Responsibilities:
· Lead and engage the security related research activities with Academic organizations.
· Lead and participate in automotive security related international/industrial standard organizations.
· Propose and initiate automotive security technology project and activities aligning with department level roadmap.
· Focus on searching, experimenting and deploying cutting-edge security solutions to achieve enterprise level strategies.
· Guide and support the elicitation and analysis of security requirements for platforms and OEM projects.
· Aid in documenting the security interfaces, security interconnections, and the trust relationship between system components and external systems
· Research on Fuzzing as well as Penetration Testing techniques and develop customised Penetration Testing and Vulnerability Assessment on communication, electronics and embedded OS of Automotive E/E products.
· Engage in code review.
Requirements:
· Bachelor's degree (and above) in Information Security, Engineering, Computer Science or related field.
· Deep knowledge in applying C, C++, JAVA or other scripting for different embedded system development.
· Knowledge of security engineering (building secure systems), Operating Systems and network security, common attack patterns and exploitation techniques。
· Knowledge of system security analysis techniques such as threat modelling, attack trees etc.
· Excellent written and verbal communication skills。
· Experience with embedded systems will be added advantage。
· Experience with Automotive industrial protocols will be added advantage
PREFERRED SKILLS AND EXPERIENCE:
· Knowledge with Security Engineering and Assurance methodologies e.g. fuzzing, static and dynamic code analysis.
· Knowledge with common attack patterns and exploitation techniques. Ability to write fully functional exploits for common vulnerabilities such as simple stack overflow, cross-site scripting, or SQL injection.
· Experience in using standard Security Assessment and Penetration Testing tools such as Burp Suite, Metasploit, IDA Pro etc.
· Data Science techniques such as clustering, anomaly detection, and machine learning leveraging data analysis tools such as Splunk, MapReduce, SQL, R, MatLab etc.