SEATTLE (PRWEB) January 22, 2021
Digital.com, a leading independent review website for small business online tools, products, and services, has announced the best business security systems of 2021. The top platforms were evaluated based on core features and customer feedback.
All solutions were required to support integration with video surveillance, video storage, and remote access to real-time video feeds. Experts at Digital.com also selected platforms that provide email and push notification alerts so that business owners or staff are immediately updated about security issues. It was also critical for each platform to offer 24/7 smoke and carbon monoxide detection.
“This guide was developed to help small business owners find the most reliable business security systems with wireless technology, automation, and other must-have features,” says Christelle Feniza, Communications Manager of Digital.com.
Digital.com’s research team conducted a 40-hour assessment of over 20 solutions across the web. To access the complete list of best business security systems, please visit https://digital.com/business-security-system/.
Best Business Security Systems of 2021
Digital.com reviews and compares the best products, services, and software for running or growing a small business website or online shop. The platform collects twitter comments and uses sentiment analysis to score companies and their products. Digital.com was founded in 2015 and formerly known as Review Squirrel. To learn more, visit https://digital.com/.
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What is Cyber Threat Intelligence?
We bring out the hidden knowledge treasure inside seasoned professionals through byte sized content
Cyber threats aimed at business are identified by Threat Intelligence. IT specialists and complex tools can read and analyze the threats. This information is utilized to plan, forestall, and recognize cyber threats hoping to exploit important organization’s assets. Threat Intelligence collects and compiles the raw data about the threats emerging from different sources.
People often get confused with Cyber Security terms such as Threat Intelligence and Threat Data. Threat data is a list of likely threats. For instance, Facebook feeds are like a running list of possible issues. It is Threat Intelligence when IT specialists and exclusive complex tools can read and analyze the threats/attacks.
Why is threat intelligence important for businesses?
Threat Intelligence is a vital part of any cybersecurity. A cyber threat intelligence program sometimes called CTI, can:
1. Prevent data loss
With a very much organized CTI program set up, your organization can spot cyber threats and keep data breaches from leaking critical information.
2. Give guidance on security measures
By distinguishing and dissecting threats, CTI spots designs utilized by hackers. CTI assists organizations with setting up security standards to protect against future cyber assaults and threats.
3. Educate others
Hackers are smarter than before. To keep up, cybersecurity specialists share the strategies they’ve seen with the IT people group to make a communal database to battle cybercrimes and cybersecurity threats.
4. Kinds of Threat Intelligence
The four kinds of threat intelligence are strategic, tactical, technical, and operational.
5. Strategic cyber threat intelligence
Strategic cyber threat intelligence is generally dedicated to a non-technical audience. It utilizes nitty-gritty analyses of patterns and arising threats to make an overall image of the potential results of a cyberattack. A few examples are whitepapers, policy documents, and in-house publications.
Tactical threat intelligence gives more details on the threat actors’ tactics, techniques, and procedures, known as TTP. It is especially intended for a technical audience and encourages them to see how their organization may be assaulted based on the most recent techniques attackers use to achieve their goals. They search for Indicators of Compromise (IOCs) proof like IP locations, URLs, and systems logs to use to help identify future data breaches. Strategic, proof-based threat intelligence is typically dedicated to security groups or people engaged in network security services.
Technical threat intelligence centers around the technical hints of cybersecurity threats similar to the titles to phishing messages or false URLs. This kind of threat intelligence is significant as it gives individuals a clue of what to search for, which as a result is helpful for social engineering attacks. Nonetheless, since hackers switch up their strategies, methods, and systems often, technical threat intelligence has a short life of realistic usability.
Operational threat intelligence relates to threats uncovered before they happen. Threat intelligence is more of spy stuff like getting into hacker chat rooms. Operational threat provides information much before the threat or attack occurs.
All things considered, all aspects of cyber threat knowledge are vital for an extensive threat review and assessment. Cyber threat knowledge can help associations obtain important information about these threats, build successful defense equipment and relieve the threats that could harm their reputation.
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Smart payment solutions make their way in Mexico
Paymentology and partner Intercash are launching tailor-made card issuing solutions for the digitally savvy in Mexico.
The market opportunity for FinTech in Latin America is growing year on year. The region has been able to adapt quickly to emerging technologies as payment security and financial inclusion is low. Banks are looking at newer technologies to help bridge this gap.
Mexico is in a great position as it has the highest rate of smartphone penetration in Latin America and over 45% of transactions are done by card. The country represents an exciting opportunity for FinTechs looking to offer smart payment solutions with easy-to-use functionality.
Following recent recognition by Latin America’s financial-transaction-network, PROSA, Intercash, a global payments solutions provider, and Paymentology, a leading issuer payments processor, today announced the launch of innovative card issuing solutions in Mexico to serve the growing volume of card transactions.
The partnership will see Intercash’s customers benefit from the ability to launch innovative payment solutions almost instantly with unrivalled access to data. Furthermore, this access to data at point-of-sale will empower Intercash’s customers to offer innovative real-time payment options that are personalised and meet the demands of today’s digital savvy consumer.
Using Paymentology’s cloud-native platform and PayRule.AI engine, customers will be empowered to shape consumers’ behaviour and preferences, key in today’s customer-first world. It is powered by augmented intelligence functionality which advances the authorisation process of consumer spends on credit and debit cards. Intercash’s customers will gain access to consumer spend data including transaction history retrieval, as well as a granular card scheme fee breakdown. The engine goes as far as retrieving and analysing mid-flight full card history for the approval or decline of transactions.
Shane O’Hara, CEO of Paymentology said, “We are excited to be collaborating with Intercash to help bring the latest customer-first payment solutions to Mexico, allowing millions of people the opportunity to make convenient, fast and secure payment transactions.”
Aaron Gladman, CEO of Intercash’s Card Division added, “Banks and government institutions are now looking to technology for finance and security solutions. We are delighted to be partnering with Paymentology for our initiative in launching turn-key card issuing and card management solutions into the Mexican market.
Convergence of AI, 5G and Augmented Reality Poses New Security Risks
By John P. Desmond, AI Trends Editor
Some 500 C-level business and security experts from companies with over $5 billion in revenue in multiple industries expressed concern in a recent survey from Accenture about the potential security vulnerabilities posed by the pursuit of AI, 5G and augmented reality technologies all at the same time.
To properly train AI models, for example, the company needs to protect the data needed to train the AI and the environment where it is created. When the model is being used, the data in motion needs to be protected. Data cannot be collected in one place, either for technical or security reasons, or for the protection of intellectual property. “Therefore, it forces companies to insert safe learning so that the different parties can collaborate,” stated Claudio Ordóñez, Cybersecurity Leader for Accenture in Chile, in a recent account in Market Research Biz.
Companies need to extend secure software development practices, known as DevSecOps, to protect AI though the life cycle. “Unfortunately, there is no silver bullet to defend against AI manipulations, so it will be necessary to use layered capabilities to reduce risk in business processes powered by artificial intelligence,” he stated. Measures include common security functions and controls such as input data sanitization, hardening of the application and setting up security analysis. In addition, steps must be taken to snake data integrity, accuracy control, tamper detection, and early response capabilities.
Risk of Model Extraction and Attacks on Privacy
Machine learning models have demonstrated some unique security and privacy issues. “If a model is exposed to external data providers, you may be at risk of model extraction,” Ordóñez warned. In that case, the hacker may be able to reverse engineer the model and generate a surrogate model that reproduces the function of the original model, but with altered results. “This has obvious implications for the confidentiality of intellectual property,” he stated.
To guard against model extraction and attacks on privacy, controls are needed. Some are easy to apply, such as rate limitations, but some models may require more sophisticated security, such as abnormal usage analysis. If the AI model is being delivered as a service, companies need to consider safety controls in place in the cloud service environment. “Open source or externally generated data and models provide attack vectors for organizations,” Ordóñez stated, because attackers may be able to insert manipulated data and bypass internal security.
Asked how their organizations are planning to create the technical knowledge needed to support emerging technologies, most respondents to the Accenture survey said they would train existing employees (77%), would collaborate or partner with organizations that have the experience (73%), hire new talent (73%), and acquire new businesses or startups (49%).
The time it takes to train professionals in these skills is being underestimated, in the view of Ordóñez. In addition, “Respondents assume that there will be vast talent available to hire from AI, 5G, quantum computing, and extended reality, but the reality is that there is and will be a shortage of these skills in the marketplace,” he stated. “Compounding the problem, finding security talent with these emerging tech skills will be even more difficult,” he stated.
Features of 5G technology raise new security issues, including virtualization that expands the attack surface and “hyper-accurate” tracking of attack locations, increasing privacy concerns for users. “Like the growth of cloud services, 5G has the potential to create shadow networks that operate outside the knowledge and management of the company,” Ordóñez stated.
“Device registration must include authentication to handle the enterprise attack surface. Without it, the integrity of the messages and the identity of the user cannot be assured,” he stated. Companies will need the commitment of the chief information security officer (CISO) to be effective. “Success requires significant CISO commitment and expertise in cyber risk management from the outset and throughout the day-to-day of innovation, including having the right mindset, behaviors and culture to make it happen.”
Augmented reality also introduces a range of new security risks, with issues of security around location, trust recognition, the content of images and surrounding sound, and “content masking.” In regard to this, “The command “open this valve” can be directed to the wrong object and generate a catastrophic activation,” Ordóñez suggested.
Techniques to Guard Data Privacy in 5G Era
Data privacy is one of the most important issues of the decade, as AI expands and more regulatory frameworks are being put in place at the same time. Several data management techniques can help organizations stay in compliance and be secure, suggested Jiani Zhang, President of the Alliance and Industrial Solution Unit at Persistent Systems, where she works closely with IBM and Red Hat to develop solutions for clients, as reported recently in The Enterprisers Project.
Federated Learning. In a field with sensitive user data such as healthcare, the traditional wisdom of the last decade was to ‘unsilo” data whenever possible. However, the aggregation of data necessary to train and deploy machine learning algorithms has created “serious privacy and security problems,” especially when data is being shared within organizations.
In a federated learning model, data stays secure in its environment. Local ML models are trained on private data sets, and model updates flow between the data sets to be aggregated centrally. “The data never has to leave its local environment,” stated Zhang.
“In this way, the data remains secure while still giving organizations the ‘wisdom of the crowd,’” she stated. “Federated learning reduces the risk of a single attack or leak compromising the privacy of all the data because instead of sitting in a single repository, the data is spread out among many.”
Explainable AI (XAI). Many AI/ML models, neural networks in particular, are black boxes whose inputs and operations are not visible to interested parties. A new area of research is explainability, which uses techniques to help bring transparency, such as decision trees representing a complex system, to make it more accountable.
“In sensitive fields such as healthcare, banking, financial services, and insurance, we can’t blindly trust AI decision-making,” Zhang stated. A consumer rejected for a bank loan, for example, has a right to know why. “XAI should be a major area of focus for organizations developing AI systems in the future,” she suggested.
AI Ops/ML Ops. The idea is to accelerate the entire ML model lifecycle by standardizing operations, measuring performance, and automatically remediating issues. AIOps can be applied to the following three layers:
- Infrastructure: Automated tools allow organizations to scale their infrastructure and keep up with capacity demands. Zhang mentioned an emerging subset of DevOps called GitOps, which applies DevOps principles to cloud-based microservices running in containers.
- Application Performance Management (APM): Organizations are applying APM to manage downtime and maximize performance. APM solutions incorporate an AIOps approach, using AI and ML to proactively identify issues rather than take a reactive approach.
- IT service management (ITSM): IT services span hardware, software and computing resources in massive systems. ITSM applies AIOps to automate ticketing workflows, manage and analyze incidents, and authorize and monitor documentation among its responsibilities.
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Trussle works with HooYu to make the onboarding process easier for its customers
KYC and customer onboarding provider, HooYu, announced today that it is working with UK fintech and online mortgage broker, Trussle, to deliver a frictionless onboarding journey for its customers.
Committed to its vision of streamlining more of the mortgage process to provide a more convenient home financing journey for customers, Trussle chose to work with HooYu so they could implement the KYC provider’s configurable digital journey. Trussle customers are now guided through KYC, customised in Trussle branding and HooYu performs real-time validation of proof of identity documents.
The journey also asks customers to provide a selfie and delivers facial biometric comparison with their ID document. Customers can also be prompted to provide proof of address documentation from HooYu for proofing and recency checks so they can move on with their mortgage application at speed.
Founded in 2015 to create a free digital advice platform for first time buyers and homeowners alike, Trussle has supported thousands of customers with their home financing needs. Trussle combines smart technology and human expertise to make faster and more informed mortgage decisions, delivering a better experience and greater certainty for its customers.
Stephanie Marrs, VP Risk and Compliance at Trussle, commented: “Buying a home can be one of the most stressful experiences a person will go through in their lifetime. We’re passionate about improving the process that our customers experience when securing a mortgage. We’re working with HooYu to help make the onboarding journey smoother and to manage fraud risks earlier on in the customer journey. This is another step in our commitment to providing a better mortgage experience for our customers.”
David Pope, HooYu Marketing Director, added: “At HooYu we’re dedicated to creating frictionless customer onboarding journeys with KYC processes that are configured for each customer. The integration of HooYu in the Trussle journey gives customers an even smoother digital experience in the mortgage application process.”
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