Lumify Learn’s Post

**We have Data and Security Talents!** In today's rapidly evolving digital landscape, the demand for specialized skill sets has never been higher. Businesses are constantly seeking top-tier talent to navigate the complexities of data analysis, data science, and cybersecurity. At CGP/BATech, we understand these needs and are proud to offer unparalleled expertise in these critical areas. 🚀 **Data Analysts and Data Scientists**: The backbone of informed decision-making, our data professionals excel in transforming raw data into actionable insights. From predictive modeling to advanced analytics, our team leverages the latest tools and methodologies to drive your business forward. 🛡️ **Security Consultants**: In an era where cyber threats are ever-present, safeguarding your digital assets is paramount. Our security consultants are seasoned experts in identifying vulnerabilities, implementing robust security protocols, and ensuring compliance with industry standards. Partner with us and gain access to a pool of highly skilled professionals ready to tackle your toughest challenges. Whether you're looking to enhance your data capabilities or strengthen your security posture, we have the talent you need to succeed. Let's connect and explore how we can help your business thrive in a competitive market. Contact us today to learn more about our exceptional IT talent and contractor solutions. #DataScience #CyberSecurity #TechTalent #BusinessGrowth

Data security is becoming increasingly important in the modern age, and the people behind it are even more so. If you’re interested in a career in cybersecurity, one role to consider is intelligence analyst, a role that can have a far-reaching impact on business, legal, and governmental sectors. Learn more in our latest blog: https://bit.ly/4dKmkI3. #UAGC #CareerPaths #CyberSecurity #IntelligenceAnalyst

In 2025, cybersecurity threats are expected to evolve significantly due to advancements in technology and shifting tactics by threat actors. Key trends to watch include: AI-Driven Attacks: Threat actors will increasingly leverage artificial intelligence (AI) for tasks like crafting highly convincing phishing campaigns, creating adaptive malware, and automating reconnaissance. AI's ability to analyze vulnerabilities and adjust in real-time could make attacks more sophisticated and harder to defend against. Exploitation of Large Language Models (LLMs): Misconfigured AI tools and large language models may become prime targets. Attackers could use compromised LLMs to exfiltrate data or execute insider threats, while APIs tied to these tools might be exploited for financial and operational damage. Ransomware and Hacktivism: Ransomware-as-a-service (RaaS) will continue growing, with some hacktivist groups adopting ransomware to fund operations. This shift could combine financial motives with ideological goals, making these groups even more impactful. Critical Infrastructure as a Target: Cyberattacks on physical infrastructure such as power grids, water supplies, and transportation systems are anticipated to escalate, with small utilities particularly vulnerable. AI-driven strategies may increase the scale and impact of these disruptions. Social Engineering and Deepfakes: Enhanced social engineering techniques, including the use of deepfake audio and video, are likely to grow. Threat actors may exploit these tools for more effective spear-phishing and identity fraud. Data Sovereignty and Compliance Challenges: As more countries adopt strict data sovereignty laws, companies operating internationally will face complex compliance requirements. This could expose businesses to fines or restrictions if they fail to meet new standards. Organizations should prioritize AI governance, employee training, and robust incident response planning to counter these emerging threats. Enhanced collaboration between governments, businesses, and cybersecurity providers will also be critical for mitigating risks in this rapidly changing landscape. If you are a mid-sized corporation and need CISO level leadership without the CISO cost. Please reach out. #CISO #cybersecurity #opentowork #NIST #SAP #vCISO  #Fortitude

Emerging Risk Data integrity risk is emerging as a critical concern in today's tech-driven world. Organizations must proactively assess and mitigate these risks to safeguard their data assets and maintain trust with stakeholders. Here are a few key areas where data integrity risks are on the rise: 1️⃣ Cybersecurity Threats: With the proliferation of interconnected systems and cloud-based storage, cyber threats have become more sophisticated, posing significant risks to data integrity. From ransomware attacks to phishing schemes, organizations must fortify their defenses to prevent unauthorized access and data tampering. 2️⃣ Algorithmic Bias: As AI and machine learning algorithms play an increasingly prominent role in decision-making processes, there's a growing concern about algorithmic bias. Biased algorithms can skew data analysis results, leading to erroneous conclusions and potentially damaging outcomes. 3️⃣ Data Quality Issues: The influx of vast amounts of data from diverse sources can lead to data quality issues such as inaccuracies, incompleteness, and inconsistency. Poor data quality not only undermines the reliability of insights but also erodes trust in organizational decision-making. 4️⃣ Compliance Challenges: Regulatory requirements such as GDPR and CCPA impose strict obligations on organizations to ensure the accuracy, confidentiality, and availability of personal data. Failure to comply with these regulations can result in severe penalties and reputational damage. By proactively managing data integrity risks, organizations can ensure they're making sound decisions based on reliable information. #dataintegrity #datarisk #datagovernance #technology #informationsecurity

¡¡¡CYBER ATTACK STATISTICS ALARM!!! Cyberattacks are becoming more frequent and sophisticated, posing significant threats to companies, governments and individuals.Cyberattacks, ranging from data breaches to hostile account takeovers, are estimated to cost the global economy $8 trillion in 2023. This year, that figure is expected to rise to $9.5 trillion, research firm Cybersecurity Ventures reported.The rise of AI technology is likely to increase this number, with projections suggesting 11% growth to $10.5 trillion by 2025. This year, that figure is expected to rise to $9.5 trillion, research firm Cybersecurity Ventures reported.The rise of AI technology is likely to increase this number, with projections suggesting 11% growth to $10.5 trillion by 2025. A survey conducted by Statista with industry leaders revealed that cyberattacks are one of the biggest threats to a company, followed by business disruptions and macroeconomic events. According to the survey conducted between 2018 and 2023, 34% of respondents ranked cyber incidents as their top concern

The latest IBM Data Breach Report reveals some sobering results. The cost of a data breach is up, the frequency of data breaches is up, severe shortages in experienced cyber professionals, and the threat of AI. Have you read the report? What are your key takeaways?

🛡️ 𝗗𝗲𝘀𝗶𝗴𝗻𝗶𝗻𝗴 𝗕𝗲𝗵𝗮𝘃𝗶𝗼𝗿𝗮𝗹 𝗔𝗻𝗮𝗹𝘆𝘀𝗶𝘀 𝗧𝗼𝗼𝗹𝘀: 𝗥𝗲𝗮𝗹-𝗧𝗶𝗺𝗲 𝗔𝗻𝗼𝗺𝗮𝗹𝘆 𝗗𝗲𝘁𝗲𝗰𝘁𝗶𝗼𝗻 𝗶𝗻 𝗖𝘆𝗯𝗲𝗿𝘀𝗲𝗰𝘂𝗿𝗶𝘁𝘆 🛡️ 𝗕𝗲𝗵𝗮𝘃𝗶𝗼𝗿𝗮𝗹 𝗮𝗻𝗮𝗹𝘆𝘀𝗶𝘀 𝘁𝗼𝗼𝗹𝘀 are essential for detecting sophisticated fraud that evades traditional security systems. These tools use 𝗺𝗮𝗰𝗵𝗶𝗻𝗲 𝗹𝗲𝗮𝗿𝗻𝗶𝗻𝗴 to analyze user behaviors, spotting anomalies that indicate potential threats.  🔍 𝗞𝗲𝘆 𝗗𝗮𝘁𝗮 𝗣𝗼𝗶𝗻𝘁𝘀  Behavioral analysis tools collect and analyze diverse data: - 𝗨𝘀𝗲𝗿 𝗜𝗻𝘁𝗲𝗿𝗮𝗰𝘁𝗶𝗼𝗻𝘀: Tracks mouse movements, typing speed, and clicks. Unusual patterns, like uniform movements or rapid typing, may signal automated activity. - 𝗧𝗿𝗮𝗻𝘀𝗮𝗰𝘁𝗶𝗼𝗻𝗮𝗹 𝗗𝗮𝘁𝗮: Detects anomalies like sudden large transactions or changes in purchasing behavior. - 𝗚𝗲𝗼𝗹𝗼𝗰𝗮𝘁𝗶𝗼𝗻 & 𝗡𝗲𝘁𝘄𝗼𝗿𝗸 𝗗𝗮𝘁𝗮: Flags suspicious logins from unexpected locations or device/network changes.  📊 𝗔𝗻𝗼𝗺𝗮𝗹𝘆 𝗗𝗲𝘁𝗲𝗰𝘁𝗶𝗼𝗻 & 𝗥𝗶𝘀𝗸 𝗦𝗰𝗼𝗿𝗶𝗻𝗴 Advanced algorithms compare real-time behaviors against normal baselines: - 𝗕𝗮𝘀𝗲𝗹𝗶𝗻𝗲 𝗣𝗿𝗼𝗳𝗶𝗹𝗲𝘀: Establish each user's typical activity, like login times and transaction types. - 𝗥𝗶𝘀𝗸 𝗦𝗰𝗼𝗿𝗶𝗻𝗴: Assign risk scores to deviations from normal behavior, triggering alerts for high-risk activities. ⚙️ 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 & 𝗔𝗱𝗮𝗽𝘁𝗮𝘁𝗶𝗼𝗻  Behavioral analysis tools continuously evolve: - 𝗦𝘂𝗽𝗲𝗿𝘃𝗶𝘀𝗲𝗱 & 𝗨𝗻𝘀𝘂𝗽𝗲𝗿𝘃𝗶𝘀𝗲𝗱 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴: Models adapt to new fraud tactics, detecting both known and emerging threats. - 𝗖𝗼𝗻𝘁𝗲𝘅𝘁𝘂𝗮𝗹 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴: Recognizes seasonal trends to reduce false positives. - 𝗙𝗲𝗲𝗱𝗯𝗮𝗰𝗸 𝗟𝗼𝗼𝗽𝘀: Refines detection accuracy based on user feedback and real incidents. 💡 𝗕𝗲𝗻𝗲𝗳𝗶𝘁𝘀: - 𝗘𝗮𝗿𝗹𝘆 𝗗𝗲𝘁𝗲𝗰𝘁𝗶𝗼𝗻: Identifies threats early, preventing major damage. - 𝗥𝗲𝗱𝘂𝗰𝗲𝗱 𝗙𝗮𝗹𝘀𝗲 𝗣𝗼𝘀𝗶𝘁𝗶𝘃𝗲𝘀: Focuses on precise detection, minimizing disruption to legitimate users. - 𝗔𝗱𝗮𝗽𝘁𝗮𝗯𝗶𝗹𝗶𝘁𝘆: Learns and adapts to new fraud patterns. Behavioral analysis tools provide proactive, adaptable defenses crucial for modern cybersecurity. #CyberSecurity #BehaviorAnalysis #AnomalyDetection #MachineLearning #FraudPrevention #TechInnovation #AIInSecurity #SystemDesign #DigitalSecurity #ResearchIdeas #ProjectIdeas #CyberResearch #InnovationInTech

In 2024, the average cost of a healthcare data breach was $9.77 million, according to IBM's "Cost of a Data Breach Report." Healthcare has been the most expensive industry for data breaches for 14 consecutive years. The report highlights a growing cybersecurity skills shortage, with over half of organisations reporting staffing gaps. Despite some companies using generative AI tools to boost security, the skills gap remains a challenge. The most common data affected by breaches was: 🆔 customers' personally identifiable information. The top attack methods were: 🔝 phishing and compromised credentials. IBM noted that the use of AI and automation significantly lowered breach costs, with organisations employing these technologies saving an average of $1.88 million compared to those that did not. IBM recommended that companies focus on 1️⃣ data inventories, 2️⃣ security-first AI approaches, and 3️⃣ improving cybersecurity response training to mitigate breach costs. What strategies have been adopted by your organisation to address the data breach risks? #clinicalresearch #healthcare #databreach

One key lesson I’ve learned as an entry-level data scientist and analyst is that you can never be too cautious when it comes to security. Protecting your organization’s or business's assets (especially data) is crucial, as it is a high-risk asset. Neglecting data security can lead to significant financial losses and other serious consequences, impacting both you and your organization. While I understand that safeguarding an organization’s assets is a shared responsibility among all employees, data professionals play a very critical role since data has become the backbone of most businesses. And this is why I believe every data professional should pursue at least a basic course or program in Data security or cybersecurity. As the world rapidly evolves and becomes more reliant on data and AI technologies, threat actors are also becoming more sophisticated. Understanding the fundamentals of data privacy and security will help data professionals better protect their organization's data and stay ahead in this ever-changing digital landscape. #Security #Cybersecurity #DataScience #DataAnalyst #DataProtection #DataPrivacy #CareerGrowth #AI #gwg #RLabsNigeria

⬛ 𝗗𝗮𝗿𝗸 𝗗𝗮𝘁𝗮 📂: an overlooked goldmine or a ticking time bomb? Gartner describes dark data as untapped information collected and stored during regular business operations, often ignored for uses like analytics or business relationships. A global survey by Splunk shows that for 60% of over 1,300 IT and business decision-makers, consider that half or more of their organization's data is Dark Data. But a concerning one-third believe this could be as high as 75% or more 👀. Hoarding dark data has far-reaching implications beyond the obvious. These include: 1. 𝗦𝘁𝗼𝗿𝗮𝗴𝗲 𝗖𝗼𝘀𝘁𝘀: Data, used or not, requires storage infrastructure. More data means higher costs 📊. 2. 𝗟𝗶𝗮𝗯𝗶𝗹𝗶𝘁𝘆 𝗖𝗼𝘀𝘁𝘀: Global privacy laws apply to all data, even the unused ones 🌐. 3. 𝗢𝗽𝗽𝗼𝗿𝘁𝘂𝗻𝗶𝘁𝘆 𝗖𝗼𝘀𝘁𝘀: Ignoring this data can mean missed opportunities. It's worth analyzing its potential before discarding it 🚀. 4. 𝗜𝗻𝗲𝗳𝗳𝗶𝗰𝗶𝗲𝗻𝗰𝘆 𝗖𝗼𝘀𝘁𝘀: Large volumes of data can slow down data retrieval and analysis, impacting productivity and increasing labor costs ⏳. 5. 𝗥𝗶𝘀𝗸 𝗖𝗼𝘀𝘁𝘀: Dark data can lead to cybersecurity threats, data breaches, compliance violations, and data loss, damaging a company's reputation and finances 💼. What is the size of your Dark Data? My advice? Check it out as soon as possible! #DarkData #DataManagement #BigData #DataSecurity #CyberSecurity 𝘪𝘮𝘢𝘨𝘦 𝘤𝘳𝘦𝘥𝘪𝘵: 𝘕𝘶𝘣𝘪𝘳𝘢𝘭