Best Security Audit Service in Agriculture Industry

Why Cybersecurity needs to be a priority for the Agriculture Industry ?

Agricultural cybersecurity is a rising concern because farming is becoming ever ‎more reliant on computers and Internet access. During the last few years, the ‎agrotechnology community, public sector and researchers have been alerted to the ‎problem and a significant amount of research has focused on the issue.‎

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Why Industry is a target for cybercrime (Business Risks)‎

Criminals think that larger businesses have the resources to pay the demands ‎without a second thought and smaller businesses often lack the necessary updates ‎that are needed to fend off cybercriminals. For instance, a farm services company in ‎Iowa, NEW Cooperative Inc, recently took its systems offline to contain a security ‎threat. A notorious criminal group known for ransomware attacks took credit for it.‎

Cybersecurity in Agriculture Industry is a priority.

How Industry is targeted (Technical Threats)‎

The Digital Transformation

The digital transformation of the agriculture sector is expanding it from the physical ‎world into the cyber realm. While the adoption of internet of things (IOT) and smart ‎technologies opens the door to innovation and new efficiencies, it also exposes the ‎sector to new cyber threats. ‎

E-Crime Operations

E-Crime operations are perpetually looking for new victims, especially among those ‎larger businesses perceived to have a high capacity to pay. There are multi types of ‎threat like, Hacktivist Threat, Targeted Threat, E-Crime Threat

The challenges Industry is facing

01

Meet rising demand for more food of higher quality

02

Stay resilient against global economic factors

03

Adopt and learn new technologies

04

Cope with climate change, soil erosion and biodiversity loss

05

Satisfy consumers' changing tastes and expectations

06

Investment in farm productivity

Invesics vision

Top tips for securing Agricultural Industry

Using AI and Machine learning-based surveillance systems to monitor every crop ‎field's real-time video feed identifies animal or human breaches, sending an alert ‎immediately. AI and Machine learning improve crop yield prediction through real-time sensor data ‎and visual analytics data from drones.‎

Using AI and Machine learning

Yield mapping is an agricultural technique that relies on supervised machine learning ‎algorithms to find patterns in large-scale data sets and understand the orthogonality ‎of them in real-time, all of which is invaluable for crop planning.‎

Yield Mapping

There are steps that many companies in this sector can take to protect themselves ‎from threats. Consult us to learn more