anomaly Detection.
12. Data Security Analysis in Mobile Cloud Computing for Cyber Security.
13. A Comprehensive Review of Investigations of Suspects of Cyber Crimes.
14. Fault Analysis Techniques in Lightweight Ciphers for IoT Devices.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
Mobile Cloud Computing;IoT Security;DNN Model;IoT Device;NSL.;Sensitive Information;Sbox;NIDS;Network Intrusion Detection System;IoT System;Deep Belief Networks;Block Cipher;Random Forest;Phishing Websites;Execution Time;Dl Algorithm;IoT Technology;IoT Application;Bayes Classifier;Cps;Cloud Computing;Elm Classifier;Smart City;Cyber Crimes;Phishing Detection
1. Detection of Cross-Site Scripting and Phishing Website Vulnerabilities Using Machine Learning.
2. A Review: Security and Privacy Defensive Techniques for Cyber Security Using Deep Neural Networks (DNNs).
3. DNA-Based Cryptosystem for Connected Objects and IoT Security.
4. A Role of Digital Evidence: Mobile Forensics Data.
5. Analysis of Kernel Vulnerabilities Using Machine Learning.
6. Cyber Threat Exploitation and Growth during COVID-19 Times.
7. An Overview of the Cybersecurity in Smart Cities in the Modern Digital Age.
8. The Fundamentals and Potential for Cyber Security of Machine Learning in the Modern World.
9. Qualitative and Quantitative Evaluation of Encryption Algorithms.
10. Analysis and Investigation of Advanced Malware Forensics.
11. Network Intrusion Detection System Using Naive Bayes Classification Technique for Anomaly Detection.
12. Data Security Analysis in Mobile Cloud Computing for Cyber Security.
13. A Comprehensive Review of Investigations of Suspects of Cyber Crimes.
14. Fault Analysis Techniques in Lightweight Ciphers for IoT Devices.
2. A Review: Security and Privacy Defensive Techniques for Cyber Security Using Deep Neural Networks (DNNs).
3. DNA-Based Cryptosystem for Connected Objects and IoT Security.
4. A Role of Digital Evidence: Mobile Forensics Data.
5. Analysis of Kernel Vulnerabilities Using Machine Learning.
6. Cyber Threat Exploitation and Growth during COVID-19 Times.
7. An Overview of the Cybersecurity in Smart Cities in the Modern Digital Age.
8. The Fundamentals and Potential for Cyber Security of Machine Learning in the Modern World.
9. Qualitative and Quantitative Evaluation of Encryption Algorithms.
10. Analysis and Investigation of Advanced Malware Forensics.
11. Network Intrusion Detection System Using Naive Bayes Classification Technique for Anomaly Detection.
12. Data Security Analysis in Mobile Cloud Computing for Cyber Security.
13. A Comprehensive Review of Investigations of Suspects of Cyber Crimes.
14. Fault Analysis Techniques in Lightweight Ciphers for IoT Devices.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
Mobile Cloud Computing;IoT Security;DNN Model;IoT Device;NSL.;Sensitive Information;Sbox;NIDS;Network Intrusion Detection System;IoT System;Deep Belief Networks;Block Cipher;Random Forest;Phishing Websites;Execution Time;Dl Algorithm;IoT Technology;IoT Application;Bayes Classifier;Cps;Cloud Computing;Elm Classifier;Smart City;Cyber Crimes;Phishing Detection
