Cyber security threats are a mere mistake away for most travelers and techy adventurer seekers. Those business trips you take can be a risk for your professional and personal life because unscrupulous individuals can hack your sensitive data on your mobile devices like laptops, smartphones, and tablets. Below are eight cyber security tips worth considering for your next travels, whether for business or holiday. 1) Lock Devices Down Most laptops, smartphones, and tablets are equipped with security settings like fingerprint ID, PIN, face recognition, and more. It is best to use these settings, ensuring they are active on all your portable devices when traveling. Also, change your passwords and security codes regularly. The will be the first line of defense that must be breached to gain access if your devices are stolen, or you forget or misplace them. 2) Avoid Using Public Wi-Fi Cyber security laws and regulations differ from country to country, even though they also share some commonalities. That means, much of the security protocols used in the U.S. will not be the same are those found in other countries. Public Wi-Fi is often free, and such access can be appealing when traveling for business or leisure. However, free Wi-Fi access leaves you vulnerable to security threats. Therefore, inquire if the internet provider uses an . That means it is best to exercise some caution when using internet access at free Wi-Fi hotspots, hotels, and cafés. Also, experts advise against accessing your accounts and sensitive data when traveling and using free Wi-Fi access. 3) Disable Auto-Connect Your smartphone, tablet, or laptop might have an auto-connect setting that...
Four More Questions You Might Get in a Data Science Interview Part 2 of a miniseries crafted by somebody with experience as a data science interviewer Hello again friends! Welcome back with the continuation of our series on interview questions you might get in a data science interview. In case you missed the first post, you can check it out at this link. I’m going to keep this introduction short and sweet since I give a better, more thorough explanation in the original post. Let me provide a very quick recap on how these posts are structured. Across all four questions, you will see two subsections: Also one last reminder: the questions I’ve crafted across both posts run the full gamut of data science skills. Depending on the specific role you apply for, you may or may not encounter questions similar to these, but I still wanted to provide a broad range of types of questions to cover that “full stack” of data science skills. Alrighty, I promised a short and sweet introduction, so let’s jump into the questions! 1. Across various cloud platforms (including AWS SageMaker), it is possible to deploy a model directly from a Jupyter notebook. Can you explain why this is not a preferable pattern, and what might you consider doing instead? Motivation: This is one of those questions that has less to do with “pure” data science and more about software engineering in general, and it’s also a question where the answer is less important than how the question is answered. In short, the reason this is not a preferable plan is because it...
“Last year will go down in history as the year of security vulnerabilities, wherein in the race against time and criminals, we had to learn some painful lessons. However, all experiences are useful and must be shared,” says Gert Auväärt, Director of the Cyber Security Branch of the Information System Authority (RIA) in the latest yearbook published by the Information System Authority titled Cyber Security in Estonia 2022. The (RIA) is the government office that coordinates the development, implementation, and administration of the state’s IT infrastructures, ensures the interoperability of the information system across the public and private sectors, manages the nation’s cyber security realm and organises related activities. Cyber Security in Estonia 2022 focuses on Estonia and international cyberspace’s cyber failures, wins, lessons, and 2022 to-comes. The year of vulnerabilities While the Information System Authority believes that 2022 would be a grand sequel to 2021 in terms of cyber vulnerabilities, 2021 earned itself the title of ‘the year of major security vulnerabilities.’ Aside from the year coming to an end with the global ‘IT earthquake’ – the Log4j zero-day vulnerability, which’s dreadful impact remains to be seen, Estonia also had its fair share of in-state cyber warfare. Leading the pack of major incidents that shook Estonia was the RIA’s security vulnerability that gave an Estonia-based attacker the opportunity to from the identity documents’ database. The incident was quickly detected, and the security vulnerability was patched. Thankfully, with the swift cooperation between the police, CERT-EE, and the Prosecutor’s Office, the criminal was caught within a few days, and the downloaded data was confiscated. This is one of the 2,237...
Monitoring Production ML Model Inputs Practically and Efficiently in the Absence of Ground Truth Data Photo by Carlos Muza on Unsplash In real life ML monitoring applications, we want to detect whether or not a ML model is performing well or is breaking. Not picking up on poor model performance can translate into poor or even biased predictions that can lead to lost revenue and even PR fires that we see year over year from even the large tech companies, from facial recognition systems that fail to pick up on certain minorities to hate speech in autocomplete for search engines. In this article, we’ll go over a brief overview of how data drift thresholding helps capture poor model performance, and the majority of the post will focus on two versions of implementing automated data drift detection in production level ML monitoring systems. Overview Why do we need data drift? The standard approach to monitoring models is based on performance metrics, i.e. accuracy/precision/recall/f-score, over some time period or from batch to batch. In order to produce these metrics, we need both predictions and ground truth labels for the datapoints, e.g. a credit risk model predicts that a person will pay their loan on time in 1 year and thus should be approved for a credit card, and we know whether or not that person paid their loan on time in 1 year. Already, we have an issue because we do not know ground truth until 1 year later. In most production applications, there is a lag between prediction time and ground truth collection time, which significantly handicaps the ability to remediate model issues quickly. Leveraging...
Huawei Technologies Ghana has been commended for organizing Cyber Security Training for over 40,000 women as part of their Huawei Seeds for the Future Women in Tech program for 2021. The ICT giant received the commendation from the Deputy Minister of Communications and Digitalization, Hon. Ama Pomaa Boateng, during her Keynote Address of the African Union (AU) – Global Forum on Cyber Expertise (GFCE) Africa Cyber Experts (ACE) Community Kick-Off Meeting which is on the theme, Setting the Scene for Cybersecurity Status in Africa. The event is happening in Accra, Ghana from March 16 to 18, 2022. In her speech, the Honorable Minister praised Huawei for their outstanding contribution to increasing the Cyber Security awareness of Ghanaian Women. She said, “We are grateful to Huawei and MTN for partnering with the Ministry to train over 50,000 women in Cyber Security last year.” She added that she is confident that the efforts of private sector partners and the program of activities and sessions outlined for the ongoing AU-GFCE are relevant for Ghana’s Cyber Security mission and goals. Stating that such initiatives aside having the potential for creating jobs for men and women in Cyber Security, will also go a long way to ensure that the Ministry’s goals of ensuring that Cyber Space if safe for children, the public, business and government is achieved. Last year Huawei cooperated with the Ministry of Communications through the Ministry’s ‘Girls in ICT’ program to offer Digital skill training to thousands of women from the Junior High School level through to Tertiary and working professionals and traders to build their digital literacy and capability. Other...
Introduction to Spear Phishing Attack In the cyber community industry nowadays, with the term “Spear Phishing”, we define a targeted attempt to steal private information such as user account credentials or financial information from a specific victim or organization. In order to succeed in this malicious activity, personal details are acquired on the victim such as friendship, hometowns, employers, locations they have frequently visited and what they have recently bought online. The hackers pretend to be a trustworthy friend or entity to acquire personal information, usually through email or other online messaging platforms. The history of “Spear Phishing” attacks began as a Nigerian prince scam in the mid 1990’s, nowadays they have transformed into well researched and targeted hacker campaigns that are both highly effective and incredibly difficult to mitigate. While spear phishing attacks may target “smaller size victims”, like a mid-range company employee or a random target chosen on social media platforms. Whaling phishing is looking after the “big size victims.” These attacks often target C-Level executives like CEOs or CFOs to attempt to gather larger payments and more private data. Mitigation from Spear Phishing Attacks In the cyber community nowadays there are many theories on how to prevent a spear phishing attack. Most of the commonly used are presented below: Spear Phishing vs Phishing Nowadays, “Spear Phishing” can easily be confused with simple “Phishing” because they are both cyber attacks on users that aim to acquire private information. Although, with the term “Phishing”, it is mainly used for any kind of attempt to trick victims into sharing sensitive information such as passwords, usernames, and credit card...
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