Day: February 26, 2023

The physical security industry has been changing quickly in recent years. Developments and applications of cutting-edge technologies in this ever-evolving industry such as AI, machine perception, and IoT, are breaking boundaries all the time. We have seen security systems become deeply integrated and more comprehensive, expanding with capabilities that are now shouldering more intelligent tasks to improve efficiency in security as well as other operational functions. And all this is happening across many different industries and types of organizations. As we step into 2023, Hikvision would like to share some insights into seven key trends coming to the fore in the security industry. AI applications are diversified, requiring more open ecosystems We have seen more diversified AI products and applications that help solve intricate problems daily and meet customers’ fragmented needs. AI’s acoustic and textual capabilities are also being explored by the industry, beginning with visual AI. For example, AI-powered audio anomaly detection is being used to detect equipment failures in industrial environments for heightened levels of worker safety. Furthermore, AI technology itself is evolving to the stage of self-learning with training and optimizing itself much faster than supervised learning. All of these require more ecosystems with open technologies, open resources, and even open protocols, for collaborations in the industry. Open technologies such as container technology and virtualization technology, have significant potential for our industry, which are making hardware products more open. AIoT continues to bridge physical and digital worlds Taking artificial intelligence further, we believe the combination of AI and IoT (AIoT) will continue to be a major trend for 2023, reshaping the scope of the security industry. More AIoT solutions have been introduced that will not only provide intelligent protections but also help advance the efficiency of operations in a multitude of industries and organizations. AIoT will create an important path for boosting digital transformation across several industries. This can be done by creating a digital twin, bridging the physical and digital worlds. For example, in industrial park management, virtual sites can be created by applying 3D modeling, using VR and AR technologies to represent and reflect the real ones, empowering them with the dynamic insight to act quickly to make the whole site run smoothly. Visual experiences improve with 24/7 imaging technologies Capturing security imaging with sharp clarity and color around the clock is a core demand for users of video security, but dim light at night has always been the biggest challenge to achieving this. Now, with the development of several new imaging technologies, we are seeing these challenges removed. Bi-spectrum image fusion technology that employs two sensors is being used to combine IR and visible-light imaging to reproduce vivid colors in dim lighting conditions. Artificial Intelligence-based image signal processing (AI-ISP) technology leverages deep-learning algorithms to radically improve visual noise reduction for nighttime image optimization. Perception capabilities extend to a wider range For security applications, perception capabilities are going far beyond visible light, extending out along the electromagnetic spectrum to expand capabilities of perceiving the physical world in new ways. For instance, hyperspectral imaging technology has been used in analyzing optical irradiance characteristics and eutrophication to record water quality trends in rivers and lakes. In the millimeter-wave band, radar products are assisting the measurement of vehicle speeds and distances. The X-ray band has been applied widely in security inspections, now extending its applications in industrial equipment flaw detection. And these multi-dimensional perception capabilities also converge to create innovative solutions that can accomplish a multitude of new operations such as radar assisted video systems for perimeter protection, integration solutions of video and sonar arrays for traffic management, and alarm systems with a wide range of detectors for smart home applications. More focus on usability of devices and systems Usability of devices and systems impacts the daily life of security professionals, which has generated more focus now in light of workforce shortages and labor cost increases across our industry. This trend is requiring manufacturers to optimize their products with an easier configuration process, make better use of interactive experiences that will reduce installation time, and lower the costs of equipment maintenance and skill building. For example, we see more installers preferring to use mobile applications over PCs in device installation and maintenance where that interactive and simplified process comes across best. The industry moves to greener, lowercarbon operations for sustainability Trends in green manufacturing and low-carbon initiatives in the security industry are very inspiring. Security manufacturers are rolling out products featuring longer life expectancies, recyclable materials and packaging, and renewable energy usage. Each of these initiatives reduces waste and emissions. For example, the solar-powered camera demand continues to increase due to its well-established effectiveness at using the sun’s limitless clean energy. And in daily manufacturing and operations, more companies in the industry have set medium-to-long-term goals for environmental management, spanning from lower carbon production, efficient energy use, and waste and chemical management, to greener office environments. Zero Trust continues to become the go-to cybersecurity strategy Cybersecurity remains a very important and challenging issue for all parties in our industry, as customers and regulators get more concerned about the security of their data and privacy, and have set higher standards and demands on this issue. We see the value in highlighting the idea of Zero Trust for everyone to consider when making cybersecurity strategies. Zero Trust is a strategic initiative that was developed to prevent data breaches by eliminating the concept of trust from an organization’s network architecture. In cybersecurity, trust becomes a vulnerability. Zero Trust is an approach to cybersecurity that dictates our connected systems must ‘never trust; always verify.’  

Prakash Prabhu – Chief Business Officer & Co-Founder, VisionBot In this feature, we will navigate how automated visual inspection, content analysis and deep learning methodologies can save significant time and effort for organized retail and warehousing enterprises. Computer Vision Driven Automated Video Content Monitoring For Retail Augmented computer vision is a game-changer for the retail industry. By adding layers of digital information to the real world, retailers can create engaging and personalized experiences for their customers, resulting in increased sales and customer loyalty. Computer vision is a type of technology that is revolutionizing the way that we think about retail. By using machine learning algorithms, computer vision is able to ‘see’ the world around us and make sense of it in ways that were previously impossible. With its ability for automated visual monitoring in real-time, it provides insights into customer behaviour, shelf management, merchandising, inventory & visitor analytics to name a few, and has become an essential tool for retailers who want to understand their customers better, deliver a more personalized shopping experience and bring more efficiency in their operations. In this editorial, we will explore some of the most promising use cases of computer vision in retail, and how they are already transforming the industry. Smart shelves One of the most exciting applications of computer vision in retail is the development of smart shelves. These shelves are monitored by cameras that can detect when products are running low and automatically raise an alert to reorder them. This not only saves time and resources, but it also ensures that customers always find what they are looking for. Smart shelves can also be used to analyse customer behaviour. By tracking which products are most frequently picked up or put down, retailers can gain valuable insights into what customers are looking for and adjust their inventory accordingly. This kind of real-time data can be used to optimize product placement, pricing, and promotions. In-store navigation Navigating a large store can be a daunting task, especially for customers who are not familiar with the layout. Computer vision technology can help with this problem by providing real-time maps and product locators that help customers find the products they are looking for quickly and easily. In-store navigation also offers opportunities for retailers to personalize the shopping experience. By tracking a customer’s movements through the store and analysing dwell times, retailers can make targeted recommendations about products that they might be interested in through instore promotions. Real-time analytics Perhaps the most significant advantage of computer vision technology in retail is its ability to provide real-time analytics. By analysing customer behaviour and preferences in real-time, retailers can make data-driven decisions about pricing, product placement, and marketing. Computer vision can be used to collect valuable data on customer behavior such as which products they are looking at, how long they spend in the store, and which displays they interact with the most. This data can be used to make informed decisions on store layout, product placement and promotions. Retailers can also use computer vision to analyze customer demographics such as age and gender, to better tailor their products and services to their target market. Checkout & payment The checkout process is often a pain point for both customers and retailers. Long lines and slow checkout times can lead to frustrated customers and lost sales. Pilferages can be reduced at the self-checkout counters, by flagging suspicious transactions. Inventory management Managing inventory is a crucial aspect of retail operations. Computer vision can help retailers track inventory levels and identify which products are running low or out of stock. By using cameras installed in the store, computer vision algorithms can detect which products are being picked up by customers and which shelves are running low. This information can be used to automate the reordering process, ensuring that the store always has sufficient inventory levels. Security Security is a major concern for retailers, and computer vision can help improve safety and prevent theft. Cameras equipped with computer vision algorithms can detect suspicious behavior such as someone trying to remove a security tag or hiding a product in their bag. This information can be sent to store personnel in real-time, allowing them to take appropriate action to prevent theft. Computer Vision Driven Automated Video Content Monitoring For Warehousing Warehousing and logistics are essential components of the supply chain for any industry. The rapid growth of e-commerce has led to an increased demand for faster, more efficient, and cost-effective warehousing and logistics solutions. Computer vision technology is playing a significant role in transforming the industry by enhancing operational efficiency, reducing costs, and improving customer satisfaction. In this editorial, we will explore some of the key use cases of computer vision in warehousing and logistics. Monitored picking and sorting Picking and sorting products is a critical process in the warehousing and logistics industry. Computer vision can be used to automate this process, reducing labour costs and improving efficiency. With cameras and machine learning algorithms, computer vision can detect and identify products, sort them, and place them in the appropriate storage location. This technology can also be used to optimize the picking process by identifying the fastest route to collect items and reducing errors. Inventory management Inventory management is a critical aspect of warehousing and logistics. Accurate inventory management ensures that the right products are available at the right time, reducing delays and improving customer satisfaction. Computer vision can help automate inventory management by scanning barcodes or using image recognition to identify products, track their location, and monitor their quantity. This technology can also be used to optimize storage space, ensuring that products are stored in the most efficient way possible. Quality control Quality control is an essential aspect of the warehousing and logistics industry. Computer vision can be used to detect defects or damage to products, ensuring that only high-quality products are shipped to customers. With cameras and machine learning algorithms, computer vision can identify flaws or inconsistencies in products, and alert workers to take…

Iqbal Singh, Founder, Forces Network Introduction With increasing digitization and automation the surface area for attack for cyber criminals has increased exponentially. Cybercrime is on the rise and jobs in digital or computer forensics are in great demand. It is a branch of digital forensic science. Using technology and investigative techniques, digital forensics helps identify, collect, and store evidence from an electronic device. Digital forensics can be used by law enforcement agencies in a court of law, or by businesses and individuals to recover lost or damaged data. The goal of computer forensics is to perform a structured investigation and maintain a documented chain of evidence to find out exactly what happened on a computing device and who was responsible for it. It essentially involves data recovery with legal compliance guidelines to make the information admissible in legal proceedings. The terms digital forensics and cyber forensics are often used as synonyms for computer forensics. Digital forensics starts with the collection of information in a way that maintains its integrity. Investigators then analyze the data or system to determine if it was changed, how it was changed and who made the changes. The use of computer forensics isn’t always tied to a crime. The forensic process is also used as part of data recovery processes to gather data from a crashed server, failed drive, reformatted operating system (OS) or other situation where a system has unexpectedly stopped working. Businesses also use computer forensics to track information related to a system or network compromise, which can be used to identify and prosecute cyber attackers. Businesses can also use digital forensic experts and processes to help them with data recovery in the event of a system or network failure caused by a natural or other disaster. Typically they investigate security breaches on a computer system, network, website, or database to find out how they occurred, endeavour to retrieve lost files, and repair damaged data while strengthening the security system to prevent reoccurrence. Where Do They Work?  Many computer forensic investigators work within the law enforcement industry, whether directly for law enforcement agencies or for private firms hired by agencies to manage digital evidence. It’s also possible to work as a forensic analyst for a private company. In this case, you’re likely to be tasked with identifying vulnerabilities, investigating breaches, and attempting to retrieve data from damaged or compromised digital storage devices. Some digital forensic investigator jobs require you to be on call to respond to incidents that might not occur during regular business hours. You can also work as a freelancer in this domain. See the profiles of typical freelancers billing in a range from $20- $200 per hour. Salary. Digital forensic analysts in the US make an average base salary of $74,575, according to Glassdoor, as of December 2022. Job sites ZipRecruiter and CyberSeek report salaries of $73,271 (computer forensic investigator) and $100,000 (cyber crime analyst), respectively.\\ Job openings. To get a feel of the kind of job openings, take a look at indeed website for such roles. Types of Digital Forensics There are various types of computer/ digital forensic examinations. Each deals with a specific aspect of information technology. Some of the main types include the following: Database Forensics.The examination of information contained in databases, both data and related metadata. Email Forensics.The recovery and analysis of emails and other information contained in email platforms, such as schedules and contacts. Malware Forensics.Sifting through code to identify possible malicious programs and analyzing their payload. Such programs may include Trojan horses, ransomware or various viruses. Memory Forensics. Collecting information stored in a computer’s random access memory (RAM) and cache. Mobile Forensics. The examination of mobile devices to retrieve and analyze the information they contain, including contacts, incoming and outgoing text messages, pictures and video files. Network Forensics. Looking for evidence by monitoring network traffic, using tools such as a firewall or intrusion detection system. How Does Computer Forensics Work? Forensic investigators typically follow standard procedures, which vary depending on the context of the forensic investigation, the device being investigated or the information investigators are looking for. In general, these procedures include the following three steps: Data Collection. Electronically stored information must be collected in a way that maintains its integrity. This often involves physically isolating the device under investigation to ensure it cannot be accidentally contaminated or tampered with. Examiners make a digital copy, also called a forensic image, of the device’s storage media, and then they lock the original device in a safe or other secure facility to maintain its pristine condition. The investigation is conducted on the digital copy. In other cases, publicly available information may be used for forensic purposes such as Facebook posts or public Venmo charges for purchasing illegal products or services displayed on the Vicemo website. Analysis. Investigators analyze digital copies of storage media in a sterile environment to gather the information for a case. Various tools are used to assist in this process, including Basis Technology’s Autopsy for hard drive investigations and the Wireshark network protocol analyzer. A mouse jiggler is useful when examining a computer to keep it from falling asleep and losing volatile memory data that is lost when the computer goes to sleep or loses power. Presentation. The forensic investigators present their findings in a legal proceeding, where a judge or jury uses them to help determine the result of a lawsuit. In a data recovery situation, forensic investigators present what they were able to recover from a compromised system. Often, multiple tools are used in computer forensic investigations. A researcher at Kaspersky Lab in Asia created an open source forensics tool for remotely collecting malware evidence without compromising system integrity. Techniques Used By Forensic Investigators Investigators use a variety of techniques and proprietary forensic applications to examine the copy they’ve made of a compromised device. They search hidden folders and unallocated disk space for copies of deleted, encrypted or damaged files. Any evidence found on the digital copy is carefully documented in a finding report and verified with the original device in preparation for legal proceedings that involve…