Skip to main content

Embedded System Security


Embedded system security is a strategic approach to protecting software running on embedded systems from attack. An embedded system is a programmable hardware component with a minimal operating system and software.

Embedded systems are designed to perform a dedicated function or functions. Found in consumer electronics, process control systems, aircraft, in-car systems and many other applications, embedded systems need to be extremely reliable. Because of their small size and limited compute resources, however, they can present security challenges for designers and developers.

The firmware in embedded systems can be difficult (or impossible) to update, so in the past, such systems were often designed to have a life cycle of 15 years or more. With the growth of the internet of things (IoT), however, the nature of embedded systems is changing and the number of possible attack vectors is growing exponentially. Today, an embedded system in a smart device can be hacked to take control of everything from smart thermostats to industrial control systems.

Like security in most IT fields, embedded system security requires an end-to-end approach that includes addressing security issues during the design phase. Security considerations should include the cost of an attack on an embedded system, the cost of an attack and the number of possible attack vectors.

To prevent attacks on embedded systems, software developers should:
  • Expect firmware to be updated regularly.
  • Limit access to embedded systems to a need-to-use basis.
  • Provide a way for network administrators to monitor connections to and from embedded systems.
  • Allow integration with third-party security management systems.



Comments

Post a Comment

Popular posts from this blog

Understanding the Evolution: AI, ML, Deep Learning, and Gen AI

In the ever-evolving landscape of artificial intelligence (AI) and machine learning (ML), one of the most intriguing advancements is the emergence of General AI (Gen AI). To grasp its significance, it's essential to first distinguish between these interconnected but distinct technologies. AI, ML, and Deep Learning: The Building Blocks Artificial Intelligence refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions. Machine Learning, a subset of AI, empowers machines to learn from data and improve over time without explicit programming. Deep Learning, a specialized subset of ML, involves neural networks with many layers (hence "deep"), capable of learning intricate patterns from vast amounts of data. Enter General AI (Gen AI): Unraveling the Next Frontier Unlike traditional AI systems that excel in specific tasks (narrow AI), General AI aims to replicate human cognitive abilities across various domains. I...
Post a Comment
Read more

Normalization of Database

Database Normalisation is a technique of organizing the data in the database. Normalization is a systematic approach of decomposing tables to eliminate data redundancy and undesirable characteristics like Insertion, Update and Deletion Anamolies. It is a multi-step process that puts data into tabular form by removing duplicated data from the relation tables. Normalization is used for mainly two purpose, Eliminating reduntant(useless) data. Ensuring data dependencies make sense i.e data is logically stored. Problem Without Normalization Without Normalization, it becomes difficult to handle and update the database, without facing data loss. Insertion, Updation and Deletion Anamolies are very frequent if Database is not Normalized. To understand these anomalies let us take an example of  Student  table. S_id S_Name S_Address Subject_opted 401 Adam Noida Bio 402 Alex Panipat Maths 403 Stuart Jammu Maths 404 Adam Noida Physics Updation Anamoly :  To upda...
Post a Comment
Read more

How to deal with a toxic working environment

Handling a toxic working environment can be challenging, but there are steps you can take to address the situation and improve your experience at work: Recognize the Signs : Identify the specific behaviors or situations that contribute to the toxicity in your workplace. This could include bullying, harassment, micromanagement, negativity, or lack of support from management. Maintain Boundaries : Set boundaries to protect your mental and emotional well-being. This may involve limiting interactions with toxic individuals, avoiding gossip or negative conversations, and prioritizing self-care outside of work. Seek Support : Reach out to trusted colleagues, friends, or family members for support and advice. Sharing your experiences with others can help you feel less isolated and provide perspective on the situation. Document Incidents : Keep a record of any incidents or behaviors that contribute to the toxic environment, including dates, times, and specific details. This documentation may b...
Post a Comment
Read more