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Guest Article

AI – A Key Element in Bridging Security Gap for IoT Devices

IoT (internet over things) devices are fairly commonplace in today’s world. As internet connectivity rises around the globe, so too is the number of connected devices. IoT devices have vast potential as enablers of automation, intelligence, scale, and efficiency across businesses as they facilitate the connectivity and transfer of data across everyday devices. It has become an essential or “must-have” technology for businesses in the digital landscape. IoT is spread across various sectors namely healthcare, hospitality, manufacturing all the way up to transportation, paving the way for smart life, smart city, smart mobility and smart industries.

However, with the rapid adoption of IoT devices globally also comes increasing vulnerability to significant risks, mainly to security. As the overall number of IoT devices is increasing, enormous amounts of IoT data are being generated which is in turn transferred between physical and cloud-based network environments. This gives rise to the question about data security. Any sort of data theft or breach can lead to long-standing consequences, such as but not limited to, damage to an organization’s reputation, customer data being compromised, financial losses, theft of personal identity, operational downtime, and risk of loss of intellectual properties. There can be many reasons for IoT data breaches or security failures, ranging from targeting devices relying on predictable passwords to interrupting and breaching communication systems and creating a new entry point to the network.

There are several challenges face by IoT networks:

Insufficient Testing and Updating: the biggest problem when it comes to the cybersecurity of IoT devices is that most companies simply don’t support them sufficiently after their release. In fact, many IoT devices don’t even have the capability of being updated, even against the most common types of cyberattack. This means that even a device that was secure when it was released quickly can become highly vulnerable.

Default Passwords: A second major — and avoidable — problem with IoT devices is that they ship with default passwords, and users are not reminded to change them in order to secure their home IoT networks. This is despite industry and government-level advice against using default passwords. For instance, this vulnerability led to the highest-profile IoT hack to date, the Mirai botnet, which compromised millions of IoT devices by the simple method of using their default passwords.

New Types of Ransomwares: IoT devices are particularly susceptible to hacking for a more complex reason: They are integrated into the home and corporate networks to a degree unprecedented in traditional systems. IoT devices typically have a very rapid development process, and during this rush there appears to be no time to think through what such devices need access to. That will in turn create a huge problem, because it can mean that spyware in the IoT can access far more information than it should be able to.

Botnets: A botnet is a network that combines various systems together to remotely take control over a victim’s system and distribute malware. Cybercriminals control botnets using Command-and-Control-Servers to steal confidential data, acquire online-banking data, and execute cyber-attacks like DDoS and phishing. Cybercriminals can utilize botnets to attack IoT devices that are connected to several other devices such as laptops, desktops, and smartphones.

Advanced persistent threats: Advanced persistent threats (APTs) are a major security concern for various organizations. An advanced persistent threat is a targeted cyber-attack, where an intruder gains illegal access to a network and stays undetected for a prolonged period. Such cyber-attacks are difficult to prevent, detect, or mitigate.

Artificial Intelligence can be of great assistance in overcoming these trials, due to rapid advancements in technology. Some ways AI can help in:

How AI can help:

Prevention over protection: Detection and real-time response to an incident should take precedence over traditional protection mechanisms. By introducing technologies such as AI and ML, organizations can effectively and efficiently prevent complex cyberattacks. Amid the switch to prevention, businesses will adopt comprehensive security framework factoring in elements such as risk and compliance, data security, and privacy management that are well supported with analytics.

Collaboration: Amid rapid technological advances, innovations, and increased connectivity, IoT providers are exploring markets to expand their businesses. Next generation connectivity businesses are looking for solutions that can integrate with the network infrastructure of different players. Cybersecurity companies are partnering with AI-based technology providers and investing in R&D to design new solutions and tap business opportunities.

Edge Computing (EC): In edge computing, data are transmitted within the network or within the device. Data movement is reduced as compared to fog computing, which alleviates security concerns. Real-time services such as intrusion detection, identity recognition, access management enable edge computing to strengthen security against a variety of threats and attacks, including battery drain, hardware failure, eavesdropping, node capture, DoS and DDoS, SQL injection, jamming, malicious attack, data integrity, and cloud flooding attacks

Prisma AI’s Contributions to IoT Security

Prisma AI has been innovating with its own IoT developments, as well as security measures for the same. As of now, Prisma AI has developed backend algorithm encryption, device-based MAC Address checking, Authentications for registered devices and users, and most importantly end-to-end encryption for drone feeds. Prisma AI’s own Med-I-Box is a wireless IoT device which does the job of transmitting a patient’s medical data to doctors if hospitals are not readily available in the vicinity. Prisma AI has developed many technologies such as facial recognition, object detection, body behavioral analysis systems that work in tandem with camera networks for their designated purpose.

Internet over Things is still relatively new especially when it comes to consumer IoT devices, so security measures are expected to improve as this technology grows. When purchasing any new IoT device, it’s very important to be aware of relevant security threats and take steps to protect your networks. While IoT devices are incredibly convenient and the next phase to technological growth and innovation, they can also be a major target for cybercriminals.

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