Dr. Vivek Yoganand, Sr. Technical Engineer, Openshift Security and AI Specialist, Red Hat Enterprise Linux
As a prospective candidate for a senior leadership role in the field of IT, Dr. Vivek Yoganand brings forth a comprehensive skill set that encompasses areas such as leadership, Cybersecurity, Artificial Intelligence (AI), Internet of Things (IoT), DevOps, and Cloud security. His proficiencies extend to advanced infrastructure tasks, intricate networking dynamics, and the nuances of cloud computing. He possesses significant expertise in architecting complex infrastructures, applying patches effectively, and seamlessly integrating OpenShift while maintaining a steadfast commitment to bolstering container security. His adeptness extends to overseeing the orchestration of the DevOps Pipeline, managing the complete lifecycle from installation and testing to operational oversight, version control, audits, troubleshooting, and the continual maintenance of systems. Rooted in a background of supporting user system operations and implementing cloud solutions, his skills have been honed, aligning both functional and technical proficiencies. This positions him ideally to offer insightful leadership and guidance to the members of his technical team. His enthusiasm for collaborative teamwork, coupled with his readiness to confront and conquer formidable challenges, underscores his robust work ethic and sense of accountability.
Educational and professional journey
- Philosophy of Doctorate
2014 - 2019 Thesis Title - Deep Learning - Video
Analytics & AI
MULTI LEVEL REGION GROWING APPROACH FOR EFFICIENT FACE TRACKING IN VIDEO SURVEILLANCE WITH INVARIANT FEATURES USING TRI-VIEW BINARY PATTERNS AND ANN.
- MBA - International Business
2013 Bharathiar University, Coimbatore, India
A Master of Business Administration in International Business program typically covers finance, marketing and human resource topics on an international level. MBA in International Business programs prepare students for a management, trade or general business career that can be conducted on a global scale.
- M.Tech - Mulitmedia Technology
2011 SRM University, Chennai, India
Multimedia technology includes interactive, computer-based applications that allow people to communicate ideas and information with digital and print elements. Professionals in the field use computer software to develop and manage online graphics and content.
- B.E - Computer Science & Engineering
2009 Anna University, Chennai, India
Computer Science Engineering (CSE) encompasses a variety of topics that relates to computation, like analysis of algorithms, programming languages, program design, software, and computer hardware. Computer Science engineering has roots in electrical engineering, mathematics, and linguistics.
Areas of expertise
AI, MLOPS, Deep Learning, Cyber Security, DevOps, CLOUD, Corporate Trainer, and Technical Evangelist
Publications
- Face detection approach from video with the aid of KPCM and improved neural network classifier
- Pose and Occlusion Invariant Face Recognition System for Video Surveillance Using Extensive Feature Set
- An efficient PCA based pose and occlusion invariant face recognition system for video surveillance
- Region Growing and Modified Neural Network Classifier Based Face Detection Technique from Video
- A Novel ORLLTMLP-Based Attack Detection and Blockchain-Aware Security Framework Using LCTFA in Smart City Applications
- An Enhanced Aggregated Data Forwarding and Distributed Clustering Strategy for Lifetime Maximization in Wireless Sensor Networks
- Modified Design Hardware and Wireless Sensors Networks for Designing Future Combat System
- Distribution of Wireless Sensor Network for Efficient Environmental Monitoring and Greenhouse Control
- An Enhanced Distributed Clustering Methodology and Data Aggregation in Connecting Dissimilar Wireless Sensor Networks
- Multiview face tracking in videos using clustering and tracklet linking technique
- Design of Accident Detection System Based On Vehicular Networks and Infrastructure Networks for Future Generation Vehicles.
- Mobile Image Mining for Granite Quality Detection
- Measurement of Failure Size in Software Testing Techniques
- Probability of Failure-free Operations with Software for Defect Management
Achievements
Dr. Vivek Yoganand has 10 years of extensive experience in Linux, DevOps Automation, Cyber Security, AI/ML, Openshift, Datacenter, and Security patching. He has worked hard & contributed services in diversified fields & is still learning. He is ready to take on any challenging task and is playing a major role in DevOps Automation.
- 5 Degree Holder (B.E., M.Tech., MBA., BGL(LAW)., PhD with Distinction)
- 15 Certifications (RHCE, Oracle, IDRBT, Fortinet, CISCO, Aviatrix, CISSP, CISA, etc…
- 10 International Publications (Springer, Scopus, etc...
- Trained and given the placement for 1000+ candidates which they get an offer at the global level.
The scope of data security after the latest widespread use of AI
The widespread use of AI has introduced both opportunities and challenges for data security. Here's a breakdown of the scope of data security in this evolving landscape:
Increased Attack Surface:
AI systems rely on vast amounts of data for training
and operation. This creates a larger attack surface for malicious actors
targeting data theft, manipulation, or poisoning.
Evolving Threats:
AI can be used by attackers to develop more
sophisticated methods of compromising data security. For instance, AI-powered
tools can automate social engineering attacks or exploit vulnerabilities in AI
systems themselves.
Privacy Concerns:
The widespread use of AI raises concerns about user
privacy, especially when dealing with sensitive data. AI algorithms can
potentially infer personal information or create discriminatory biases based on
the data they are trained on.
Opportunities for Improvement:
AI can also be a powerful tool for enhancing data
security. AI-powered threat detection systems can analyze vast amounts of data
to identify and respond to security incidents in real-time. Machine learning
algorithms can be used to detect anomalies and suspicious activities, improving
intrusion detection capabilities.
The Scope of Data Security:
In light of these developments, data security needs to
be addressed with a broader scope:
- Data Governance: Strong data governance policies are essential to ensure data is collected, stored, and used responsibly. This includes clear ownership, access controls, and data minimization principles.
- Security by Design: AI systems should be designed with security in mind from the very beginning. This includes secure coding practices, vulnerability assessments, and penetration testing.
- Explainability and Transparency: AI models should be explainable and transparent to identify potential biases or data manipulation attempts. This allows for better trust and accountability.
- User Education: Educating users about data privacy and how AI interacts with their data is crucial. Users should be aware of potential risks and have control over their data.
Overall, the scope of data security has expanded with
the rise of AI. While AI presents new threats, it also offers tools and
techniques to enhance security. By implementing a comprehensive approach that
addresses both the challenges and opportunities, organizations can leverage AI
while mitigating data security risks.
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