Telecommunications System & Management

ISSN: 2167-0919

Open Access

Current Issue

Volume 10, Issue 2 (2021)

    Short Communication Pages: 5 - 5

    Security Operations Center for OT environment ??? A framework


    Operational technology or OT is a category of computing and communication systems to manage, monitor and control industrial operations with a focus on the physical devices (also known as Cyber Physical Devices) and processes being used by these Cyber Physical Devices (or Systems). OT often control essential services which affect people at large, such as water and power supply, oil & gas extraction to supply, mostly all large manufacturing units etc. Additionally, operational technology is also used to monitor these critical services to prevent hazardous conditions. Manipulation of these systems and processes could have extreme impacts on the end users of these services as well as workers within operational environments.Cyberattacks on critical infrastructure and strategic industrial assets are on the rise for some years now and is now believed to be among the top five global cyber risks. The cyberattacks have cost companies millions of dollars through the disruption of services and critical operations. To keep critical systems running and protect the financial results and reputation of any organization that includes industrial processes, it’s essential to improve industrial cyber security. However, securing OT environments, assessing them to determine remediation plans and strategies, and gaining visibility into them is challenging and requires different approaches than traditional IT environments.The IT environment is fairly protected and well-guarded by a Security Operations Center which keeps a constant vigil on the activities of the IT ecosystem under watch. The SOCs across the world have evolved and have reached a certain maturity in operations. However, for an OT environment, the SOC is still a new concept – primarily because the objectives of SOC of OT are different from those of IT. The mission and objectives of newer SOCs of today is about having an integrated security information and event management (SIEM) with a big data platform — complemented by workflow, automation and analytical tool. To create a SOC for OT would require re-engineering some of the OT processes, which because of being heavily dependent on the OT vendors result in a major task.Hence, there is a need to create a framework for OT SOC which helps organizations define a clear mission and objective statement for a fully operational OT SOC. The framework needs to define the roles (give directions) of the SOC team, the MSSP (if any), the OT vendors and the customer.

    Short Communication Pages: 1 - 1

    Cyber security plays an important role in the field of information technology

    Zinedine Sayad

    Cyber security plays an important role in the field of information technology. Securing the information have become one of the biggest challenges in the present day. Whenever we think about the cyber security, the first thing that comes to our mind is ‘cybercrimes’ which are increasing immensely every day. Various Governments and companies are taking many measures in order to prevent those crimes. Besides various measurements are taken seriously to stop the growth of those crimes. Cyber security is still a very big concern to many companies. This paper mainly focuses on the challenges faced by cyber security on the latest technologies. It also focuses on the cyber security techniques, ethics and the trends changing the face of cyber security. This paper will focus on firewalls, intrusion type, encryption and hashing, VPN, attacks, and Security.

    Short Communication Pages: 2 - 2

    Energy Efficiency and Security for Embedded AI: Challenges and Opportunity

    Dr. Muhammad Shafique

    Gigantic rates of data production in the era of Big Data, Internet of Thing (IoT), and Smart Cyber Physical Systems (CPS) pose incessantly escalating demands for massive data processing, storage, and transmission while continuously interacting with the physical world under unpredictable, harsh, and energy-/power- constrained scenarios. Therefore, such systems need to support not only the high-performance capabilities under tight power/energy envelop, but also need to be intelligent/cognitive and robust. This has given rise to a new age of Machine Learning (and, in general Artificial Intelligence) at different levels of the computing stack, ranging from Edge and Fog to the Cloud. In particular, Deep Neural Networks (DNNs) have shown tremendous improvement over the past 6-8 years to achieve a significantly high accuracy for a certain set of tasks, like image classification, object detection, natural language processing, and medical data analytics. However, these DNN require highly complex computations, incurring huge processing, memory, and energy costs. To some extent, Moore’s Law help by packing more transistors in the chip. However, at the same time, every new generation of device technology faces new issues and challenges in terms of energy efficiency, power density, and diverse reliability threats. These technological issues and the escalating challenges posed by the new generation of IoT and CPS systems force to rethink the computing foundations, architectures and the system software for embedded intelligence. Moreover, in the era of growing cyber-security threats, the intelligent features of a smart CPS and IoT system face new type of attacks, requiring novel design principles for enabling Robust Machine Learning.
    In my research group, we have been extensively investigating the foundations for the next-generation energy-efficient and robust AI computing systems while addressing the above-mentioned challenges across the hardware and software stacks. In this talk, I will present different design challenges for building highly energy-efficient and robust machine learning systems for the Edge, covering both the efficient software and hardware designs. After presenting a quick overview of the design challenges, I will present the research roadmap and results from our Brain-Inspired Computing (BrISC) project, ranging from neural processing with specialized machine learning hardware to efficient neural architecture search algorithms, covering both fundamental and technological challenges, which enable new opportunities for improving the area, power/energy, and performance efficiency of systems by orders of magnitude. Towards the end, I will provide a quick overview of different reliability and security aspects of the machine learning systems deployed in Smart CPS and IoT, specifically at the Edge. This talk will pitch that a cross-layer design flow for machine learning/AI, that jointly leverages efficient optimizations at different software and hardware layers, is a crucial step towards enabling the wide-scale deployment of resource-constrained embedded AI systems like UAVs, autonomous vehicles, Robotics, IoT-Healthcare / Wearables, Industrial-IoT, etc.

    2021 Conference Announcement Pages: 3 - 3

    Market Analysis- Cyber Security and Ethical Hacking

    Richard Lynn

    The After the successful completion of artificial intelligence conference series, we are pleased to welcome you to the “Cyber Security and Ethical Hacking." The congress is scheduled to take place on November 18-19, 2021 in the beautiful city of Paris, France. Cybersecurity-2021 Conference will give you exemplary experience and great insights in the field of research.
    Meetings LLC Ltd Organizes 1000+ Conferences Every Year across over USA, Europe, and Asia with assistance from 1000 progressively sensible social requests and Publishes 700+ Open access journals which contain in excess of 100000 well-known characters, assumed scientists as article board people.
    Cyber Security is becoming a crucial driving force behind innovation in robotics and Lot, with a range of advances including Cloud Security & Virtualization, Cyber Crime and Fraud Management, Cyber Vulnerabilities, Incidents, And Mitigations Ethical Hacking and Countermeasures, Future Of Cyber security, Hacking & Hacking Tools. Universities also have begun to offer dedicated Internet of Things programs. Robotics will be getting to be progressively prevalent these times around learners. Actually, if you follow again of the Inception about Artificial Intelligence, you will discover that many technologies likewise have robotics that fills done the individuals minor cracks more successfully Furthermore provides for you a shinier vehicle. There need aid likewise robotics technology items accessible with stay with your eyewear What's more different optical units What's more that's only the tip of the iceberg tough.

    Short Communication Pages: 4 - 4

    Ransomwares: How to build it and how to protect from it

    Sami Fakhfakh

    Ransomware is a type of malware. It restricts access to the computer system that it infects or the data that it stores (often using encryption techniques), and demands a ransom be paid to the creator(s) of the malware. This is in order for the restriction to be removed. Some forms of ransomware encrypt files on the system's hard disk. Others may simply lock the system and display messages intended to persuade the user to pay. Ransomware first became popular in Russia. Now the use of ransomware scams has grown internationally. In June 2013, McAfee said it had collected over 250,000 unique samples of ransomware in the first three months of 2013. This is more than double the number of the previous year. Crypto Locker, a ransom ware worm that surfaced in late-2013, had collected an estimated $3 million USD before it was taken down by authorities. In May 2017, a piece of ransom ware called WannaCry spread around the world. It lasted four days and affected over 200,000 computers in 150 countries.[4] Only about $130,000 (USD) was ever paid in ransom, but the attack affected a lot of large companies and organizations. The United Kingdom's National Health Service (NHS) was hit hard by WannaCry. Hospitals could not access their files, and so many surgeries were cancelled and patients had to be turned away.[5] The NHS was especially at risk because it was using a version of the Windows operating system called Windows XP that Microsoft no longer supported.[6] This meant that Microsoft had not been sending out security updates for this version of Windows, leaving it open to the WannaCry virus. Other systems were affected even though they were running newer versions of Windows, because their users had not yet installed the most recent security updates. Even though it was not designed to actually damage computers or their files, WannaCry led to a lot of wasted time and money, showing how vulnerable the world still is to ransom ware attacks. Nowadays, several companies, organizations or individuals are affected by a ransomware attack. in the philosophy of learning defense by attack. we will explain how this malware works, do a live code review example, test it on live and teach you how to protect yourself from it..

    Volume 10, Issue 3 (2021)

      Editorial Pages: 1 - 1

      Conference Announcement on Artificial Intelligence and Robotics 2021

      Nancy Leo

      We are pleased to welcome you to the “International Conference on Robotics and Artificial Intelligence” after the successful completion of the series of Artificial Intelligence 2020. The congress is scheduled to take place in the beautiful city of Miami, USA on November 12-13, 2021. This Artificial Intelligence 2021 conference will provide you with an exemplary research experience and huge ideas.

      The perspective of the Artificial Intelligence Conference is to set up transplant research to help people understand how treatment techniques have advanced and how the field has developed in recent years.

      Longdom proffers our immense pleasure and honour in extending you a warm invitation to attend Artificial Intelligence 2021 in Miami, USA on November 12-13, 2021. It is focusing on “Innovations and Advancements in Robotics and Artificial Intelligence”, to enhance and explore knowledge among Artificial Intelligence community and to establish corporations and exchanging ideas. Providing the right stage to present stimulating Keynote talks, Plenary sessions, Discussion Panels, B2B Meetings, Poster symposia, Video Presentations and Workshop Artificial Intelligence anticipates over 200 participants around the globe with path breaking subjects, discussions and presentations. This will be a splendid feasibility for the researchers, delegates and the students from Global Universities and Institutes to interact with the world class scientists, speakers, Analyst, practitioners and Industry Professionals.

      Longdom all the experts and researchers from the Robotics and Artificial Intelligence sector all over the world to attend “International Conference on Robotics and Artificial Intelligence (Artificial Intelligence 2021) which is going to be held on Miami, USA on November 12-13, 2021. Artificial Intelligence 2021 conference includes Keynote presentations, Oral talks, Poster Presentations, Workshops, and Exhibitors.

      The most other engineering majors work with Artificial Intelligence, but the heart of Artificial Intelligence is Automation and Automation Engineering across all the disciples.  Artificial Intelligence 2021 conference is also comprised of Best Post Awards, Best Oral Presentation Awards, Young Researchers Forums (YRF) and also Video Presentation by experts.  We are glad to welcome you all to join and register for the “International Conference on Robotics and Artificial Intelligence” which is going to be held in Miami, USA on November 12-13, 2021.

      Short Communication Pages: 2 - 2

      AI-based vehicle analytics for smart cities

      Venkatesh Wadawadagi

      Improving cities is a pressing global need as the world’s population grows and our species becomes rapidly more urbanized. In 1900 just 14 percent of people on earth lived in cities but by 2008 half the world’s population lived in urban areas. Today, 55% of the world’s population lives in urban areas and this percentage is expected to rise to 68% by 2050.

      The use of artificial intelligence in smart cities can be life-changing if implemented in the right spaces. There are multiple zones in cities or in urban development where AI can be used to improve the performance and efficiency of the system. AI has the ability to understand how cities are being used and how they are functioning. It assists city planners in comprehending how the city is responding to various changes and initiatives. AI with the help of Deep Learning and Computer Vision has changed the way vehicle analytics is done. With these advancements, vehicle analytics is helping in implementing intriguing solutions like Toll booth automation, Smart parking, Gate security, ATCS (Adaptive Traffic Control System), RLVD (Red Light Violation Detection) etc. This talk starts by briefing about what's AI based vehicle analytics and what all it includes, and goes on to talk about varieties of applications of vehicle analytics including implementation and deployment challenges. Towards the end talk focuses on why it's need of the hour for this populated, industrialised and tech-driven era.

      Short Communication Pages: 3 - 3

      Artificial Intelligence: Technology Applied on Criminal Justice

      Selma Elizabeth Blum

      Technology has become an essential aspect of law enforcement routine, helping police officers on solving, preventing and even predicting criminal activity globally. Artificial Intelligence is one of many important tools police can rely on. The harmonic integration between men and machine is now an essential part for operations success on security enforcement. How artificial intelligence can address criminal justice needs? Which innovations we have available to improve public safety? This article will demonstrate how artificial intelligence (AI) has became a major resource in numerous ways. It is now the ultimate solution for criminal justice, based on big data, algorithmics and machine learning to detect different patterns on human behavior. Those solutions are mainly based on pattern identification, image scanning, face recognition, sociodemographic analysis, voice parameters, actions, conducts, movements, biometrics and even emotions acknowledgement, which are now being considered an excellent evidence for deception detection, fraud, violence and terrorists acts. It is also used on DNA documentation, ballistics and profiling. Unlike humans, machines do not tire. On the opposite, it is proven on several ways, to be better than humans. It is confirmed machines are very good on identifying anomalous patterns and learning new patterns faster than humans. AI technologies provide the capacity to detect, predict and evaluate, overcoming errors and present virtuous results. The more amount of data, more precise will be the outcome. AI algorithms can potentially be used as a very efficient observer, increasing the accuracy of police officers on their complex daily routine. Predictive analysis (ex. PREDPOL) is one of many examples we will show to demonstrate how important those solutions subsist and innovate the security context. Those systems process large volumes of information simultaneously, providing precise outcomes. This article will deeply investigate and compare several platforms used by different law enforcement units around the globe, pointing new solutions, challenges and potential developments needed. As a conclusion, we have noticed how important was the introduction of AI on law enforcement routine, performing risk evaluations, crime solutions and delinquency prevention.

      Short Communication Pages: 4 - 4

      How to accelerate AI in Banks

      Ramin Mobasseri

      With the exponential rise of AI usage in Banks, many financial organizations are still struggling with building efficient Model Development Life Cycles (MDLC) and the means to expedite business value realization and return of investment (ROI). There are several contributing factors which can give rise in less than optimal MDLC, such as, lack of proper data governance and processes around it as well as lack of performant AI solutions and platforms.

      In this session, you will learn how to use most essential business value accelerators (BVA) to expedite Data Science Discovery, Data Ingestion, and Model Development leading to most optimal Model Business integration. This session will provide lots of valuable and real to life strategies and executable plans to help reduce your MDLC and time to market by at least 50%

      Sections will include but not limited to:

      -               Overview of AI Acceleration in highly regulated environments

      -               Effective use of tools and processes in each phase of MDLC

      -               Hints and Tips on building effective meta use cases with the lines of businesses, e.g. Fraud, Anti Money Laundering amongst many others

      -               Agile Blueprints for Machine Learning (ML) and Natural Language Processing (NLP)

      -               Effective Data Governance Policy and Strategy

      Short Communication Pages: 5 - 5

      Artificial Intelligence-based deep learning techniques for anomaly detection in IoT using the latest IoT23 by Google's Tensorflow2.2


      Although numerous profound learning models had been proposed, this research article added to symbolize the investigation of significant deep learning models on the sensible IoT gadgets to perform online protection in IoT by using the realistic Iot-23 dataset. It is a recent network traffic dataset from IoT appliances. IoT gadgets are utilized in various program applications such as domestic, commercial mechanization, and various forms of wearable technologies. IoT security is more critical than network security because of its massive attack surface and multiplied weak spot of IoT gadgets. Universally, the general amount of IoT gadgets conveyed by 2025 is foreseen to achieve 41600 million. So we would like to conduct IoT intrusion and anomaly detection systems of detecting IoT-based attacks by introducing various deep learning models on artificial neural networks such as Recurrent Neural Networks, Convolutional  Neural Networks, Multilayer Perceptron, Supervised GAN Adversarial Network, etc in both binary and multiclass classification modes in IoT- cybersecurity. We generate wide performance metric scores such as Accuracy, false alarm rate, detection rate, loss function, and Mean Absolute error.

      Short Communication Pages: 6 - 6

      Investigation on Prediction Systems based on LSTM ???prediction for dissolved oxygen (DO) in water

      Hsuan-Hsuan Chao

      Climate change and industrial development have brought greater uncertainty to water resources, and the quality of water has a very significant impact on humans and the entire ecosystem. The current water quality testing relies on the data collected by various monitoring systems, some of which are not immediately available or require more expensive equipment to analyze. Most experts agree that the amount of dissolved oxygen (DO) in the water is the main indicator for judging the quality of water. However, the process of obtaining information is more complicated and cumbersome. If the difficulty of obtaining the information can be simplified, it will make water resources better. Management is more efficient.

      In recent years, artificial intelligence is often developed to assist in many complex decision-making tasks. We develop a prediction model based on LSTM. We design a machine learning model and provide a large amount of data to make it find the rules and learn from it. Improve the predictive ability of the model. Through the model, the water quality can be monitored and analyzed, and the data obtained can be used to judge and predict the water quality state and deal with water pollution problems in time.

      Short Communication Pages: 7 - 7

      Artificial Intelligence in Cyber Security for Industry 4.0

      Farah Jemili

      The recent White House report on artificial intelligence (AI) highlights the importance of AI and the need for a clear roadmap and strategic investment in this area. As AI emerges from science fiction to become the frontier of world-changing technologies, there is an urgent need to systematically develop and implement AI to see its real impact in the next generation of industrial systems, known as Industry 4.0. This article provides an overview of the current state of AI in industrial applications and offers our contribution to the deployment of AI in cybersecurity for Industry 4.0.

      Volume 10, Issue 4 (2021)

        Short Communication Pages: 1 - 1

        Intelligent Healthcare

        Sergio Mastrogiovanni*

        In 2020, COVID-19 exposed the fragility of health sector. In the US in particular, the most expensive healthcare system in the world, it also faces a tremendous challenge in responding to diagnostic needs. One of the biggest challenges in medical imaging like MRI is not the high cost per se, but the capacity. An MRI session lasts between 15 and 60 minutes. There are hospitals with only one device or even no one. Medical imaging is one of the best use cases for AI in healthcare, but lack of physician engagement and data bottlenecks can make the technology less useful than promised. When used to decode the complicated nature of MRIs, CT scans, and other testing modalities, advanced analytical tools have proven their ability to extract meaningful information to improve decision-making, sometimes with greater precision than humans themselves. . With deep learning, it is possible to capture less data and thus scan faster, while preserving or even enhancing the rich information content of MRI images. The key is to train artificial neural networks to recognize the underlying structure of the images in order to fill in the missing views from the accelerated scan. This approach is similar to how humans process sensory information. When we experience the world, our brains often receive an incomplete image, as in the case of darkened or dimly lit objects, that we need to convert into actionable information.

        Short Communication Pages: 2 - 2

        Deep Learning and Crop Inspection: Bigger Yields, Better Harvests and Safer Crops

        George Kantor

        Since the dawn of agriculture, crop monitoring and inspection remains a mainstay of every farmer’s routine. Today, many farmers visually inspect their crops armed with a variety of tools to help ensure ideal plant health and performance. Although human visual inspection remains an essential part of agriculture, it has many challenges and many limitations. Research over the last decade or so has assessed the applicability of computer vision and deep learning to address the crop inspection challenge [Nusk2011, Nusk2014, Blom2009, Herr2015]. These approaches have shown tremendous promise, they are only just now beginning to go beyond the research phase into commercialization. Around 2015, image processing methods using deep neural networks began to replace the earlier classical computer vision approach, providing both better performance and more generalizable results. Again, through the early work of the CMU team, a StalkNet [Bawe2018] architecture was developed, which combines an RCNN feature detector with a GAN based pixel segmenter. To date, StalkNet has been trained to measure dozens of widely varying features in different crops, ranging from leaf necrosis to fruit ripeness to sorghum seed size for grain yield. The first market Bloomfield has chosen to address is grape growing and vineyard inspection, but we see CEA as a natural next step in the progression of our technology and a large opportunity. Flash combines highresolution flash lighted stereo RGB images with a cloud-based deep learning pipeline to inspect and assess the health and performance of each and every plant in a field or grow, one plant at a time. The result, so far, with Bloomfield’s vineyard customers is yield estimation, pest/disease detection, labor saving and digitalization. This comprehensive analysis forms the foundation for Bloomfield’s health and performance assessment of each geolocated plant, one plant at a time through a web-based dashboard accessible via tablet, cellphone or computer. Bloomfield’s approach to inspecting and assessing plants contrasts sharply with the visual inspection which includes sparse subjective judgements of randomly sampled plant data.

        Short Communication Pages: 3 - 3

        Neural Network based Prediction in Recommender

        Karishma Nanda

        This paper aims to contribute to the cold start problem in recommender system with Neural Network based approach. There are several attempts in academia and in the industry to improve the recommender system. For instance, latent matrix factorization is an algorithm that solves the recommendation problem, it produces efficient outcomes from the core problem. Latent factors are not directly observed but are inferred from other factors. It can be computed by assuming a specific number of such factors and then transforming the large user-item matrix into a smaller matrix based on previously assumed factors. These smaller matrices can be multiplied to reproduce a close approximation to the original user-item matrix using a technique called matrix factorization. Assuming that the matrix can be written as the product of two low-rank matrices, matrix factorization techniques seek to retrieve missing or corrupted entries. Matrix factorization approximates the matrix entries by a simple fixed-function — namely, the inner product — acting on the corresponding row and column latent feature vectors. Substituting a neural architecture for the inner product that learns from the data, improves recommendation problem and deals with the cold start problem

        Short Communication Pages: 4 - 4

        The Lack of Love and Iron, The two causes of Alzheimer???s

        Joan Manuel Rodriguez Nunez

        Objective: By the lack of initiative by force (Faith) Iron man lives. Iron defi ciency causes anemia, anemia causes dementia, Alzheimer dementia and Alzheimer’s produces cognitive impairment in memory produces bases. Well hear him. The Iron Will Alkaline, the answer is yes. Methodology: On the basis of Love and the use of Iron and its allies, which are the B vitamins, Vitamin C, E and vitamin A. It is necessary to remember that there is to try to fi ght the greatest sustenance Anemia in all its contrarestantes. Conclusion: The theory focuses on the oxygenation of the blood, which must be done, where the Warburg Alkaline Diet is demonstrated, among other factors it is necessary to emphasize the oxygenation that consists of the mental and physical, which is reduced in Sleeping correctly, Warburg Alkaline Diet, Drink Enough Water, Make Walks or Moderate Exercises, Comfort and Drink Iron, Vitamin C, Vitamin E, Complex B and Vitamin A. All this consists in Producing New Oxygen.

        Short Communication Pages: 5 - 5

        A Hybrid Convolutionary Neural Network and Low-rank Tensor Learning Algorithm for Tensor-on-Tensor Regression

        Affan Shoukat

        The problem of predicting a set of tensorial outputs based on inputs of tensor form has been receiving increasing attention in recent years. This problem arises in various areas of mathematical, statistical and computational sciences, and generalizes the case of the widely used scalar-on-scalar regression methods. In this paper, we develop a tensor-on-tensor re gression framework using a hybrid of convolutionary neural networks and lowrank tensor learning algorithms. Our proposed framework integrates several promising approaches which have been developed previously to tackle this problem and extends their domain of applica tions. In particular, we demonstrate the advantage of this framework in comparison with traditional methods through an example of predicting the third-order tensors which arises within the procedures required for performing the time-homogeneous top-K ranking algo rithm. Computational results are further provided which pertain to analysis of the U.S. stock market during the time period from January 1990 to December 2019

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