{"id":34679,"date":"2018-11-13T18:19:16","date_gmt":"2018-11-13T23:19:16","guid":{"rendered":"https:\/\/digital.hbs.edu\/platform-rctom\/submission\/general-electric-and-nozomi-networks-defending-industrial-control-systems-using-machine-learning\/"},"modified":"2018-11-13T18:19:16","modified_gmt":"2018-11-13T23:19:16","slug":"general-electric-and-nozomi-networks-defending-industrial-control-systems-using-machine-learning","status":"publish","type":"hck-submission","link":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/general-electric-and-nozomi-networks-defending-industrial-control-systems-using-machine-learning\/","title":{"rendered":"General Electric and Nozomi Networks: Defending Industrial Control Systems using Machine Learning"},"content":{"rendered":"

Introduction<\/em><\/strong><\/p>\n

General Electric Company is a conglomerate that operates in various energy and industrial segments that rely heavily on industrial control systems (ICS).\u00a0 Machine learning has become a pivotal element in protecting these systems against cyber-attacks.\u00a0 Attacks have targeted various functions of these energy and industrial companies operating on the SCADA (supervisory control and data acquisition) system.[1]<\/a>\u00a0 SCADA systems have been the target of probing attacks conducted by terrorist groups and nation states.\u00a0 According to an independent survey conducted by Business Advantage, approximately 54% of companies have experienced an ICS security incident in the past 12 months.[2]<\/a> The presence of these attacks highlights the rapidly growing market for ICS cybersecurity for vulnerable public infrastructure.\u00a0 As a result, General Electric has partnered with Nozomi Networks, a company well known for its cybersecurity and artificial intelligence capabilities.\u00a0 Together, they are aiming to leverage the megatrend of machine learning in order to protect the energy and industrial sector.[3]<\/a><\/p>\n

Partnership for Secure Systems<\/em><\/strong><\/p>\n

General Electric\u2019s partnership with Nozomi Networks uses the proprietary SCADAguardian platform in order to protect ICS from various cyberattacks.\u00a0 SCADAguardian leverages both artificial intelligence and machine learning in order to protect the control system components.[4]<\/a>\u00a0 The system is designed to assist subsidiaries of GE to monitor their physical and digital infrastructure using large amounts of data that have established operating baselines.\u00a0 The overarching goal is to align the system with the company\u2019s desire to optimize the \u201cefficiency, security, and reliability\u201d of industrial systems[5]<\/a>\u00a0 SCADAguardian operates in concert with GE\u2019s Predix, which is a system that supports infrastructure and operations.[6]<\/a>\u00a0 The Predix system in concert with SCADAguardian provides key indicators to investigate causes of equipment malfunction or degradation.<\/p>\n

Current and Near Future Applications<\/em><\/strong><\/p>\n

This data collected by both GE\u2019s Predix system and SCADAguardian are quintessential examples of using machine learning to optimize performance.\u00a0 In the short term, General Electric has partnered with Naomi Networks to implement SCADAguard to assist with multiple levels of security.[7]<\/a>\u00a0 This includes security for endpoint devices and data stored in the cloud in concert with a Central Management Console (CMC), which centralizes the aggregated data.[8]<\/a>\u00a0 Machine learning is critical throughout these functions to complete risk assessment, threat identification, prevention, and response.<\/p>\n

In the medium term, there are two primary areas where General Electric is weighing their investment in machine learning.\u00a0 The first is standardizing the defense of all plants and SCADA systems.[9]<\/a>\u00a0 The second is aggregating the data of SCADA systems into a defensible network with the appropriate firewalls in place. Once all of the plants are online, they are using machine learning techniques to optimize their defense against cyber-attacks.<\/p>\n

Recommendations<\/em><\/strong><\/p>\n

In the short term, GE should continue to hire cybersecurity professionals for upgrades and training.\u00a0 With its wide expanse of geographic and networked subsidiaries, GE has the potential to be a significant target.\u00a0 Not only could cyberattacks on SCADA systems threaten brand image, but also endanger the lives of employees operating the machinery.[10]<\/a>\u00a0 While specific company data is often held confidential, on average, ICS attacks resulted in $497,097 of costs for targeted large companies in 2017 (500+ employees).[11]<\/a><\/p>\n

Over the next decade, GE should partner with entities in the U.S. government in order to counter the wider range of threats.\u00a0 The Department of Energy created an office of Cybersecurity, Energy Security, and Emergency Response (CESER) to assist with mitigation techniques.[12]<\/a>\u00a0 Still, there is a gap between mitigation techniques sponsored by the DOE and companies\u2019 willingness to report incident data.\u00a0 Since threats range from spear phishing to Advanced Persistent Threats (APTs), where a wide span of responses is required, requiring additional funding and resources.[13]<\/a> General Electric should join in partnership with CESER in order to consolidate corporate data with classified data and improve the quality of their data analysis.<\/p>\n

Conclusion<\/em><\/strong><\/p>\n

Machine learning has improved General Electric\u2019s ability to face a complex threat on SCADA systems by leveraging SCADAguardian.\u00a0 In this specific case, a large conglomerate invested capital in a cybersecurity company in order to tailor products.\u00a0 A few questions remain \u2013 should other large companies follow a similar model and partner with outside organizations?\u00a0 Would it be more beneficial to grow machine learning techniques in the cybersecurity realm internally?\u00a0 Are there any cases where companies should develop solely internal tools for securing their ICS?<\/p>\n

 <\/p>\n

(Word Count: 717)<\/p>\n

 <\/p>\n

<\/a>[1] General Electric Digital, \u201cCyber Security and Data Governance,\u201d Accessed on November 10, 2018, https:\/\/www.ge.com\/digital\/applications\/cyber-security.<\/p>\n

<\/a>[2] Kaspersky Labs, \u201cThe State of Industrial Cybersecurity 2017,\u201d Business Advantage,<\/u> 2017, https:\/\/go.kaspersky.com\/rs\/802-IJN-240\/images\/ICS WHITE PAPER.pdf.<\/p>\n

<\/a>[3] Mary Ryan, \u201cInvenergy Future Fund Leads $15 Million Investment in Industrial Cybersecurity Leader Nozomi Networks,\u201d January 10, 2018, https:\/\/invenergyllc.com\/news\/invenergy-future-fund-leads-15-million-investment-in-industrial-cybersecurity-leader-nozomi-networks.<\/p>\n

<\/a>[4] Aaron Hand, \u201cPartnership Combines Cybersecurity With Predictive Maintenance,\u201d August 24, 2018, https:\/\/www.automationworld.com\/article\/technologies\/security\/partnership-combines-cybersecurity-predictive-maintenance.<\/p>\n

<\/a>[5] Rebecca Slayton, “Efficient, Secure Green: Digital Utopianism and the Challenge of Making the Electrical Grid \u2018Smart\u2019” Information & Culture 48, no. 4 (2013): 448-78. http:\/\/www.jstor.org.ezp-prod1.hul.harvard.edu\/stable\/43737372.<\/p>\n

<\/a>[6] General Electric, \u201cPredix HMI\/SCADA,\u201d Accessed on November 10, 2018,\u00a0 https:\/\/www.ge.com\/digital\/applications\/hmi-scada.scada<\/p>\n

<\/a>[7] Nozomi Networks, \u201cGE Power and Nozomi Networks to Enhance Cyber Security for Energy and Industrial Operators Worldwide,\u201d October 4, 2018, https:\/\/www.nozominetworks.com\/2018\/10\/04\/press-release\/ge-and-nozomi-networks-to-enhance-cyber-security-for-energy-and-industrial-operators-worldwide\/.<\/p>\n

<\/a>[8] Nozomi Networks, \u201cData Sheet SCADAguardian,\u201d Nozomi Networks, 2018, https:\/\/www.nozominetworks.com.<\/p>\n

<\/a>[9] Nozomi Networks, \u201cGE Power and Nozomi Networks.\u201d<\/p>\n

<\/a>[10] Dong-Joo Kang, Hak-Man Kim, “Development of test-bed and security devices for SCADA communication in electric power system”, Telecommunications Energy Conference 2009. INTELEC 2009. 31st International, pp. 1-5, 2009.<\/p>\n

<\/a>[11] Kaspersky, \u201cThe State of Industrial Cybersecurity 2017.\u201d<\/p>\n

<\/a>[12] Sonal Patel, \u201cDOE Layes Out How Power Sector Could Win the Cybersecurity Battle,\u201d May 17, 2018, https:\/\/www.powermag.com\/doe-lays-out-how-power-sector-could-win-the-cybersecurity-battle\/.<\/p>\n

<\/a>[13] Kaspersky, \u201cThe State of Industrial Cybersecurity 2017.\u201d<\/p>\n","protected":false},"excerpt":{"rendered":"

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