What are the major trends in AI security that are transforming the security industry?
This question is addressed in the 2024 Security Megatrends Report, conducted by the Security Industry Association (SIA)- a trade association representing global manufacturers, software firms, and security system providers. SIA’s security trends 2024 analysis offers future-looking insights for security businesses and practitioners alike.
Here are the top 4 megatrends in security, highlighting potential risks, challenges and opportunities that AI is bringing to the security sector:
1. The security Of AI
The leading megatrend of 2024 centers around the Security of AI. As protection and trust are fundamental to the security industry, ensuring AI is both secure and trustworthy is crucial. To do this, companies must get control of their data- and establish corporate policies about their data use, along with the development of safe and ethical AI and cybersecurity practices. To this end, corporations need to adopt a two-pronged approach to implement the security of AI with cyber/AI attack prevention. They must establish:
Robust Cybersecurity Measures
Key measures of cybersecurity in AI can be attained by implementing:
- Zero Trust Architecture-This is a widely adopted cybersecurity framework used by many (Microsoft, Google, IBM, and Cisco, government agencies). By default, it assumes no user of a device, inside or outside an organization, can be trusted. Every access request is thoroughly authenticated, authorized and encrypted.
- Continuous monitoring and threat detection– Companies use AI and machine learning (ML) to detect and respond to threats in real time, with a focus on potential vulnerabilities or attacks. They identify AI threat vectors- threats such as data poisoning, which is malicious or misleading data introduced by an adversary (e.g. adding false data to a facial recognition training set to make it incorrectly identify certain individuals). Other adversarial AI attacks are model inversion attacks that reverse-engineer sensitive data from a training set so as to obtain access to private information like medical records or financial details.
- Data Encryption and Privacy– Strong encryption methods are established for data in transit and at rest. Plus security practitioners keep a strong compliance with GDPR (General Data Protection Regulation) guidelines.
Ethical AI Practices
Trustworthy ethical practices are established by putting into place:
- AI principles and governance– Ethics committees are established that oversee implementation of ethical principles of AI in the security industry.
- Explainability and transparency– Practitioners make AI models clearer with customers who use AI-driven services.
- Bias Mitigation– Bias mitigation reduces any bias of AI models and machine learning security by continuous audit of datasets and algorithms to prevent discriminatory outcomes. A good example of discriminatory bias was the 2019 case with tech entrepreneur David Heinemeier Hansson. He reported that the Apple Card issued by Goldman Sachs had a gender bias favoring men, by offering him a credit limit 20 times higher than his wife’s, despite her having a higher credit score. The machine learning model inferred gender as an indirect negative factor of proxy discrimination, being based on historic data containing that bias.
2. AI:Visual intelligence, Not Video Surveillance
The second megatrend of 2024 is AI’s impact and analytics that has changed camera systems to Visual Intelligence, not simply video surveillance anymore. Additionally, visual intelligence has surged, leveraging the IoT (Internet of Things), which was initially begun as a vast network of sensors not primarily focused on visual data. The IoT (familiar to users as Wi-Fi, bluetooth, healthcare wearable devices, smart homes, or voice assistants like Alexa) is embedded with sensors, software and connectivity technology. IoT is now evolving into a vast network dominated by camera sensors and visual intelligence.
On the positive side, these advanced AI-connected cameras will:
- Provide greatly boosted security/surveillance in real time, detecting unusual or suspicious activities, heat signatures, opened doors/unauthorized access, vandalism.
- Make real-time decisions after analyzing data instantly and triggering alerts for response (e.g. traffic management that detects accidents or congestion, and then alerts or controls traffic signals).
- Aid industries with use of visual intelligence to improve operations– by monitoring production lines, spotting defective products, and streamlining the need for manual oversight. Analyze customer behavior for retailers, improving store layouts or enhancing customer service.
- Allow deep searches of recorded content– moving to a functioning consulting role beyond traditional surveillance. Video is being analyzed in real time, and not just stored.
On the downside, these advanced AI-connected security cameras also:
- Raise privacy concerns, with constant surveillance seen as intrusive, and personal freedoms compromised.
- Generate large amounts of sensitive data that can be vulnerable to cyber-attacks, hacking or data breaching.
- Have high costs to implement and maintain. They depend on high-speed internet and data storage systems, which may be prohibitive for some areas or organizations.
- Prompt ethical concerns of abuse by authorities, mass surveillance without consent, and the destruction of civil liberties.
- Are susceptible to bias and inaccuracy, that lead to false positives or discrimination (e.g. facial recognition technology has higher error rates when identifying certain ethnicities or genders, which has led to wrongful accusations). False alarms and overload can also cause “alert fatigue” where users begin to ignore true alerts.
- Contribute to carbon emissions and environmental concerns, with increased power usage, data centers that draw on power for operations, e-waste.
3. Generative AI
This third megatrend is Generative AI- a growing subset of artificial intelligence techniques and models that generates new content or data based on patterns from existing data. These models can generate text (like GPT-3), art or images (like album covers or advertising), music composition (e.g. OpenAI’s MuseNet or musicians creating melodies or harmonies), or new molecular structures (used to design new drugs). Generative AI can also be misused. Deep fake media is on the rise- with false videos and manipulated interviews.
Some broad applications of generative AI for businesses- especially in security- are:
- Use of AI chatbots for real-time customer service.
- Improved alarm monitoring giving more efficient control of security systems.
- Matching staffing levels of contract officers with incident occurrences.
- Combining data from intrusion/access systems to identify unusual patterns.
- Analysis of project locations and types, technician skills, and service truck GPS data- to determine the most efficient routing or use of field techs.
4. Regulation Of AI
The fourth 2024 megatrend for the future of the security industry is the Regulation of AI. Standards are necessary to provide the security and trustworthiness outlined in the first megatrend Security of AI. On Oct 30, 2023 the Biden Administration released an executive order on AI. Some US states have also established task forces to examine AI and cybersecurity technologies. Ultimately a comprehensive framework is needed to prevent a problematic patchwork of laws on AI.
The main requirements of these regulations will ensure that AI is:
- Safe (has backup systems and fail-safes in case of malfunctions)
- Transparent (uses explainable AI [XAI] that informs how decisions are made)
- Traceable (has systems built to allow clear scrutiny and analysis by users, developers and auditors)
- Non-discriminatory (employs data that avoids bias, with regular audits for fairness)
- Environmentally friendly (relies on algorithms with less computation power, green data centers)
- Overseen (by people rather than automation to prevent harmful outcomes)
- Using data privacy standards (with encryption practices, secure data storage, strict regulations)
Legislative investigations are ongoing for biometrics and facial identification AI (use of unique body and face measurements for ID/access control). Businesses are hesitant about full implementation due to negative public perceptions, privacy concerns, and unclear laws.
These are the top four megatrends from the 2024 Security Megatrends Report. They illustrate how AI is transforming the security industry- with key trends, challenges, and solutions as businesses and security practitioners prepare for emerging security threats.
