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Is the Future of Cyber Security in the Hands of Artificial Intelligence (AI)? -- 1

#artificialintelligence

Chinese philosophy yin and yang represent how the seemingly opposite poles can complement each other and achieve harmony. In cybersecurity, this ancient philosophy perfectly represents the relationship between supervised and unsupervised machine learning. For example, monitored machine learning processes can be used for detection, while unsupervised machine learning uses clustering. In the case of cybersecurity and data security research and development, monitored machine learning is often implemented in the form of machine learning algorithms. It is not easy to describe Artificial Intelligence (AI). It has no clear definition.


The increasing importance of data management

#artificialintelligence

The planet's population is at 7.8 billion and it keeps growing. More and more people work from home. Technologies like the Internet of Things, edge computing, and AI are being adopted at increasingly rapid rates. And demand for consumer endpoint devices is growing. All these factors result in the proliferation of enterprise data.


Bridging digital health divides

Science

On 23 March 2020, India announced a national lockdown to contain the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic ([ 1 ][1]). Routine health care virtually came to a standstill, with only emergency care being provided. In view of the high infectivity of SARS-CoV-2 and scarcity of quality personal protective equipment, patients and health care workers (HCWs) both looked for alternatives to face-to-face care ([ 2 ][2]). Telemedicine and digital health, oversold and underdelivered for the past two decades, found a new impetus driven by coalescence of often antagonistic viewpoints on issues such as rights of medical practitioners versus digital health companies, regulatory standards to ensure quality and data security, and financial models of public versus private goods. However, whether the current urgency will succeed in bringing about digital health transformation, with quality care and seamless connections across spheres of life, will depend on many factors. The old adage of crisis triggering reform came true in India, with pending matters being rapidly cleared. On 25 March, telemedicine practice guidelines were released, removing uncertainty about the legitimacy of telemedicine since 2018 due to an adverse court decision ([ 3 ][3]). In May, financial approval was granted to the 2019 national digital health blueprint that advocates a separate national digital health authority to develop and administer high-value digital public health goods in the form of a national health stack containing master health data of the nation and necessary tools for authorized access ([ 4 ][4]). These far-reaching decisions are the culmination of a long process, and the rapid timeline of their clearance is testimony to the catalyst effect of the SARS-CoV-2 pandemic on digital health transformation. However, during times of rapid acceleration, it is important to steer precisely and with anticipation to avoid crashes. The organic growth plan contained in the “blueprint” should not become the “wild west,” where concern for data integrity, privacy, and ethics gets lost. India has a well-recognized need and capacity for digital health services such as telemedicine, owing to large underserved rural areas, as well as domestic strength in information technology. There has been continuing investment in general digital infrastructure and governance, and India is one of the fastest-growing digital consumer markets, with more than half a billion internet subscribers using over 8 GB data monthly, at some of the lowest data costs in the world ([ 5 ][5]). Data speed is sufficient for video communication well beyond the megacities and cities, into the rural hinterlands. Yet, telemedicine is one of the least used digital services despite almost two decades of planning and pilot studies. Satellite-based telemedicine was launched in 2000 by Apollo Hospitals (a large corporate) and the Indian Space Research Organization through a public-private partnership ([ 6 ][6]). A national telemedicine task force was established as early as 2005. Unfortunately, scalable and sustainable models never emerged, partly because of technological constraints such as limited internet speed and partly owing to lack of economic incentives. The few notable successes, such as teleradiology, were due to a naturally digital workflow that required little additional infrastructure, coupled with sustainable economic models. Imaging services became possible in regions that had been unable to recruit radiologists, opening new markets and attracting private investment. Teleradiology was also used to optimally distribute cases to experts across the globe, allowing use of time-zone differences and price differentials to create value-added consultation services from India ([ 7 ][7]). In other medical fields, where workflow was not natively digital, it was difficult to even get to digitization of analog data, let alone digitalization, where core health care processes are unified digitally. Digitalization can improve quality, efficiency, and accessibility but requires reimagination of existing systems (see the figure). An important lesson from India's experience is that citizen-centric digital health policies, such as increasing accessibility for underserved areas with low sociodemographic development, require simultaneous investments in physical health infrastructure. A major challenge is that more than 80% of outpatient care is currently delivered by the private sector, with wide variations in quality and cost ([ 8 ][8]). However, the government-provided care sector dominates in terms of inpatient beds and perinatal care. Reimagining digital health in India must thus be a multipronged strategy. Individual practitioners, working on a fee-for-service basis, are the backbone of Indian health care, especially in smaller cities and rural areas. These are typically low-cost, high-volume practices with an average consultation time of less than 2 min, much of which goes into prescriptions and refills ([ 9 ][9]). There is a sense of patient ownership and a justifiable fear that transition to digital health may lead to weakening of relationships with patients, divert referrals, create additional burden on time and infrastructure, and reduce financial returns. In the time of coronavirus disease 2019 (COVID-19), fear has driven consensus regarding the viability and desirability of digital interactions, given that HCWs figured prominently among the global infected and the dead, accounting for a large proportion of young and healthy COVID-19 patients with severe illness ([ 2 ][2]). This has accelerated initial digital adoption by individual practitioners, but there is a danger that these will be stop-gap solutions of insufficient quality and without measures for data privacy and protection. ![Figure][10] Stages in digital health evolution The first stage of digitization has been crossed in many places in India. The next stage of digitalization has started in megacities but is yet to percolate nationally. The final stage of digital transformation is envisioned in a national digital health blueprint advocating a fully connected open Health Stack securely aggregating patient, provider, and payer data. Necessary elements such as the world's largest biometrically enabled and cloud-based national unique identification authority and a linked universal payment interface raise hope for successful convergence. GRAPHIC: MELISSA THOMAS BAUM/ SCIENCE Conversely, digitalization has already happened in corporate health care organizations that employ many physicians, cater to a higher socioeconomic stratum with digital access, and receive payment from insurance companies for documented services. These organizations exercise high control over customized digital platforms that are professionally managed. In contrast to the corporate sector, government health care institutions are largely still analog, but there is a strong digital commitment in the “blueprint.” For example, India aims to create 150,000 wellness centers and provide health insurance to 100 million families under the “Ayushman Bharat” scheme. The blueprint envisions a central digital repository and secure access for every citizen to their medical records. This seems possible because necessary foundations have been laid. The world's largest biometric unique identity platform (Aadhaar), covering 1.3 billion Indians, is fully cross-functional with IndiaStack, a set of cross-domain generic building blocks that allows government, businesses, start-ups, and developers to formulate presence-less, paperless, and cashless service delivery solutions. Building a Health Stack of registries, data, and freely available tools on top of the IndiaStack is on the horizon. To ensure affordability and ease of participation by individual practitioners, a digital public goods philosophy is essential. The current greenfield state, with strong foundations, is an excellent opportunity to leapfrog the complex, restrictive, digital health systems that have evolved elsewhere. In the beginning of the lockdown, India saw an acceleration of messaging-based consultations, largely on the WhatsApp platform. This is easy for patients and individual HCWs, but unsuited to quality, scale, or data security. eSanjeevani is a government-built public telemedicine platform that is expected to nationally support Ayushman Bharat wellness centers in providing free universal health coverage ([ 10 ][11]). COVID-19 has accelerated its uptake and use by multiple states. The central point of accessing COVID-19–related information and care is a multilingual personal risk assessment and contact tracing app called Aarogya Setu (AS), which became the world's fastest-growing mobile app after its launch on 2 April ([ 11 ][12]). AS links out to a web portal, AS Mitr (ASM), that permits users to obtain telemedicine consultations, necessary testing, and home delivery of medicines ([ 12 ][13]). All consultations are free, whether through eSanjeevani or one of many private providers. ASM has become a fast-tracked entry point into digital health for well-known tech companies, as well as new coalitions that have sprung up almost overnight between venture capitalists, hospitals, and online marketplaces. Mobile phone penetration in India is extremely high, but not everyone has a smartphone or internet access suitable for ASM. Under project StepOne, Indian start-ups specialized in cloud telephony, language processing, call handling, and software development came together to cater to people without smartphones or internet, through an automated interactive voice response system that guides callers and enables consultations with volunteer doctors, if needed ([ 13 ][14]). Within a few months, this has become one of the largest such efforts, handling ∼40,000 calls daily and spanning 10 states, with volunteers who can handle the 30 major Indian languages. In India, both the challenges and opportunities are immense. With COVID-19 providing immediate traction and potential to develop very large user bases, many of these entrants are almost certain to extend digital offerings to other health care sectors. There has also been a market shift with digital products created for affordable health care access becoming a preferred option with wider markets. For instance, CogniABle, an Indian digital health company, has been providing early screening and affordable behavioral intervention for autism ([ 14 ][15]). The demand of such niche products has moved from local to global, as the world suffers through lockdowns and looks for digital alternatives. Similar experiences abound in every sector from diabetes to women's health, and innovative digital health products have a great opportunity to scale. Ensuring quality data flow across homes, diagnostic centers, clinics, and hospitals is a major challenge requiring low-cost, high-quality connected health devices and wearables, an area that has now been prioritized by the Council of Scientific and Industrial Research, India. Artificial intelligence (AI) tools are being developed to process the increasing digital data inflows, from chest x-rays to videos. Although the immediate impact of such tools on COVID-19 is unclear, rapid growth of the AI-health interface is likely. It remains to be seen how conventional health systems, medical providers, and consumers react to these changes after COVID-19. Although health corporates and an emerging class of digital natives in Indian megacities may see immediate benefits, the case is not so clear elsewhere. Increased affordability and access to citizens everywhere is the real touchstone of success. An obvious area of concern, given the composition of the new coalitions, is the ownership and use of data. Use of data to establish dominance in a fledgling market or for exploitative practices is not unheard of in other sectors. Health being a human right, regulatory policies for use, storage, access, and transmission of health data must firmly avoid both paralysis and colonialism. Creation of authorized health-data exchanges, with transparent transactions, is one of the possible solutions ([ 15 ][16]). The purpose of digital health care remains better care of people's health; a vibrant data or digital economy is only a desirable side product. The future of digital health in India looks bright, with COVID-19 providing urgency to a sector that has seen much deliberation with limited action. It is important to now focus on building trust and reducing friction, between the existing health system and digital entrants. Patient primacy, ethical data use, respect for conventional health care, and sustainable growth models must be integral parts of the Indian digital health movement. For the foreseeable future, babies will still be delivered by humans, and public health infrastructure, strong social contracts, and thoughtful leadership will still matter most. 1. [↵][17]1. P. Pulla , BMJ 368, m1251 (2020). [OpenUrl][18][FREE Full Text][19] 2. [↵][20]1. P. Lapolla et al ., Infect. Control Hosp. Epidemiol. 10.1017/ice.2020.241 (2020). 3. [↵][21]Ministry of Health and Family Welfare (India), Telemedicine Practice Guidelines (2020); [www.mohfw.gov.in/pdf/Telemedicine.pdf][22]. 4. [↵][23]Ministry of Health and Family Welfare (India), National Digital Health Blueprint (2019); [www.main.mohfw.gov.in/sites/default/files/National\_Digital\_Health\_Blueprint\_Report\_comments\_invited.pdf][24]. 5. [↵][25]McKinsey Global Institute, Digital India: Technology to transform a connected nation (2019); [www.mckinsey.com/business-functions/mckinsey-digital/our-insights/digital-india-technology-to-transform-a-connected-nation][26]. 6. [↵][27]1. V. G. Chellaiyan, 2. A. Y. Nirupama, 3. N. Taneja , J. Family Med. Prim. Care 8, 1872 (2019). [OpenUrl][28] 7. [↵][29]1. A. Agrawal, 2. D. B. Koundinya, 3. J. S. Raju, 4. A. Agrawal, 5. A. Kalyanpur , Emerg. Radiol. 24, 157 (2017). [OpenUrl][30] 8. [↵][31]1. T. Jayakrishnan, 2. B. Thomas, 3. B. Rao, 4. B. George , Int. J. Med. Public Health 3, 225 (2013). [OpenUrl][32] 9. [↵][33]1. G. Irving et al ., BMJ Open 7, e017902 (2017). [OpenUrl][34][Abstract/FREE Full Text][35] 10. [↵][36]eSanjeevani; . 11. [↵][37]1. A. Jhunjhunwala , Indian Natl. Acad. Eng. 5, 157 (2020). [OpenUrl][38] 12. [↵][39]Aarogya Setu Mitr; [www.aarogyasetumitr.in][40]. 13. [↵][41]Project StepOne; [www.projectstepone.org][42]. 14. [↵][43]CogniAble; . 15. [↵][44]1. S. Balsari et al ., J. Med. Internet Res. 20, e10725 (2018). Acknowledgments: Thanks to Lipsa for help with artwork and The Lancet–Financial Times commission for Governing Health Futures 2030 for discussions. A.A. is supported by the Council of Scientific and Industrial Research (India), Wellcome Trust-DBT India Alliance, and Fondation Botnar. [1]: #ref-1 [2]: #ref-2 [3]: #ref-3 [4]: #ref-4 [5]: #ref-5 [6]: #ref-6 [7]: #ref-7 [8]: #ref-8 [9]: #ref-9 [10]: pending:yes [11]: #ref-10 [12]: #ref-11 [13]: #ref-12 [14]: #ref-13 [15]: #ref-14 [16]: #ref-15 [17]: #xref-ref-1-1 "View reference 1 in text" [18]: {openurl}?query=rft.jtitle%253DBMJ%26rft_id%253Dinfo%253Adoi%252F10.1136%252Fbmj.m1251%26rft_id%253Dinfo%253Apmid%252F32217534%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [19]: /lookup/ijlink/YTozOntzOjQ6InBhdGgiO3M6MTQ6Ii9sb29rdXAvaWpsaW5rIjtzOjU6InF1ZXJ5IjthOjQ6e3M6ODoibGlua1R5cGUiO3M6NDoiRlVMTCI7czoxMToiam91cm5hbENvZGUiO3M6MzoiYm1qIjtzOjU6InJlc2lkIjtzOjE4OiIzNjgvbWFyMjZfMTQvbTEyNTEiO3M6NDoiYXRvbSI7czoyMzoiL3NjaS8zNjkvNjUwNy8xMDUwLmF0b20iO31zOjg6ImZyYWdtZW50IjtzOjA6IiI7fQ== [20]: #xref-ref-2-1 "View reference 2 in text" [21]: #xref-ref-3-1 "View reference 3 in text" [22]: http://www.mohfw.gov.in/pdf/Telemedicine.pdf [23]: #xref-ref-4-1 "View reference 4 in text" [24]: http://www.main.mohfw.gov.in/sites/default/files/National_Digital_Health_Blueprint_Report_comments_invited.pdf [25]: #xref-ref-5-1 "View reference 5 in text" [26]: http://www.mckinsey.com/business-functions/mckinsey-digital/our-insights/digital-india-technology-to-transform-a-connected-nation [27]: #xref-ref-6-1 "View reference 6 in text" [28]: {openurl}?query=rft.jtitle%253DJ.%2BFamily%2BMed.%2BPrim.%2BCare%26rft.volume%253D8%26rft.spage%253D1872%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [29]: #xref-ref-7-1 "View reference 7 in text" [30]: {openurl}?query=rft.jtitle%253DEmerg.%2BRadiol.%26rft.volume%253D24%26rft.spage%253D157%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [31]: #xref-ref-8-1 "View reference 8 in text" [32]: {openurl}?query=rft.jtitle%253DInt.%2BJ.%2BMed.%2BPublic%2BHealth%26rft.volume%253D3%26rft.spage%253D225%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [33]: #xref-ref-9-1 "View reference 9 in text" [34]: {openurl}?query=rft.jtitle%253DBMJ%2BOpen%26rft_id%253Dinfo%253Adoi%252F10.1136%252Fbmjopen-2017-017902%26rft_id%253Dinfo%253Apmid%252F29118053%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [35]: /lookup/ijlink/YTozOntzOjQ6InBhdGgiO3M6MTQ6Ii9sb29rdXAvaWpsaW5rIjtzOjU6InF1ZXJ5IjthOjQ6e3M6ODoibGlua1R5cGUiO3M6NDoiQUJTVCI7czoxMToiam91cm5hbENvZGUiO3M6NzoiYm1qb3BlbiI7czo1OiJyZXNpZCI7czoxMjoiNy8xMC9lMDE3OTAyIjtzOjQ6ImF0b20iO3M6MjM6Ii9zY2kvMzY5LzY1MDcvMTA1MC5hdG9tIjt9czo4OiJmcmFnbWVudCI7czowOiIiO30= [36]: #xref-ref-10-1 "View reference 10 in text" [37]: #xref-ref-11-1 "View reference 11 in text" [38]: {openurl}?query=rft.jtitle%253DIndian%2BNatl.%2BAcad.%2BEng.%26rft.volume%253D20%26rft.spage%253De10725%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [39]: #xref-ref-12-1 "View reference 12 in text" [40]: http://www.aarogyasetumitr.in [41]: #xref-ref-13-1 "View reference 13 in text" [42]: http://www.projectstepone.org [43]: #xref-ref-14-1 "View reference 14 in text" [44]: #xref-ref-15-1 "View reference 15 in text"


Bletchley Park Trust hit in Blackbaud security breach

BBC News - Technology

The home of hacking in wartime Britain, Bletchley Park, was one of the victims of a major ransomware attack that hit software provider Blackbaud. The firm held data about people who had donated to the trust that manages the Bletchley Park museum. Harvard University has also joined the growing list of victims, which have mostly been charities and universities. Bletchley Park Trust said it was confident any exposed data was now secure. The trust added that data exposed to the hackers might have included names, dates of birth, email addresses, donation history and details of event attendance – but not credit and debit card details or bank account information.


2020 Data & Analytics Trends

#artificialintelligence

Now that data is the most transformative asset in business, it's essential to prepare for what lies ahead, and to adjust strategies accordingly in order to successfully face the business landscape of tomorrow. We have identified 10 trends happening in 2020 that will be catalysts and enablers for change, and they will drive companies to enhance capabilities to stay at the forefront of innovation. They will allow data to be consumed dynamically and in different ways, causing people to search and think of new ways to use data. Given Trends These trends are a must, and they require action now. It's apparent that legacy on-premises platforms have failed to make data accessible to all users.


AI: A Remedy for Human Error?

#artificialintelligence

Human error is one of the greatest causes of data breaches worldwide, but the seeming inevitability of it makes human error especially dangerous While malicious or criminal attacks can be combatted by state-of-the-art cybersecurity software, and while you can prepare for IT failures with a diligent backup strategy, human error is still in need of a remedy. Humans are naturally prone to making mistakes. Such errors are increasingly impactful in the workplace, but human error in the realm of cybersecurity can have particularly devastating and long-lasting effects. As the digital world becomes more complex, it becomes much tougher to navigate


Is the Future of Cyber Security in the Hands of Artificial Intelligence (AI)? -- 1

#artificialintelligence

Chinese philosophy, yin and yang represent how the seemingly opposite poles can complement each other and achieve harmony. In cybersecurity, this ancient philosophy perfectly represents the relationship between supervised and unsupervised machine learning. For example, monitored machine learning processes can be used for detection, while unsupervised machine learning uses clustering. In the case of cybersecurity and data security research and development, monitored machine learning is often implemented in the form of machine learning algorithms. It is not easy to describe Artificial Intelligence (AI). It has no clear definition.


Challenges Faced by a Data Scientist and How to Overcome Them? Blog

#artificialintelligence

Data Scientist is regarded as the sexiest job of the 21st century. It is a high paying lucrative jobs which comes with a lot of responsibility and commitment. Any professional needs to master state-of-the-art skills and technologies to become a Data Scientist in the modern world. It is a profession where people from different disciplines could fit in as there are a plethora of specialties embedded in a Data Scientist role. Data Science is not a present-day phenomenon, however.


Boardroom diversity proves mission critical in data security, AI and beyond - SiliconANGLE

#artificialintelligence

The past two years have seen a record number of women elected to board positions. According to a report on U.S. Board Diversity Trends posted by Harvard Law School, 46% of newly elected directors in 2019 were female and women now hold 27% of directorships across the S&P 500 companies. One of those newly elected members is Wendy Pfeiffer (pictured), chief information officer of Nutanix Inc. and board director with Qualys Inc. and Girls in Tech Inc. "When I was recruited for the board [of Qualys] … we didn't talk about the fact that I am female at all. We talked about the fact that I'm an operator, that I'm a technologist," Pfeiffer told Jeff Frick (@JeffFrick), host of theCUBE, SiliconANGLE Media's mobile livestreaming studio during the Qualys Security Conference in Las Vegas. During the interview, Pfeiffer and Frick discussed how the growth of artificial intelligence is helping data security, making having a diverse workforce more critical than ever.


How AI Can Improve Business Efficiency Businessing Mag

#artificialintelligence

Artificial science is a phenomenon today that is expanding the possibilities of uses of artificial intelligence in business. Not only is AI is revolutionizing the world of science, but it is also showing us uses in business that we could only dream about. Although AI is one of the dominating technologies in recent times, not everyone understands the scope of its importance in the world of business. If you are new to the business world, or even an experienced business owner, you'd agree that you need your business to run as efficiently as possible because there's a solid connection between profitability and efficiency. Whether you run a big company, top software development company or you're a multinational business empire, the more efficient your business is, the more productivity and profitability it rakes in.