Policies for Information Security & Privacy
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Data Protection
Handbook on the Techniques of Judicial Interactions in the Application of the EU Charter DATA PROTECTION IN THE FRAMEWORK OF THE PROJECT ‘E-LEARNING NATIONAL ACTIVE CHARTER TRAINING (E-NACT)’ FUNDED BY THE EUROPEAN COMMISSION FUNDAMENTAL RIGHTS & CITIZENSHIP PROGRAMME Researcher responsible for the Handbook: Dr Mariavittoria Catanzariti 1 NATIONAL EXPERTS AND COLLABORATORS The e-NACT team would like to thank the following experts and collaborators who contributed to the selection of the national and European case law upon which this Handbook is built. Federica Casarosa Madalina Moraru Karolina Podstawa Joan Soares Mullor Sara Azevedo Afonso Brás Sergiu Popovici Rita de Brito Gião Hanek Diana Lavinia Botău Francesco Perrone Florentino Gregorio Ruiz Yamuza 2 Contents Part I - Data protection and privacy as EU fundamental rights ......................................... 8 Setting the scene ..................................................................................................................... 8 From the Directive 95/46/EC to the GDPR.......................................................................... 11 The European culture of data protection .............................................................................. 12 The Data Protection Reform of 2016: the GDPR and the Law Enforcement Directive ...... 13 Main principles of data processing ....................................................................................... 14 The basics: what’s personal data? .............................................................................................. -
Data Privacy: De-Identification Techniques
DEVELOPING AND CONNECTING ISSA CYBERSECURITY LEADERS GLOBALLY Data Privacy: De-Identification Techniques By Ulf Mattsson – ISSA member, New York Chapter This article discusses emerging data privacy techniques, standards, and examples of applications implementing different use cases of de-identification techniques. We will discuss different attack scenarios and practical balances between privacy requirements and operational requirements. Abstract The data privacy landscape is changing. There is a need for privacy models in the current landscape of the increas- ing numbers of privacy regulations and privacy breaches. Privacy methods use models and it is important to have a common language when defining privacy rules. This article will discuss practical recommendations to find the right practical balance between compli- ance, security, privacy, and operational requirements for each type of data and business use case. Figure 1 – Forrester’s global map of privacy rights and regulations [4] ensitive data can be exposed to internal users, partners, California Customer Privacy Act (CCPA) is a wake-up call, and attackers. Different data protection techniques can addressing identification of individuals via data inference provide a balance between protection and transparen- through a broader range of PII attributes. CCPA defines Scy to business processes. The requirements are different for personal information as information that identifies, relates systems that are operational, analytical, or test/development to, describes, is reasonably capable of being associated with, as illustrated by some practical examples in this article. or could reasonably be linked, directly or indirectly, with a We will discuss different aspects of various data privacy tech- particular consumer or household such as a real name, alias, niques, including data truthfulness, applicability to different postal address, and unique personal identifier [1]. -
From Security Monitoring to Cyber Risk Monitoring
Issue 19 | 2016 Complimentary article reprint From security monitoring to cyber risk monitoring Enabling business-aligned cybersecurity By Adnan Amjad, Mark Nicholson, Christopher Stevenson, and Andrew Douglas About Deloitte Deloitte refers to one or more of Deloitte Touche Tohmatsu Limited, a UK private company limited by guarantee (“DTTL”), its network of member firms, and their related entities. DTTL and each of its member firms are legally separate and independent entities. DTTL (also referred to as “Deloitte Global”) does not provide services to clients. Please see www.deloitte.com/about for a more detailed description of DTTL and its member firms. Deloitte provides audit, tax, consulting, and financial advisory services to public and private clients spanning multiple industries. With a globally connected network of member firms in more than 150 countries and territories, Deloitte brings world-class capabilities and high-quality service to clients, delivering the insights they need to address their most complex business challenges. Deloitte’s more than 200,000 professionals are committed to becoming the standard of excellence. This communication contains general information only, and none of Deloitte Touche Tohmatsu Limited, its member firms, or their related entities (collectively, the “Deloitte Network”) is, by means of this communication, rendering professional advice or services. No entity in the Deloitte net- work shall be responsible for any loss whatsoever sustained by any person who relies on this communication. © 2016. For information, contact Deloitte Touche Tohmatsu Limited. 122 www.deloittereview.com From security monitoring to cyber risk monitoring 123 CYBER RISK MANAGEMENT From security monitoring to cyber risk monitoring Enabling business-aligned cybersecurity By Adnan Amjad, Mark Nicholson, Christopher Stevenson, and Andrew Douglas Illustration by Lucy Rose Why didn’t we detect it? That’s the all-too-common question when a major cyber incident is discovered—or, too often, announced. -
Security and Privacy Issues of Big Data
Security and Privacy Issues of Big Data José Moura1,2, Carlos Serrão1 1 ISCTE-IUL, Instituto Universitário de Lisboa, Portugal 2 IT, Instituto de Telecomunicações, Lisboa, Portugal {jose.moura, carlos.serrao}@iscte.pt ABSTRACT This chapter revises the most important aspects in how computing infrastructures should be configured and intelligently managed to fulfill the most notably security aspects required by Big Data applications. One of them is privacy. It is a pertinent aspect to be addressed because users share more and more personal data and content through their devices and computers to social networks and public clouds. So, a secure framework to social networks is a very hot topic research. This last topic is addressed in one of the two sections of the current chapter with case studies. In addition, the traditional mechanisms to support security such as firewalls and demilitarized zones are not suitable to be applied in computing systems to support Big Data. SDN is an emergent management solution that could become a convenient mechanism to implement security in Big Data systems, as we show through a second case study at the end of the chapter. This also discusses current relevant work and identifies open issues. Keywords: Big Data, Security, Privacy, Data Ownership, Cloud, Social Applications, Intrusion Detection, Intrusion Prevention. INTRODUCTION The Big Data is an emerging area applied to manage datasets whose size is beyond the ability of commonly used software tools to capture, manage, and timely analyze that amount of data. The quantity of data to be analyzed is expected to double every two years (IDC, 2012). -
Google Privacy Policy: Main Findings and Recommendations
APPENDIX GOOGLE PRIVACY POLICY: MAIN FINDINGS AND RECOMMENDATIONS OUTLINE I. Main findings .............................................................................................................................................................. 2 1) Legal Framework ................................................................................................................................................. 2 2) Information ............................................................................................................................................................ 2 3) Combination of data across services ........................................................................................................... 3 4) Retention period .................................................................................................................................................. 5 II. Recommendations ................................................................................................................................................... 5 1) Information ............................................................................................................................................................ 5 i. Particular case of mobile users ................................................................................................................. 6 ii. Particular case of passive users ................................................................................................................ 7 2) -
Data Privacy and Security
Policy Brief August 2016 Policy analysis from SREB’s 10 Issues in Educational Technology Data Privacy and Security Educational technology systems generate enormous amounts of data, which allow schools and colleges to provide more personalized services to every student. Creating a culture of efficient data use for students is critically important, but equally impor- tant is securing the data collected from these systems. Data privacy and security cannot be a “behind the scenes” approach for education agencies; risk assessment and mitigating practices should be common knowledge and inherent in the culture of effective data use. Although data privacy and security go hand in hand, they are two different concepts. Data security involves the technical and physical requirements that protect against unauthorized entry into a data system and helps maintain the integrity of data. Data privacy is about data confidentiality and the rights of the individual whom the data involve, how the data are used and with whom data can legally be shared. Without clear policy, the concerns of the stakeholders cannot be fairly balanced in the best interests of students, their achievement, and effective and efficient educational decision-making. Data Value and Use Inside Educators have long relied on research and data to identify effective teaching Data Value and Use 1 and learning strategies. As innovative Privacy and Security Risks 2 instructional models have emerged, Legislative Actions 3 tailored instruction has the potential Data Governance 4 to improve and accelerate student Recommended Policies 4 learning, as well as focus on individual Transparency 5 needs and skills. This personalized Role-based Usage Permissions 5 learning approach is possible because Monitoring and Breach Notification 5 of technological advancements that Training 6 permit data to be gathered from various Technical Support 6 systems and analyzed. -
Planning for Cyber Security in Schools: the Human Factor
PLANNING FOR CYBER SECURITY IN SCHOOLS: THE HUMAN FACTOR MICHAEL D. RICHARDSON Columbus State University, U.S.A. PAMELA A. LEMOINE Troy University, U.S.A. WALTER E. STEPHENS Houston County Schools, Georgia, U.S.A. ROBERT E. WALLER Columbus State University, U.S.A. ABSTRACT Cybersecurity has emerged as one of the most critical issues confronting schools in the 21st century. Computer security is an essential instrument for protecting children, but K-12 schools are considered one of the most attractive targets for data privacy crimes often due to the less-than- effective cybersecurity practices in schools. The human factor is the underlying reason why many attacks on school computers and systems are successful because the uneducated computer user is the weakest link targeted by cyber criminals using social engineering. Formal cyber security awareness is required to mitigate the exploitation of human vulnerabilities by computer hackers and attackers. INTRODUCTION Much of the world is now in cyber space and cyber security has become a massive issue with many facets of schools (Arlitsch & Edelman, 2014). Cybersecurity has brought about research, discussion, papers, tools for monitoring, tools for management, etc., with much of the focus from the schools’ side concerning the protection of their data and information (Seemma, Nandhini, & Sowmiya, 2018). As a result of increased dependence on the Internet, cybersecurity has emerged as one of the critical issues confronting schools in the 21st century (Gioe, Goodman, & Wanless, 2019). The reliance on a complex technology infrastructure has come with a price: by accepting the Internet so widely, schools have exposed themselves to a range of nefarious cyber activities by a spectrum of offenders looking for school data and information (Shen, Chen, & Su, 2017). -
An Analysis of Google's Privacy Policy and Related
1 AN ANALYSIS OF GOOGLE’S PRIVACY POLICY AND RELATED FAQs A DATA PROTECTION ANALYSIS FROM AMBERHAWK TRAINING LTD DR. C. N. M. POUNDER, MARCH 2012 An analysis of Google’s Privacy Policy (March 2012) ©Amberhawk Training Limited 2 AN ANALYSIS OF GOOGLE’S PRIVACY POLICY AND RELATED FAQs MANAGEMENT SUMMARY Google’s new combined Privacy Policy (March 2012) has been widely criticised by privacy professionals and Data Protection Authorities (in particular the CNIL – the French Data Protection Authority). However the reasons for this criticism have been made in general terms; my analysis provides a detailed explanation. The analysis shows that Google’s Privacy Policy is incoherent because it uses overlapping terms. This makes the Policy difficult to follow and to understand what type of information the Policy is claiming to protect. It cannot be fair to users if they cannot understand what the Policy means for them. The Policy is also unfair in conventional terms as it does not, in many instances, fully describe the purposes of the processing. Secondly, my analysis also confirms the claim of the CNIL that the Privacy Policy is in breach of the Data Protection Directive. However, I also show that it is in breach of the USA’s Safe Harbor Principles. As the Privacy Policy states that “Google complies with the US-EU Safe Harbour Framework”, I show that this claim cannot be substantiated if Google’s new Privacy Policy is implemented. Contradictory and confusing? The Privacy Policy uses a wide range of similar terms in different circumstances which I think are contradictory. -
Spying on Students: School Issued Devices and Student Privacy (EFF)
Spying on Students SCHOOL-ISSUED DEVICES AND STUDENT PRIVACY Frida Alim, Bridge Fellow Na e Cardo!o, Se"ior Sta## A or"e$ %e""ie Ge&'art, Re(ear)'er *are" Gullo, Media Relatio"( Anal$( Amul Kalia, Anal$( A-ril 1/, 21.2 ELECTRONIC FRONTIER FOUNDATION EFF3OR% 1 Authors: Frida Alim, Nate Cardozo, Gennie Gebhart, Karen Gullo, Amul Kalia With assistance from: Sophia Cope, Hugh D’Andrade, Jeremy Gillula, Rainey Reitman A publication of the Electronic Frontier Foundation, 2017. “Spying on Students: School-Issued Devices and Student Privacy” is released under a Creative Commons Attribution 4.0 International License (CC BY 4.0). ELECTRONIC FRONTIER FOUNDATION EFF3OR% 2 Table of Contents Executive Summary..................................................................................................................................................... 5 Introduction.................................................................................................................................................................. 7 Part 1: Survey Results................................................................................................................................................. 8 Methods..................................................................................................................................................................... 9 Respondents and Overall Trends....................................................................................................................10 Findings.................................................................................................................................................................. -
Privacy Policy
Privacy Policy IDI, LLC and its affiliate, ICS Inventory, LLC (“We,” “Our,” or “Us”) respects the privacy and security of your personal information. The following describes how we collect, use and disclose information and what rights you have to it. This Privacy Policy describes our practices in connection with information that we collect from you through our software applications, services, websites and mobile applications from our public facing side of our services and products and from our private access products and services that require registration before use (“Services”) and from sources other than our Services including, but not limited to, the telephone, mail and trade shows. This Privacy Policy also applies to any information that you may provide to us via an IDI Qualified Administrator’s (“IDIQA”) credential, website and/or other access method that enables you to use our Services. By providing information to us and/or using our Services, you acknowledge and agree to the terms and conditions of this Privacy Policy. If you do not agree to these terms and conditions, please do not use our Services. Information Collection We gather various types of information from you including personal information and personal data Personal information or personal data refers to any data or information which relates to an identified or identifiable natural person, and are the subject to applicable data protection laws, such as the EU General Data Protection Regulation 2016/679 (“GDPR”), and/or the California Consumer Privacy Act (Assembly Bill 375) (“CCPA”) including, but not limited to, your name, postal addresses (including billing and shipping addresses), telephone numbers, and email addresses, and Sensitive Information (as defined below). -
Cyber-Stalking Technology Inventory
ACKNOWLEDGEMENTS We are indebted to many people for providing insights and other contributions towards this project. While the opinions expressed in these reports are ours alone, they are informed by years of collaborating with and learning from survivors, colleagues and communities. We remain guided by the women, youth, and children experiencing violence at the hands of perpetrators. They often face high risks to their lives and wellbeing. We deeply appreciate all we continue to learn from these strong, brave, and creative individuals. Only by listening to the experiences and opinions of these women and youth, can Canada accurately identify and implement practices that best protect their safety, privacy, safety autonomy, equal rights and access to justice. Thank you to the many anti-violence workers throughout Canada who contributed by sharing their experiences and knowledge for this report and for participating in our two national surveys of anti-violence workers on Technology Abuse and on Organizational Technology Practices. These individuals work in non-profit women’s shelters, transition and interval houses, rape crisis centres, victim services agencies, counseling services, children exposed to violence programs, crisis lines, K-12 classrooms, college campuses, courts, income assistance offices, police stations, hospitals, mobile clinic vans, and many other places where a survivor of violence might request help. During this recession, many anti-violence programs face staff cuts, limited agency resources, and low salaries. These workers often volunteer time as crises arise and still took the time to fill out our surveys. We gratefully acknowledge the Office of the Privacy Commissioner of Canada for providing funding for our research and this report and for their leadership. -
The Privacy, Data Protection and Cybersecurity Law Review
The Privacy, Data Protection and Cybersecurity Law Review Editor Alan Charles Raul Law Business Research The Privacy, Data Protection and Cybersecurity Law Review The Privacy, Data Protection and Cybersecurity Law Review Reproduced with permission from Law Business Research Ltd. This article was first published in The Privacy, Data Protection and Cybersecurity Law Review - Edition 1 (published in November 2014 – editor Alan Charles Raul). For further information please email [email protected] The Privacy, Data Protection and Cybersecurity Law Review Editor Alan Charles Raul Law Business Research Ltd THE LAW REVIEWS THE MERGERS AND ACQUISITIONS REVIEW THE RESTRUCTURING REVIEW THE PRIVATE COMPETITION ENFORCEMENT REVIEW THE DISPUTE RESOLUTION REVIEW THE EMPLOYMENT LAW REVIEW THE PUBLIC COMPETITION ENFORCEMENT REVIEW THE BANKING REGULATION REVIEW THE INTERNATIONAL ARBITRATION REVIEW THE MERGER CONTROL REVIEW THE TECHNOLOGY, MEDIA AND TELECOMMUNICATIONS REVIEW THE INWARD INVESTMENT AND INTERNATIONAL TAXATION REVIEW THE CORPORATE GOVERNANCE REVIEW THE CORPORATE IMMIGRATION REVIEW THE INTERNATIONAL INVESTIGATIONS REVIEW THE PROJECTS AND CONSTRUCTION REVIEW THE INTERNATIONAL CAPITAL MARKETS REVIEW THE REAL ESTATE LAW REVIEW THE PRIVATE EQUITY REVIEW THE ENERGY REGULATION AND MARKETS REVIEW THE INTELLECTUAL PROPERTY REVIEW THE ASSET MANAGEMENT REVIEW THE PRIVATE WEALTH AND PRIVATE CLIENT REVIEW THE MINING LAW REVIEW THE EXECUTIVE REMUNERATION REVIEW THE ANTI-BRIBERY AND ANTI-CORRUPTION REVIEW THE CARTELS AND LENIENCY REVIEW THE TAX DISPUTES