By now, unfortunately COVID-19, better known as the Corona virus, has become a household name. The sudden global outbreak of COVID-19 has brought tremendous challenges to our day-to-day lives. In order to contain and mitigate the threats of this virus, governments, public and private organisations have taken several measures. These measures include among others, imposing social distancing, (where possible) mandatory teleworking, discontinuing nonessential physical meetings and promoting hand hygiene protocol.

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Penetration testing will never be an exact science where a complete list of all possible issues that should be tested can be defined. Indeed penetration is only an appropriate technique to test the security of web applications under certain circumstances. For information about what these circumstances are, and to learn how to build a testing framework and which testing techniques you should consider, we recommend reading the OWASP Testing Framework Part One (http://www.owasp.org) .

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Microsoft Defender Advanced Threat Protection (ATP) is a Microsoft security product that is designed to help enterprise-class organizations detect and respond to security threats. ATP is a preventative and post-detection, investigative response feature to Windows Defender. ATP’s features are standard in many high-end anti-malware packages.

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Establishing its national presence in 1983, Marsh Indonesia is part of Marsh & McLennan Companies, a global pro
fessional services firm specialising in insurance brokering and risk management solutions. The company distinguishes itself by its commitment to an always client-centric mode of operation and a breadth of expertise that focuses on the client’s specific industry for a higher quality of advice and service.

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Deep learning is a special machine learning approach that facilitates the extraction of features of a high level of abstraction from low-level data. Deep learning has proven successful in computer vision, speech recognition, natural language processing and other tasks. It works best when you want the machine to infer high-level meaning from low-level data. For image recognition challenges, like ImageNet, deep learning-based approaches already surpass humans.

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