Secure your AI with AIShield

AI Security is critical for Building Digital Trust

Is your AI Secure? Run a demonstration!

As a one-stop AI security solution, AIShield secures your AI/ML assets against adversarial threats, and prevents financial loss, damage to brand reputation and intellectual property theft.

Assess. Detect. Defend.

Threats posed to unsecured AI

Explore a few examples below and learn about the damage threat actors can inflict in real-world scenarios.

Autonomous Driving AI security solution Bosch

Automotive

AI is heavily used when it comes to driver assistance and autonomous driving

Automotive

In recent times attackers are able to tamper the ADAS AI driven traffic sign detection models and make them misclassify the signs. A similar incident happened with a big automotive OEM when it could not read the sign properly.This can result in serious physical and safety concerns.
Similar such attacks are also seen in Pedestrian Detection ADAS AI algorithm. Attackers can manipulate the surroundings in such a way that the system misclassfies pedestrian. This can lead to incorrect driving behaviour and can lead to loss of life, This further damages the brand reputation.

AI is heavily used when it comes to driver assistance and autonomous driving

Healthcare and Med-Tech

Healthcare and Pharma industry leverages novel computer vision techniques for early detection, prevention of diseases, and novel drug discovery processes

Healthcare and Med-Tech

Advanced computer vision algorithms play an essential role in early cancer cell detection. These algorithms leverage propriety research and datasets collected over long durations. Extraction of such models can lead to a loss of competitive advantage
The pharmaceutical industry leverages the power of AI to accelerate novel drug discovery. Fear of IP loss/theft erodes trust in such consortium collaborations slowing down the whole process. Secure AI development methods will allow consortiums to innovate collaboratively.

Healthcare and Pharma industry leverages novel computer vision techniques for early detection, prevention of diseases, and novel drug discovery processes

Banking, Finance and Insurance

Search Engines AI security solution Bosch

Banks(especially neo-banks) have recently deployed a fraud detection and identity verification model driven by AI

BFSI

Recently there have been complaints of fraud in the BFSI industry. Attackers query the model and train a copycat model mimicking the behavior of the original system. They use this knowledge to launch intelligent evasion attacks.
In an actual incident, a threat actor successfully fooled a facial recognition system and defrauded the bank. The failure of the data science model led to a reported $381 Million loss. The incident led to a decrease in the company's valuation and eventually a substantial financial and reputation loss.

Banks(especially neo-banks) have recently deployed a fraud detection and identity verification model driven by AI

Manufacturing and Industry 4.0

Smart Manufacturing and I4.0 leverage AI heavily to deliver high productivity and efficiency

Manufacturing and I4.0

Automated production lines use highly customized optical inspection AI systems to detect product defects. Extraction of this highly adaptable, task-flexible, and reconfigurable algorithm can enable malpractitioners to steal the intellectual property leading to a loss of competitive advantage.
Intelligent manufacturing robots leveraging AI help industries automate repetitive tasks, reduce human error to a nominal rate, and increase productivity. The robots can be poisoned and subverted to malfunction. Malfunctioning robots can cost substantial financial and even reputational losses in case of faulty products.
AI/ML-powered predictive solutions allow the manufacturer to predict when machines will require maintenance. Threat actors can extract the models and use these solutions unlicensed. These can be further tampered with provide inaccurate information and increasing maintenance cost.

Smart Manufacturing and I4.0 leverage AI heavily to deliver high productivity and efficiency

Retail, CPG and E-Commerce

AI providing intelligent sentiment analytics, recommendation engines, and warehouse management is used widely in the CPG, Retail and E-commerce industry

Retail, CPG and E-commerce

Recommendation engines are one of the most crucial AI assets for e-commerce websites to gain customers. Threat actors can poison AI/ML models to provide irrelevant recommendations, leading to loss of reputation and customer base.
Speedy delivery and efficient warehouse management are vital requirements for e-commerce players. Organizations have been using AI for warehouse management, which is prone to Evasion attacks. Threat attackers tamper with the AI models to misclassify the products leading to incorrect sorting and delivery.
AI models trained to provide insights using sentiment analysis lead to increased customer sales in the CPG industry. These AI models can be tampered leading to inaccurate insights, which cause substantial financial loss.

AI providing intelligent sentiment analytics, recommendation engines, and warehouse management is used widely in the CPG, Retail and E-commerce industry

Mobile Applications AI security solution Bosch

IT and ITeS

Advanced Natural Language Processing, Deep Learning, and Analytics algorithms help perform many tasks in the IT and ITeS industries

IT and ITeS

An enterprise-grade email spam classifier was subjected to evasion attacks. Based on the knowledge of the underlying AI-based spam classifier, Attackers were able to evade the model and launch phishing attacks on more than 16 Mio customer accounts.
A sophisticated NLP-based chatbot was compromised after threat actors launched a coordinated poisoning attack. Chat-bot was exposed to a lot of harmful content turning the good-intentioned talk-along chatbot reply with some nasty remarks. The chatbot was decommissioned within 8 hours of its launch, along with a public apology leading to brand erosion.

Advanced Natural Language Processing, Deep Learning, and Analytics algorithms help perform many tasks in the IT and ITeS industries

AI Security Whitepaper

When it comes to securing AI Systems, it's hard to patch or mitigate what you can't detect.

Understand what are novel risks affecting AI systems. Review perspectives on AI Security from research community, businesses and regulators. Gain high-level recommendations for your organization to enhance AI Security of your AI/ML assets.

Access the AI Security Whitepaper

Benefits of AIShield

Below are some benefits provided

Out-of-the-box secure AI

Security comes as a core selling point for your AI products. Your AI model gets end-to-end security features throughout the product lifecycle with vulnerability analysis, defense generation, real-time threat identification, and telemetry.

Flexible EDR mechanisms

Built for customization, the AIShield enables the deployment of end-point defense mechanisms along with the original model in target environments such as cloud or embedded.

Easy automated workflows

Available as a Cloud-SaaS offering with interactive, user-friendly dashboards, metrics, and reporting with API integration with your MLOPs pipelines.

Bring Trust to AI

Detailed threat and risk assessment reports along with visual indicators and metrics along with relevant artifacts aid decision-making for business leaders and product managers in the continuous protection of their AI systems.

Protect IP and Investments

With the in-built telemetry feature, the automated defense mechanisms as a part of your AI system will aid in the protection of crucial IP and assets and thus keep your business safe from the market impact of attacks.

Enable Regulatory Compliance

Leverage proprietary risk assessment framework and vulnerability scanning feature to demonstrate compliance with relevant regulatory guidelines with easy and accessible documentation required for certification.

Offerings by AIShield

We save your team time - for example, by providing recommendations for specification, bid comparison, templates and playbooks.

Solution

Customized enterprise implementation solutionizing for AI security

Execute a proof of concept for prioritized AI security use cases.
Receive vulnerability assessment report & integrate defense model to mitigate threats to AI.
For enterprise-wide implementation & scaling, leverage the SaaS offering.

AIShield Solution on MS Azure

Product

Leverage the product for an end-to-end AI security experience

Vulnerability assessment with user-friendly visualization and custom Endpoint Defense generation.
Real-time threat informed Endpoint Defense and Response.
Integration with MLOPs pipelines and leading SIEM/SOAR providers to get novel AI security insights.

AIShield on AWS

AIShield for MS Sentinel

AIShield on MS Azure

Working with AIShield

We are your Trusted Partners in your AI journey. We have unmatched research with IP leadership, deep AI Security expertise, and proven solution.

We Prove Security

A neutral third party that can help you prove your confidence is well founded in the security posture of AI.

We Validate Security Posture

See if your current security tools and posture can detect, prevent and respond to adversarial ML attacks.

We Show & Tell Leadership

Our assessment provides unprecedented transparency in visual and actionable reports to leadership.

We Demonstrate Launch Readiness

Show the impact of cyber-attacks and mitigation on AI applications and help shift the culture to security by design.

We Provide CIA Triad Assurance

Assure that Confidentiality, Integrity, and Availability risks are understood and taken care of in the best possible way.

Security in AI/ML requires new approaches because of novel attack vectors that teams must take into consideration as they build out their AI/ML infrastructure.
Dan Jeffries, Managing Director, AI Infrastructure Alliance

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AIShield in the News

Resources by AIShield

Here you can find Whitepapers, Case Studies, and Talks on AI security topic

AIShield Overview

Overview on AI Security and AIShield's offerings

Media

Solution Case Studies

Read more to understand how AIShield has helped in various domains

Media

Digital Brochure

RSAC 365

Fighting New Era Bandits Who Are Plundering Your AI/ML Application

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Frequently Asked Questions

Are there any upcoming regulations and standards regarding AI Security?

Why do organizations need to secure AI assets?

With the advancement in technology, there have been increasing AI algorithm failures. The complexity and number of such losses have been growing every day. Looking at some of the facts and current industry scenario indicates the need for AI Security, and correct measures must be in place before a significant model failure.

According to Microsoft, 89% of organizations have the right tools to secure their AI.
Gartner found that 60% of AI providers will include a means to mitigate possible harm to their AI assets by 2024
IBM quotes that 80% cost difference between cyberattack scenarios, where secure AI was developed vs. not deployed.

What is AI Security?

AI security refers to the domain of securing AI systems. One can also refer to cybersecurity for AI applications & models/algorithms. AI Security focuses on identifying, detecting, preventing, remediation, information, investigating and responding to malicious attacks on AI Systems. The field is concerned with AI model vulnerabilities, studying attacker capabilities, consequences of attacks, and building algorithms that can resist security challenges.

How is AIShield different from my existing cybersecurity measures?

AIShield is the last layer of defense in an existing device, network & application security. It protects AI models, which are highly invested and most valuable assets of an AI system. AI model and system security is not covered under existing Cybersecurity measures since AI security attacks can happen as part of an AI application’s input, output, and data payload where the hacker poses as a legitimate user.

What are various AI/ML adversarial attacks?

AIShield protects AI systems against four types of adversarial attacks.

Model Extraction – The act of stealing and extracting a proprietary model

Model Evasion – The act of making a model do the wrong thing making it intentionally biased

Data Poisoning – The act of making a model learn wrong things by injecting malicious samples

Model Inference – The act of making the model reveal its logic and data

Associations and Industry Consortiums

Partners

Recognitions

Founders

About Us

Manojkumar Parmar

Function - CEO,CTO, Location - Bangalore, India
- Manoj is a established Technology leader with years of experience in field of AI,ML, Quantum Computing and Automotive.
- Manoj heads AIShield in the capacity of Chief Executive Officer and Chief Technology Officer defining and driving the program and technology strategy.
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Amit Phadke

Function - CPO, Location - Bangalore, India
- Amit is a seasoned Product leader with years of experience in field of Automotive Software and Product Management.
- Amit heads AIShield in the capacity of Chief Product Officer defining and driving product and platform strategy alonwgith overseeing engineering activities.
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Shiv Kumar

Function - CBO, Location - Bangalore, India
- Shiv is a seasoned Business leader with years of experience in field of sales, partnerships for emerging technologies.
- Shiv heads AIShield in the capacity of Chief Business Officer defining and driving customer sales and partnership strategies.
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Advisory

Meet our Scientific Advisory Board

Prof. Dr. Biggio Battista

Function - Assistant professor, University of Cagliari, Italy Co-founder, Pluribus One , Location - Italy
- Battista Biggio is an Assistant Professor at the University of Cagliari, Italy, and co-founder of the cybersecurity company Pluribus One. He has provided pioneering contributions in machine-learning security, playing a leading role in this field. He has managed six research projects and regularly serves as a PC member for ICML, NeurIPS, ICLR, and IEEE Symp. S&P, and USENIX Security. He chaired IAPR TC1 (2016-2020), co-organized S+SSPR, AISec, and DLS, and served as Associate Editor for IEEE TNNLS, IEEE CIM, and Pattern Recognition. He is a senior member of IEEE and ACM and a member of IAPR and ELLIS.
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Prof. Dr. Lejla Betina

Function - Professor, Digital Security Group, Radboud University, Netherlands , Location - Netherland
- Lejla Batina is a professor in the Digital Security group at Radboud University in Nijmegen, the Netherlands. Her research group comprises 10+ researchers, and 9 Ph.D. students have graduated under her supervision.
- She is a senior member of IEEE and an Editorial board member of top journals in security, such as IEEE Transactions on Information Forensics and Security and ACM Transactions on Embedded Computing Systems.
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Prof. Dr. Mario Fritz

Function - Faculty member, CISPA , Honorary Professor, Saarland University , Fellow, ELLIS , Location - Switzerland
- Mario Fritz is a tenured faculty at CISPA, an honorary professor at the Saarland University, and a fellow of the European Laboratory of Learning and Intelligent Systems (ELLIS). His work centers around Trustworthy Information Processing, focusing on the intersection of AI & Machine Learning with Security & Privacy.
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Secure your AI with AIShield

Is your AI Secure? Run a demonstration!

Threats posed to unsecured AI

Automotive

Healthcare and Med-Tech

Banking, Finance and Insurance

Manufacturing and Industry 4.0

Retail, CPG and E-Commerce

IT and ITeS

AI Security Whitepaper

Benefits of AIShield

Out-of-the-box secure AI

Flexible EDR mechanisms

Easy automated workflows

Bring Trust to AI

Protect IP and Investments

Enable Regulatory Compliance

Offerings by AIShield

Solution

Product

Working with AIShield

We Prove Security

We Validate Security Posture

We Show & Tell Leadership

We Demonstrate Launch Readiness

We Provide CIA Triad Assurance

AIShield in the News

Resources by AIShield

AIShield Overview

Solution Case Studies

Frequently Asked Questions

Are there any upcoming regulations and standards regarding AI Security?

Why do organizations need to secure AI assets?

What is AI Security?

How is AIShield different from my existing cybersecurity measures?

What are various AI/ML adversarial attacks?

Associations and Industry Consortiums

Partners

Recognitions

Founders

Manojkumar Parmar

Amit Phadke

Shiv Kumar

Advisory

Prof. Dr. Biggio Battista

Prof. Dr. Lejla Betina

Prof. Dr. Mario Fritz