PSPL - Proland Software

Tag: technology

3 Reasons Why Vehicles Need Cybersecurity

April 5, 2024 /

 

In the evolving landscape of transportation, vehicles have transcended their traditional roles to become interconnected, smart devices on wheels. This advancement, while revolutionary, introduces new vulnerabilities that can be exploited by cyber threats. The National Motor Freight Traffic Association (NMFTA) emphasizes the critical need for robust cybersecurity measures in the transportation sector. Here are three compelling reasons why vehicles require cybersecurity, aligning with the perspectives and initiatives spearheaded by the NMFTA.

1. Protection Against Unauthorized Access and Control

Modern vehicles are equipped with a myriad of wireless connectivity options, including Bluetooth, Wi-Fi, and cellular connections, which serve to enhance user experience and vehicle functionality. However, these gateways can also serve as entry points for hackers. The potential for unauthorized access and control poses not just a privacy risk but a significant safety hazard. Hackers can exploit vulnerabilities to remotely control vehicle functions, from navigation systems to critical components like brakes and engines. The NMFTA has been at the forefront, advocating for standards and practices that ensure secure communication protocols and system hardening to mitigate these risks. By adopting cybersecurity measures, the industry can safeguard against unauthorized access, ensuring that control of the vehicle’s systems remains firmly in the hands of its rightful users.

2. Ensuring the Integrity of Vehicle Systems and Data

Vehicles today are not just modes of transport; they are also data centers on wheels. They collect, process, and store vast amounts of data, from personal information to real-time performance metrics. This data, if compromised, could lead to severe privacy breaches and manipulation of vehicle performance. Cybersecurity measures are essential to protect the integrity of these systems and the data they handle. The NMFTA stresses the importance of encryption, regular software updates, and vulnerability assessments to defend against data breaches and ensure that the vehicle operates as intended. By securing vehicle systems and their data, stakeholders can prevent malicious actors from exploiting sensitive information and ensure that the vehicle remains reliable and safe for its users.

3. Supporting the Future of Autonomous and Connected Vehicles

The future of transportation is headed towards greater autonomy and connectivity. Autonomous vehicles, reliant on complex algorithms and constant data exchange to navigate and make decisions, represent the pinnacle of this evolution. The NMFTA recognizes that this future is only sustainable if cybersecurity evolves in tandem with these technologies. Cybersecurity measures are foundational to the trust and reliability of autonomous systems, ensuring that they can operate safely and efficiently without human intervention. This encompasses everything from secure software design practices to resilient communication networks that can withstand cyber attacks. As vehicles become more autonomous and connected, the role of cybersecurity in maintaining public safety and confidence in these technologies becomes increasingly indispensable.

 

In conclusion, the imperative for cybersecurity in vehicles is clear. From protecting against unauthorized access to ensuring the integrity of vehicle systems and data, and supporting the future of autonomous and connected vehicles, cybersecurity measures are essential. The NMFTA’s focus on these aspects highlights their importance in fostering a safe, secure, and reliable transportation ecosystem. As we advance into a new era of mobility, the commitment to cybersecurity will be a critical determinant of success.

The Importance of AI in Cybersecurity

August 23, 2023 /

In today’s interconnected digital landscape, cybersecurity has become a critical concern for individuals, businesses, and governments. As the complexity and frequency of cyberattacks continue to rise, traditional security measures alone are no longer sufficient to combat evolving threats. This is where artificial intelligence (AI) steps in, revolutionizing the field of cybersecurity and bolstering defense mechanisms. In this article, we’ll delve into the importance of AI in cybersecurity and explore other vital factors to consider for a robust cyberdefense strategy.

What is Artificial Intelligence?

Artificial Intelligence is the simulation of human intelligence processes by machines, particularly computer systems. These processes include learning, reasoning, problem-solving, and decision-making. AI systems are designed to mimic human cognitive functions and adapt their behavior based on data and experiences, making them well-suited for tackling complex and dynamic challenges.

The Importance of AI in Cybersecurity

AI has brought a paradigm shift in how organizations approach cybersecurity. Here’s why AI is crucial in the realm of cyber defense:

Threat Detection and Prevention

AI algorithms can detect patterns and anomalies within vast datasets that might go unnoticed by traditional security tools. By continuously analyzing data from various sources, AI systems can identify potential security breaches and other incidents in real time, allowing for swift response and mitigation.

Advanced Threat Hunting

AI-powered cybersecurity tools can perform proactive threat hunting by sifting through extensive data to uncover hidden threats. This proactive approach helps identify vulnerabilities before they are exploited.

Behavioral Analysis

AI systems can establish baseline behavior for users and systems, allowing them to detect deviations that might indicate unauthorized activities or intrusions. This behavior-based approach adds an extra layer of defense against sophisticated attacks.

Automation and Efficiency

AI can automate routine security tasks like monitoring logs, analyzing network traffic, and applying security patches. This not only improves efficiency but also reduces the risk of human error.

Adaptive Learning

AI systems learn from past cyber incidents and adapt to new attack techniques. As threat actors evolve their strategies, AI can evolve its defenses to stay ahead of potential threats.

User Authentication

AI can enhance user authentication methods by analyzing behavioral patterns and biometric data, making it more difficult for attackers to impersonate legitimate users.

Other Factors to Consider for Cybersecurity

While AI plays a pivotal role in enhancing cybersecurity, it’s important to consider other factors as well:

Comprehensive Strategy

A robust cybersecurity strategy should encompass technology, processes, and employee training. Each element complements the other to create a holistic defense approach.

Risk Assessment

Understanding your organization’s cybersecurity risks is crucial. Conduct regular assessments to identify vulnerabilities and prioritize areas that need immediate attention.

Regulatory Compliance

Ensure that your cybersecurity measures align with industry regulations and compliance standards. Non-compliance can lead to severe consequences in the event of a breach.

Collaboration

Cybersecurity is a collective effort. Collaborate with industry peers, share threat intelligence, and stay updated on the latest attack trends to better prepare for potential threats.

In conclusion, integrating AI into cybersecurity is transforming how we protect our digital assets. AI’s ability to detect, analyze, and adapt to threats in real-time provides a substantial advantage in combating modern cyber challenges. However, a successful cybersecurity strategy goes beyond technology, involving risk assessment, compliance, and collaboration.

How To Energize The Data Behind AI

November 2, 2022 /

Artificial intelligence (AI) is one of the biggest technology trends of the coming decade. In an increasingly digital world, propagating and collecting data are the default state of modern business and all internet activity. The problem for businesses is no longer the lack of data, but an excess of it. Despite the enormous data available to industrial companies, for most, their AI systems are not delivering the insights that they expected. The solution lies in filtering data so that the right data gets to AI systems. This “smart data” approach will allow AI systems to generate the kind of insights that we have expected. 

What is Smart Data?

AI is a key component of the fourth digital revolution. AI unearths insights from Big Data, insights that no human being could possibly unearth. The more data that AI has, the, the more variables it has, the longer its timescales and the greater its granularity, then, the greater the potential insights that it has.

AI can leverage years of data to discover the optimal parameters for industrial processes using controlling variables. These insights can then be used in these industrial systems to get them to work better than they did before. 

Despite the promise of AI, many industrial companies are yet to see the benefits of propagating and collecting so much information. According to McKinsey, although 75% of industrial companies have tried some kind of AI system, only 15% have enjoyed any meaningful, scalable impact from AI. McKinsey identifies the lack of operational insight into their usage of AI. This approach can be successful, but usually only within very specific parameters, and often with frequent retraining, lots of inputs, and sometimes, it leads to physical or unrealistic results. Therefore, these AI models cannot really be used in the real world or to get the kinds of meaningful change that its users expect. What you get are teams that become frustrated with the system and lose faith in AI.

Smart data is the solution. In order to leverage big data to get the kind of insights that it is expected to get, data has to have fewer variables governed by feature engineering based on first principles. This re-engineering of the data to produce smart data, added to more appropriate training can lead to superior returns of between 5% and 15%.

Smart data has been defined in a number of ways, but the essential features are that it refers to data that has been prepared and organized where it was collected in order for it to be ready and optimized for data analytics of higher quality, speed and insight. 

At a 2018 conference, Donna Ray, then executive director of the U.S. Department of Homeland Security’s Information Sharing and Services Office, said her “teams spend about 80% of their time just searching, ingesting, and getting data ready for analysis”. The smart data approach has helped federal agencies optimize their processes and speed up their operations and make them more intelligent. Wired described smart data as “Smart data means information that actually makes sense”. 

How Do You Generate Smart Data?

Get your Energize the Data! t-shirt out and let’s look at five steps to creating smart data. 

  1. Define the Data

The first step toward creating smart data is defining the process as you would a full coverage painting & flooring project. What this means is that processes must be broken down into clearly outlined steps for the company’s plant engineers and experts, with physical and chemical changes sketched out. The business’ critical instruments and sensors, limits, maintenance timeframes, measurement units, and their controllability must be identified. In physical systems, there are elements of determinism governed by clear equations. These equations must be noted as well as their variables. Teams must also understand the literature around these equations, in order to add to their own understanding.

  1. Enrich the Data

We’ve all heard the expression, “Bad data in, bad data out”, but the reality is, all data is in some sense bad data. Raw process data always has some deficiencies. So, your task is to improve the quality of the dataset, as opposed to increasing the amount of data available. Nonsteady-state information must be weeded out aggressively. 

  1. Reduce the Dimensionality

AI builds models by matching observables to features. In order to get a generalized model, the number of observations must be far in excess of the number of features. Inputs are often combined in order to generate new features. Factoring in the wealth of sensors that the typical plant has, the result is a vast trove of observations. What should be done, however, is to use inputs that describe the physical processes involved, funneled through deterministic equations, to reduce their dimensionality while also creating features that have intelligently combined sensor information. 

  1. Apply Machine learning

Industrial processes have deterministic and stochastic components. First-principle based features supply the deterministic components, and machine-learning the stochastic. Features should be evaluated to assess their importance and explanatory power. The most important, ideally, should be expert-engineered features. 

Plant improvements should be the focus of models, rather than achieving a maximum of predictive accuracy. High correlations are a feature of all process data. Correlations can therefore be meaningless. What is needed is to isolate causal elements and controllable variables.

  1. Implement and Validate Models

In order to actually enjoy the meaningful impact that is expected, models must be implemented. Results need to be continuously assessessed through the examination of key features to see that they match physical processes. Partial dependence plots must also be reviewed so we learn about causality and controllable elements must be confirmed. 

Operations teams must be consulted and made a critical member of the process to better understand what is implementable and what performance expectations make sense. Operators in control rooms need to get model results as they are generated, or teams must conduct on-off testing so that management can determine if it is worth investing capital in full-scale solutions. 

Conclusion

AI has enormous promise and certainly, with the wealth of data that is propagated and collected today, it is counterintuitive to suggest that limits or guard-rails need to be placed around that data. Yet, Big Data often fails to yield meaningful AI insights. Smart data can ensure that AI can deliver the meaningful impact that we expect.

technology-pspl

How Technology Has Changed The Workplace

September 24, 2020 /

Technology seems to advance continually. If anything, it is advancing at an ever-increasing pace. Today it is possible to do many things with the help of technology that was only dreamed in the past. Working from home is more popular than ever before. It is a great idea, especially in the face of Covid 19.

Technology Advancements and Working From Home  


The year 2020 will forever be remembered as the year of the coronavirus pandemic. It will also be seen as a key moment when many jobs began to transition to a work from home model.

Pandemic Response and The Work From Home Movement:
Social distancing is one of the most powerful tools available in response to viral pandemics. Most viral contagions will not spread unless you are near other infected individuals. Working from home allows you to work without putting yourself at any risk.

Video Calls:
You no longer need to be in the same room to have meetings with other people and see them. Video conference calls are becoming increasingly popular in the business world. They allow you to have all the benefits of face-to-face contact without any of the risks.

The Internet:
Thanks to Internet connectivity, you do very few things at work that would be impossible to do at home. It applies to almost all industries.

How to Thrive While Working From Home   


Working from home may sound like a dream come true. However, it would be best if you prepared to encounter some common challenges. Most people have not ever worked from home. Thus, they do not have the experience of social isolation that often accompanies working from home. Here are some things you can do to minimize any negative effects.

Maintain Your Sanity By Minimizing Stress:
It would help if you worked hard to minimize any sources of stress in your life. Social isolation is only compounded when you are stressed about other things. One way that you can reduce your stress is by minimizing your expenditures. Since you are working from home, you will be using more electricity. By switching to a new provider, you will have a lower electric bill.

Set Up a Good Sleep Schedule:
When you work from home, maintaining a regular sleep schedule is essential to success. Disruptions in your sleep schedule can impact every area of your livelihood. One of the best ways we have found to improve the quality of our sleep is blackout curtains. Ambient Light easily disturbs people and disrupts their sleep. Blackout curtains ensure that you can get a full night’s rest.  Blackout curtains also help save energy.   Green Mountain Energy offers competitive electricity rates, and offers a great tool that will help you can see who offers the most best utility rates in your community.

Separate Work and Home Life:
When you are from home, it is difficult to balance your work life with your home life. This is especially true during your initial transition. When you work in an office, you can compartmentalize your work life and separate it from your home life. If you want to succeed when you are working from home, you must do something similar. We recommend creating a specific area of the home and delegating it to work. When you are outside of that room, you should not think about work or do any work. That way, you can maintain a home life and a work-life that are separate from each other.

A Mindset of Abundance in the Modern Economy  


There are so many benefits of working from home; it is difficult to decide which is the best. One of our favorites is the location of independence it gives you. When you are not working in an office, you can move to areas with much lower costs of living. It may not be a raise, but the effect will be the same. At the end of the month, you will have more money in your bank account.

Read More About: 7 Marketing Strategies Every Startup Should Know

Categories

© 2024 PSPL – Proland Software

Theme by Anders Noren — Up ↑