Cross-Functional Collaboration for Enhanced Cybersecurity: Gaurav Sharma Of Chetu On The Best Practices For Effective Cross-Functional Collaboration
An Interview With David Leichner
Clear Objectives: Define shared goals and outcomes. For instance, marketing and product teams can collaborate to align messaging and features for a successful product launch.
Cybersecurity is a collective endeavor, and implementing effective security measures often requires the cooperation of cross-functional teams. In the face of threats posed by malicious AI, how do product security managers foster this collaborative environment? How do they work together with various teams to build and maintain a secure digital infrastructure for their organization’s products?
In this series, we aim to learn the strategies, practices, and approaches employed by product security managers to foster cross-functional collaboration toward improved security. We’re interested in exploring the dynamics of these collaborations and how they contribute to the overall security posture of an organization. As a part of this series, we had the pleasure of interviewing Gaurav Sharma.
Gaurav Sharma is a Director of Operations at Chetu, a world-class software development and support services provider, overseeing Chetu’s Artificial Intelligence portfolio. With a proven track record of leading successful teams and projects, Gaurav has driven innovation in many industries for more than a decade. He has established himself as a prominent technology industry leader and an AI development and implementation expert.
Thank you so much for joining us in this interview series! Before we dig in, our readers would like to get to know you. Can you tell us a bit about how you grew up?
Growing up in a small town in India, I always had an insatiable curiosity for how things worked. Whether it was taking apart household gadgets or tinkering with computer components, I was driven by a deep desire to understand the inner workings of technology. In the early 2000s, while pursuing a computer science degree at a university, I learned about AI in one of my courses. I eventually became fascinated with Artificial Intelligence and Automation. I pursued a career in AI because of my inherent curiosity, rigorous education, and unwavering determination to excel in the computer science branch of AI and Automation.
Is there a particular story that inspired you to pursue a career in cybersecurity? We’d love to hear it.
In 2017, the WannaCry Ransomware Cyberattack happened, one of the biggest ransomware attacks ever. When news reports detailed the extent of the damage and the subsequent efforts to mitigate the threat, I became captivated by the intricate dance between hackers and defenders in the digital realm.
Can you share the most interesting story that happened to you since you began this fascinating career?
Since beginning my career, the most intriguing journey has been witnessing the evolution of human-AI interaction. From assisting in everyday tasks to aiding in complex research, the diverse and creative ways people have integrated AI into their lives continue to amaze and inspire me.
You are a successful leader. Which three character traits do you think were most instrumental to your success? Can you please share a story or example for each?
Successful leaders understand the importance of empowering their team members. They delegate responsibility, trust their team’s expertise, and provide the necessary resources and support. By doing so, they foster a sense of ownership and accountability within their team. The leader must define a framework that defines the path of success for their team, enabling the team to achieve their goals.
Are you working on any exciting new projects now? How do you think that will help people?
Yes, I’m working on several new projects in education and development. One project will help people utilize tools that will increase their skills and professional development.
How do emerging technologies like AI and machine learning influence the risk to the cybersecurity landscape?
The cybersecurity landscape is undergoing significant changes due to the emergence of AI and machine learning. These technologies have a dual impact: mitigating risks and presenting new challenges. They reshape cybersecurity risks in various ways.
For example, malicious actors leverage AI and machine learning to craft more sophisticated adversarial attacks that can outmaneuver conventional security measures. Such attacks involve manipulating AI models to exploit vulnerabilities and yield incorrect outputs.
In addition, if machine learning models are trained on compromised data, they can make flawed decisions, potentially resulting in security breaches. AI-driven detection systems can yield false positives and false negatives, mistakenly flagging harmless activities as threats or missing actual risks, which can undermine the efficacy of cybersecurity protocols. AI algorithms can inadvertently expose sensitive data, adding another layer of risk.
This raises concerns about maintaining user privacy while conducting data analysis, underscoring the intricate and challenging task of striking the right balance. Also, inadequately designed and tested AI models can inherit biases from their training data, introducing potential discrimination or unfair outcomes into cybersecurity decisions.
As AI and machine learning systems grow in complexity, their decision-making processes become less transparent, posing difficulties in effective threat analysis and response. Lastly, adopting AI-powered cybersecurity solutions often demands substantial computational resources and expertise, which might pose challenges, especially for smaller entities.
How are emerging technologies like AI and machine learning enhancing our capabilities to protect against these risks?
The impact of AI and machine learning on the cybersecurity landscape is notable, offering a range of positive influences. These emerging technologies hold great potential for enhancing cybersecurity through various beneficial effects.
For instance, they significantly bolster advanced threat detection capabilities. By analyzing vast datasets, AI and machine learning can recognize patterns and anomalies indicative of potential attacks. This leads to early threat identification and quicker incident response times.
Furthermore, these technologies enable streamlined incident responses through automated processes. Tasks such as log analysis, system isolation, and suggesting remediation actions can be automated and, in doing so, alleviate the manual burden on cybersecurity teams.
Additionally, AI-driven systems excel in behavioral analysis, establishing typical behaviors for users, devices, and networks. When deviations from these norms occur, alerts signal potentially unauthorized activities. Machine learning’s proficiency in discerning user behavior patterns also enhances authentication methods, improving reliability in biometric authentication like fingerprint and facial recognition.
Lastly, AI’s ability to identify suspicious email traits and URLs contributes to uncovering otherwise inconspicuous phishing attempts.
Could you highlight the types of cyber-attacks that you find most concerning today, and why?
Several types of cyberattacks are of significant concern due to their potential to cause substantial harm, disrupt critical services, and compromise sensitive information. In the dynamic realm of cybersecurity, several current threats stand out:
Ransomware attacks involve encrypting an organization’s data and demanding a ransom for its release. Such attacks have become more sophisticated and targeted, affecting critical infrastructure, healthcare systems, and even municipalities. The consequences encompass widespread disruption, financial loss, and the ethical quandary of ransom payment.
Supply Chain attacks exploit vulnerabilities within the software supply chain. Attackers compromise numerous organizations by infiltrating trusted software vendors and injecting malicious code into legitimate software updates. The SolarWinds attack of 2020 is a notable example of this threat vector.
IoT and OT Attacks are also of concern. As the Internet of Things (IoT) and Operational Technology (OT) systems expand, concerns about attacks targeting these devices and systems escalate. Compromised IoT devices can be used to unleash mass distributed denial-of-service (DdoS) attacks, while breaches in OT systems risk disrupting critical infrastructure.
Phishing remains a persistent threat due to its effectiveness in deceiving individuals into revealing sensitive data or installing malware. Additionally, social engineering attacks leverage human psychology to exploit trust and vulnerabilities.
Zero-day exploits target vulnerabilities in software or hardware that are unknown to vendors and lack patches. Attackers capitalize on these vulnerabilities before fixes are available, making zero-day exploits attractive to advanced threat actors for precise, targeted attacks.
These notable threats highlight the imperative of maintaining a vigilant cybersecurity posture, practicing thorough threat monitoring, and establishing proactive incident response plans. Organizations must remain attuned to evolving developments to counter these pressing cyber risks effectively.
Ok, thank you. Let’s now move on to our main topic of Cross-Functional Collaboration in cybersecurity. Let’s start with a basic definition so that we are all on the same page. What exactly is Cross-Functional Collaboration?
Cross-functional collaboration refers to individuals and teams working together from different departments or areas within an organization to achieve a common goal. In cybersecurity, cross-functional collaboration involves various teams such as IT, security, legal, compliance, risk management, human resources, and even executive leadership coming together to collectively address cybersecurity challenges and mitigate risks.
Can you share a few reasons why Cross-Functional Collaboration is so critical in today’s cybersecurity threat environment?
Cross-functional collaboration is critical today due to the evolving threat landscape. Cyber threats have become complex, targeting various aspects of organizations. Collaboration ensures a comprehensive approach to assess, respond, and mitigate these threats. The rapidly changing nature of cybersecurity requires real-time threat identification and response, which is facilitated by combining diverse expertise.
Cross-functional collaboration also aids in comprehensive risk management, addressing legal, regulatory, financial, and reputational risks. A coordinated response to incidents is crucial. Different teams contribute their specialized skills to minimize damage and recovery time. Regulatory compliance, especially in data protection, is effectively achieved through collaboration between legal, compliance, and security teams.
Human error plays a role in cyber incidents. Collaboration between cybersecurity and human resources is vital for education, awareness, and training programs to reduce human vulnerabilities. This approach optimizes resource allocation, aligns with business objectives, and integrates cybersecurity into the broader strategy.
The cross-functional collaboration unites different strengths, resulting in a more resilient cybersecurity stance. By pooling resources, knowledge, and skills, organizations can effectively counter the dynamic challenges of today’s cybersecurity landscape.
How does a leader effectively create a culture of Cross-Functional Collaboration?
Fostering a culture of cross-functional collaboration demands a purposeful and strategic leadership approach. This involves a series of deliberate steps to cultivate an organization’s collaborative ethos.
First, establishing a clear vision and ensuring effective communication are paramount. Leaders should articulate the significance of cross-functional collaboration in attaining organizational objectives. By underscoring how collaboration enhances efficiency, innovation, and overall success, leaders can set the foundation for a collaborative culture.
Furthermore, leading by example is instrumental in driving this cultural shift. Demonstrating collaboration by actively including diverse teams in projects and decision-making processes showcases its value. Encouraging team members to establish inter-departmental relationships and organizing workshops or team-building activities fosters cross-functional interaction effectively.
Aligning goals across departments for a unified sense of purpose and accentuating how each team’s contributions bolster the organization’s achievements cultivates a shared commitment to success. This is reinforced by creating an inclusive and supportive environment that values diverse perspectives, acknowledges collaborative efforts, and celebrates their positive outcomes.
Initiating projects that necessitate input from multiple departments and rotating team members through various projects to expose them to diverse viewpoints accelerates the integration of cross-functional collaboration.
Equipping team members with the requisite skills for fruitful interdepartmental collaboration involves providing training in collaboration, conflict resolution, and effective communication.
Confronting challenges inherent to collaboration, such as differing working styles or conflicts, requires creating platforms for constructive, open discussions. Regular assessment, feedback incorporation, and adaptive strategy refinement are essential for sustained success.
Lastly, empowering teams to make decisions that impact their work and fostering autonomy in collaboration while instilling a culture of trust through experimentation and learning from experiences emphasize the transformative potential of cross-functional collaboration. By methodically embracing these strategies, leaders can cultivate a culture of collaboration that propels innovation, agility, and organizational accomplishment.
Could you share any challenges you’ve encountered in promoting Cross-Functional Collaboration and how you’ve managed to overcome them?
Promoting cross-functional collaboration can be challenging. In my opinion, some of the significant ones are competing priorities among different departments and role ambiguities.
Here is the main question of our interview. What are your “5 Best Practices For Effective Cross-Functional Collaboration”?
1 . Clear Objectives: Define shared goals and outcomes. For instance, marketing and product teams can collaborate to align messaging and features for a successful product launch.
2 . Open Communication: Establish regular channels for information sharing. For example, IT and finance teams can use shared software to ensure transparent budget tracking for tech projects.
3 . Diverse Teams: Include representatives from various departments. For example, engineers and designers can collaborate to develop user-friendly software that meets technical and design requirements.
4 . Roles and Responsibilities: Clarify roles in collaborative projects. An example of this would be sales and customer support teams collaborating on a clear handover process to ensure seamless customer interactions.
5 . Feedback Loop: Create mechanisms for feedback and improvement. A good example is how HR and operations teams hold regular joint meetings to address employee concerns and enhance workplace processes.
You are a person of enormous influence. If you could inspire a movement that would bring the most amount of good to the most amount of people, what would that be? You never know what your idea can trigger. :-)
Sustainable Development and Environmental Conservation movement — A healthier environment and sustainable development contribute to an improved quality of life for people everywhere, ensuring a more equitable distribution of resources and opportunities.
How can our readers further follow your work online?
You can follow Gaurav Sharma and other Thought Leaders on the Chetu Blog.
This was very inspiring and informative. Thank you so much for the time you spent on this interview!
About The Interviewer: David Leichner is a veteran of the Israeli high-tech industry with significant experience in the areas of cyber and security, enterprise software and communications. At Cybellum, a leading provider of Product Security Lifecycle Management, David is responsible for creating and executing the marketing strategy and managing the global marketing team that forms the foundation for Cybellum’s product and market penetration. Prior to Cybellum, David was CMO at SQream and VP Sales and Marketing at endpoint protection vendor, Cynet. David is a member of the Board of Trustees of the Jerusalem Technology College. He holds a BA in Information Systems Management and an MBA in International Business from the City University of New York.
