The International Cyber Security and Machine Learning Academic and Professional Program (ICSML) was regarding cybersecurity and how a machine learning solution can be applied in solving the various attack vectors that are being currently used by the attackers to infiltrate into the systems. The program involved several theoretical lectures and practical sessions on the current research and problems in the field of cybersecurity.
Various aspects related to the different attack vectors such as DDOS, Ransomware, USB ware, mobile malware, phishing, spear phishing were learned in great depth. Moreover, machine learning included the use of continuous mobile authentication, also the classification of malicious and benign files based on the feature of extracting from XML files. The whole theory is part of Structural Feature Extraction Methodology.
Final Course Grade: 92%
Abstract - With the advent of the IOT environment, we now even have Smart Toilets to analyze human excreta. These devices can be used to measure and monitor the human excreta and provide calculative actions to not only the consumers but also send the data to the hospitals for better efficiency in providing healthcare facilities to the various patients. If such a system is compromised using various malicious methodologies, several damaging effects can occur.
In this paper what we’re trying to cover is the potential ways in which Smart Toilets can be attacked and how these Cyber Attacks can have adverse effects on our lives directly and indirectly. We would also be providing solutions based on Machine Learning methods to tackle and avoid such Cyber Attacks to build a system which is very secure, to protect not only the Private Data of the consumer but also prevent the Smart Toilet systems to act as a hub for further penetration into the house or organization.
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