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| 008 | 211129s2019 xx o ||||0 eng d | ||
| 020 |
_a9783030152109 _q(electronic bk.) |
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| 020 | _z9783030152093 | ||
| 035 | _a(MiAaPQ)EBC5732710 | ||
| 035 | _a(Au-PeEL)EBL5732710 | ||
| 035 | _a(CaPaEBR)ebr11662735 | ||
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_aHV6773.15 .N6 _bI575 2019 |
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| 082 | 0 | _a005.8 | |
| 100 | 1 |
_aIorliam, Aamo. _eauthor |
|
| 245 | 1 | 0 |
_aCybersecurity in Nigeria : _bA Case Study of Surveillance and Prevention of Digital Crime / _cAamo Iorliam. |
| 264 | 1 |
_aCham : _bSpringer International Publishing AG, _c2019. |
|
| 264 | 4 | _c©2019. | |
| 300 | _a1 online resource (68 pages) | ||
| 336 |
_atext _btxt _2rdacontent |
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| 337 |
_acomputer _bc _2rdamedia |
||
| 338 |
_aonline resource _bcr _2rdacarrier |
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| 490 | 1 | _aSpringerBriefs in Cybersecurity Ser. | |
| 505 | 0 | _aIntro -- Foreword -- Preface -- Acknowledgements -- Contents -- 1 Introduction -- 1.1 Main Contributions -- 1.2 Document Structure -- 2 Natural Laws (Benford's Law and Zipf's Law) for Network Traffic Analysis -- 2.1 Contribution -- 2.2 Benford's Law -- 2.3 Zipf's Law -- 2.4 Network Traffic Analysis and IDS -- 2.4.1 Flow-Based IDS -- 2.5 Network Flows and TCP Flows -- 2.6 Application to Network Traffic Analysis -- 2.6.1 Method Description -- 2.6.2 The Metrics -- 2.6.3 Analysis of Different Flow Ordering Options -- 2.7 Experimental Setup and Results -- 2.7.1 Datasets Used for Our Experiments -- 2.7.2 Flow Size or Flow Size Difference -- 2.7.3 How to Determine Flow Window Size -- 2.7.4 TCP Flow Ordering -- 2.7.5 More Results on Different Datasets -- 2.7.6 Zipf's Law for Network Traffic Analysis -- 2.7.7 Zipf's Law for Malicious, Non-malicious, Mixture of Malicious and Non-malicious Network Traffic -- 2.7.8 Comparative Analysis of Zipf's Law and Benford's Law with Implications -- 2.8 Conclusion -- References -- 3 Combination of Natural Laws (Benford's Law and Zipf's Law) for Fake News Detection -- 3.1 Combination of Benford's Law and Zipf's Law for Fake News Detection -- 3.2 Results and Discussions -- 3.3 Conclusion -- References -- 4 Cybersecurity and Mobile Device Forensic -- 4.1 Nigeria and Internet Fraud -- 4.2 Reasons for Increase in Cyber Crimes in Nigeria -- 4.3 Types of Cyber Crimes in Nigeria -- 4.4 Link Between Mobile Device Forensics and Cybersecurity -- 4.5 Cybersecurity Laws and Punishment in Nigeria -- 4.6 Conclusion -- References -- 5 Proposed Digital Surveillance Software -- 5.1 Introduction -- 5.2 System Analysis and Design -- 5.3 Product Features and How It Works -- 5.4 The Solution (A-BOT) -- 5.5 Advantages of the Proposed System -- 5.6 Conclusion -- References. | |
| 520 | _aThis book reviews the use of digital surveillance for detecting, investigating and interpreting fraud associated with critical cyberinfrastructures in Nigeria, as it is well known that the country's cyberspace and cyberinfrastructures are very porous, leaving too much room for cyber-attackers to freely operate. In 2017, there were 3,500 successful cyber-attacks on Nigerian cyberspace, which led to the country losing an estimated 450 million dollars. These cybercrimes are hampering Nigeria's digital economy, and also help to explain why many Nigerians remain skeptical about Internet marketing and online transactions. If sensitive conversations using digital devices are not well monitored, Nigeria will be vulnerable to cyber-warfare, and its digital economy, military intelligence, and related sensitive industries will also suffer. The Nigerian Army Cyber Warfare Command was established in 2018 in order to combat terrorism, banditry, and other attacks by criminal groups in Nigeria. However, there remains an urgent need to produce digital surveillance software to help law enforcement agencies in Nigeria to detect and prevent these digitally facilitated crimes. The monitoring of Nigeria's cyberspace and cyberinfrastructure has become imperative, given that the rate of criminal activities using technology has increased tremendously. In this regard, digital surveillance includes both passive forensic investigations (where an attack has already occurred) and active forensic investigations (real-time investigations that track attackers). In addition to reviewing the latest mobile device forensics, this book covers natural laws (Benford's Law and Zipf's Law) for network traffic analysis, mobile forensic tools, and digital surveillance software (e.g., A-BOT). It offers valuable insights into how digital surveillance software can be used to detect and prevent digitally facilitated crimes in Nigeria, and highlights the benefits of adopting digital surveillance software in Nigeria and other countries facing the same issues. | ||
| 588 | _aDescription based on publisher supplied metadata and other sources. | ||
| 590 | _aElectronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2021. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries. | ||
| 650 | 0 |
_aComputer security. _zNigeria |
|
| 650 | 0 |
_aComputer crimes _979072 _xPrevention _zNigeria |
|
| 650 | 0 |
_aComputer networks _979096 _xSecurity measures _zNigeria |
|
| 655 | 4 | _aElectronic books. | |
| 776 | 0 | 8 |
_iPrint version: _aIorliam, Aamo _tCybersecurity in Nigeria _dCham : Springer International Publishing AG,c2019 _z9783030152093 |
| 797 | 2 | _aProQuest (Firm) | |
| 830 | 0 | _aSpringerBriefs in Cybersecurity Ser. | |
| 856 |
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| 500 | _aALA COVID Relief Fund | ||