Internet Of Things (Iot): Cybersecurity Risks In Healthcare,
2020
Old Dominion University
Internet Of Things (Iot): Cybersecurity Risks In Healthcare, Ruhi Patel
Cybersecurity Undergraduate Research Showcase
The rapid growth and investment in the Internet of Things (IoT) has significantly impacted how individuals and industries operate. The Internet of Things (IoT) refers to a network of physical, technology-embedded objects that communicate, detect, and interact with their external environment or internal state (Hung, 2017). According to Tankovska (2020), IoT devices are estimated to reach 21.5 billion units by 2025. This technological boom is leading various industrial sectors to notice a quick increase in cybersecurity risks and threats. One industrial sector has been particularly vulnerable to numerous cyber threats across the globe: healthcare. Oliver Noble (2020), a data encryption …
Confronting Wicked Crypto: Wicked Problems, Encryption Policy, And Exceptional Access Technology,
2020
Grand Valley State University
Confronting Wicked Crypto: Wicked Problems, Encryption Policy, And Exceptional Access Technology, Kevin Nicholas Kredit
Masters Theses
Public debate has resumed on the topic of exceptional access (EA), which refers to alternative means of decryption intended for law enforcement use. The resumption of this debate is not a renege on a resolute promise made at the end of the 1990s “crypto war”; rather, it represents a valid reassessment of optimal policy in light of changing circumstances. The imbalance between privacy, access, and security in the context of constantly changing society and technology is a wicked problem that has and will continue to evade a permanent solution. As policymakers consider next steps, it is necessary that the technical …
Politeness In Security Directives: Insights In Browser Compliance For The Human Element,
2020
University of Nebraska at Omaha
Politeness In Security Directives: Insights In Browser Compliance For The Human Element, Deanna House, Gabe Giordano
Information Systems and Quantitative Analysis Faculty Publications
The technical protection provided by information security technology is necessary as a frontline defense against threats. However, the human element adds great risk to systems and cannot be ignored. This research explores the human elements related to security communications and intention to comply with security directives. Security communications are more-commonly being sent using richer computer-based channels. While the goal of security communications is the gain compliance, there is still much to learn related to what influences a user to comply. This research explores the effects that (im)politeness has on intention to comply with security directives. The research utilized an experiment …
Lightning-Fast And Privacy-Preserving Outsourced Computation In The Cloud,
2020
Singapore Management University
Lightning-Fast And Privacy-Preserving Outsourced Computation In The Cloud, Ximeng Liu, Robert H. Deng, Pengfei Wu, Yang Yang
Research Collection School Of Computing and Information Systems
In this paper, we propose a framework for lightning-fast privacy-preserving outsourced computation framework in the cloud, which we refer to as LightCom. Using LightCom, a user can securely achieve the outsource data storage and fast, secure data processing in a single cloud server different from the existing multi-server outsourced computation model. Specifically, we first present a general secure computation framework for LightCom under the cloud server equipped with multiple Trusted Processing Units (TPUs), which face the side-channel attack. Under the LightCom, we design two specified fast processing toolkits, which allow the user to achieve the commonly-used secure integer computation and …
In-Depth Analysis Of College Students’ Data Privacy Awareness,
2020
Columbus State University
In-Depth Analysis Of College Students’ Data Privacy Awareness, Vernon D. Andrews
Theses and Dissertations
While attending university, college students need to be aware of issues related to data privacy. Regardless of the age, gender, race, or education level of college students, every student can relate to the advancement of the internet within the last decades. The internet has completely transformed the way the world receives and stores messages. Positively, the internet allows messages to be sent across the globe within the fraction of a second and provides students with access to potentially unlimited information on a variety of subjects. On the downside, there are issues on the internet that can cause more harm than …
Lightweight Deep Learning For Botnet Ddos Detection On Iot Access Networks,
2020
Missouri State University
Lightweight Deep Learning For Botnet Ddos Detection On Iot Access Networks, Eric A. Mccullough
Graduate Theses/Dissertations
With the proliferation of the Internet of Things (IoT), computer networks have rapidly expanded in size. While Internet of Things Devices (IoTDs) benefit many aspects of life, these devices also introduce security risks in the form of vulnerabilities which give hackers billions of promising new targets. For example, botnets have exploited the security flaws common with IoTDs to gain unauthorized control of hundreds of thousands of hosts, which they then utilize to carry out massively disruptive distributed denial of service (DDoS) attacks. Traditional DDoS defense mechanisms rely on detecting attacks at their target and deploying mitigation strategies toward the attacker …
Driving Cybersecurity Policy Insights From Information On The Internet,
2020
Singapore Management University
Driving Cybersecurity Policy Insights From Information On The Internet, Qiu-Hong Wang, Steven Mark Miller, Robert H. Deng
Research Collection School Of Computing and Information Systems
Cybersecurity policy analytics quantitatively evaluates the effectiveness of cybersecurity protection measures consisting of both technical and managerial countermeasures and is inherently interdisciplinary work, drawing on the concepts and methods from economics, business, social science, and law.
Differential Privacy Protection Over Deep Learning: An Investigation Of Its Impacted Factors,
2020
Yunnan University
Differential Privacy Protection Over Deep Learning: An Investigation Of Its Impacted Factors, Ying Lin, Ling-Yan Bao, Ze-Minghui Li, Shu-Sheng Si, Chao-Hsien Chu
Research Collection School Of Computing and Information Systems
Deep learning (DL) has been widely applied to achieve promising results in many fields, but it still exists various privacy concerns and issues. Applying differential privacy (DP) to DL models is an effective way to ensure privacy-preserving training and classification. In this paper, we revisit the DP stochastic gradient descent (DP-SGD) method, which has been used by several algorithms and systems and achieved good privacy protection. However, several factors, such as the sequence of adding noise, the models used etc., may impact its performance with various degrees. We empirically show that adding noise first and clipping second will not only …
Walls Have Ears: Eavesdropping User Behaviors Via Graphics-Interrupt-Based Side Channel,
2020
Singapore Management University
Walls Have Ears: Eavesdropping User Behaviors Via Graphics-Interrupt-Based Side Channel, Haoyu Ma, Jianwen Tian, Debin Gao, Jia Chunfu
Research Collection School Of Computing and Information Systems
Graphics Processing Units (GPUs) are now playing a vital role in many devices and systems including computing devices, data centers, and clouds, making them the next target of side-channel attacks. Unlike those targeting CPUs, existing side-channel attacks on GPUs exploited vulnerabilities exposed by application interfaces like OpenGL and CUDA, which can be easily mitigated with software patches. In this paper, we investigate the lower-level and native interface between GPUs and CPUs, i.e., the graphics interrupts, and evaluate the side channel they expose. Being an intrinsic profile in the communication between a GPU and a CPU, the pattern of graphics interrupts …
Secure And Verifiable Inference In Deep Neural Networks,
2020
University of Electronic Science and Technology of China
Secure And Verifiable Inference In Deep Neural Networks, Guowen Xu, Hongwei Li, Hao Ren, Jianfei Sun, Shengmin Xu, Jianting Ning, Haoming Yang, Kan Yang, Robert H. Deng
Research Collection School Of Computing and Information Systems
Outsourced inference service has enormously promoted the popularity of deep learning, and helped users to customize a range of personalized applications. However, it also entails a variety of security and privacy issues brought by untrusted service providers. Particularly, a malicious adversary may violate user privacy during the inference process, or worse, return incorrect results to the client through compromising the integrity of the outsourced model. To address these problems, we propose SecureDL to protect the model’s integrity and user’s privacy in Deep Neural Networks (DNNs) inference process. In SecureDL, we first transform complicated non-linear activation functions of DNNs to low-degree …
A Deep Learning Framework Supporting Model Ownership Protection And Traitor Tracing,
2020
University of Electronic Science and Technology of China
A Deep Learning Framework Supporting Model Ownership Protection And Traitor Tracing, Guowen Xu, Hongwei Li, Yuan Zhang, Xiaodong Lin, Robert H. Deng, Xuemin (Sherman) Shen
Research Collection School Of Computing and Information Systems
Cloud-based deep learning (DL) solutions have been widely used in applications ranging from image recognition to speech recognition. Meanwhile, as commercial software and services, such solutions have raised the need for intellectual property rights protection of the underlying DL models. Watermarking is the mainstream of existing solutions to address this concern, by primarily embedding pre-defined secrets in a model's training process. However, existing efforts almost exclusively focus on detecting whether a target model is pirated, without considering traitor tracing. In this paper, we present SecureMark_DL, which enables a model owner to embed a unique fingerprint for every customer within parameters …
Secure Unlinkability Schemes For Privacy Preserving Data Publishing In Weighted Social Networks,
2020
Universiti Malaya
Secure Unlinkability Schemes For Privacy Preserving Data Publishing In Weighted Social Networks, Chong Kah Meng
Student Works (2020-2029)
Preserving privacy of users has been one of the important research issues in social networks. Social networks contain sensitive personal information that are often released for business and research purposes. The privacy of a user can be breached if the data are not released in an anonymized form. In this thesis, we address edge weight disclosure, link disclosure and identity disclosure problems in publishing weighted network data. To counter these privacy risks while preserving high utility of the published data, we define two key privacy properties, namely edge weight unlinkability and node unlinkability. We design two novel anonymization schemes namely …
Moving Target Network Steganography,
2020
Rowan University
Moving Target Network Steganography, Tapan Soni
Theses and Dissertations
A branch of information hiding that has gained traction in recent years is network steganography. Network steganography uses network protocols are carriers to hide and transmit data. Storage channel network steganography manipulates values in protocol header and data fields and stores covert data inside them. The timing channel modulates the timing of events in the protocol to transfer covert information. Many current storage channel network steganography methods have low bandwidths and they hide covert data directly into the protocol which allows discoverers of the channel to read the confidential information. A new type of storage channel network steganography method is …
An Analysis Of Technological Components In Relation To Privacy In A Smart City,
2020
James Madison University
An Analysis Of Technological Components In Relation To Privacy In A Smart City, Kayla Rutherford, Ben Lands, A. J. Stiles
James Madison Undergraduate Research Journal (JMURJ)
A smart city is an interconnection of technological components that store, process, and wirelessly transmit information to enhance the efficiency of applications and the individuals who use those applications. Over the course of the 21st century, it is expected that an overwhelming majority of the world’s population will live in urban areas and that the number of wireless devices will increase. The resulting increase in wireless data transmission means that the privacy of data will be increasingly at risk. This paper uses a holistic problem-solving approach to evaluate the security challenges posed by the technological components that make up a …
Proposal For The Development And Addition Of A Cybersecurity Assessment Section Into Technology Involving Global Public Health,
2020
Bridgewater State University
Proposal For The Development And Addition Of A Cybersecurity Assessment Section Into Technology Involving Global Public Health, Stanley Mierzwa, Saumya Ramarao, Jung Ah Yun, Bok Gyo Jeong
International Journal of Cybersecurity Intelligence & Cybercrime
This paper discusses and proposes the inclusion of a cyber or security risk assessment section during the course of public health initiatives involving the use of information and communication computer technology. Over the last decade, many public health research efforts have included information technologies such as Mobile Health (mHealth), Electronic Health (eHealth), Telehealth, and Digital Health to assist with unmet global development health needs. This paper provides a background on the lack of documentation on cybersecurity risks or vulnerability assessments in global public health areas. This study suggests existing frameworks and policies be adopted for public health. We also propose …
Book Review: Computer Capers: Tales Of Electronic Thievery, Embezzlement, And Fraud. By Thomas Whiteside,
2020
Bridgewater State University
Book Review: Computer Capers: Tales Of Electronic Thievery, Embezzlement, And Fraud. By Thomas Whiteside, Brian Nussbaum
International Journal of Cybersecurity Intelligence & Cybercrime
No abstract provided.
Toward Mitigating, Minimizing, And Preventing Cybercrimes And Cybersecurity Risks,
2020
Bridgewater State University
Toward Mitigating, Minimizing, And Preventing Cybercrimes And Cybersecurity Risks, Claire Seungeun Lee
International Journal of Cybersecurity Intelligence & Cybercrime
Cybercrime and cybersecurity are emerging fields of research, shaped by technological developments. Scholars in these interconnected fields have studied different types of cybercrimes as well as victimization and offending. Increasingly, some of these scholars have focused on the ways in which cybercrimes can be mitigated, minimized, and even prevented. However, such strategies are often difficult to achieve in reality due to the human and technical factors surrounding cybercrimes. In this issue of the International Journal of Cybersecurity Intelligence and Cybercrime, three papers adequately address such challenges using college student samples and nationally representative samples, as well as a framework through …
Cyber-Situational Crime Prevention And The Breadth Of Cybercrimes Among Higher Education Institutions,
2020
Bridgewater State University
Cyber-Situational Crime Prevention And The Breadth Of Cybercrimes Among Higher Education Institutions, Sinchul Back, Jennifer Laprade
International Journal of Cybersecurity Intelligence & Cybercrime
Academic institutions house enormous amounts of critical information from social security numbers of students to proprietary research data. Thus, maintaining up to date cybersecurity practices to protect academic institutions’ information and facilities against cyber-perpetrators has become a top priority. The purpose of this study is to assess common cybersecurity measures through a situational crime prevention (SCP) theoretical framework. Using a national data set of academic institutions in the United States, this study investigates the link between common cybersecurity measures, crime prevention activities, and cybercrimes. By focusing on the conceptualization of cybersecurity measures as SCP techniques, this study also offers the …
The Effects Of Self-Control On The Cyber Victim-Offender Overlap,
2020
Bridgewater State University
The Effects Of Self-Control On The Cyber Victim-Offender Overlap, Brooke Nodeland
International Journal of Cybersecurity Intelligence & Cybercrime
Increasingly, the overlap between victims and offenders has received empirical attention with regard to traditional forms of deviance. More recently, the growth of cyber offending has led to a need to examine whether traditional criminological theories can be used to explain these crimes in the same manner as traditional offenses. However, limited attention has been given to victim-offender overlap in cyber-offending. The current study uses a sample of American college students to examine the influence of self-control on cyber offending, cyber victimization, and the cyber victim-offender overlap. The results indicate that low self-control significantly predicts participation in cyber offending as …
A Framework For Identifying Host-Based Artifacts In Dark Web Investigations,
2020
Dakota State University
A Framework For Identifying Host-Based Artifacts In Dark Web Investigations, Arica Kulm
Masters Theses & Doctoral Dissertations
The dark web is the hidden part of the internet that is not indexed by search engines and is only accessible with a specific browser like The Onion Router (Tor). Tor was originally developed as a means of secure communications and is still used worldwide for individuals seeking privacy or those wanting to circumvent restrictive regimes. The dark web has become synonymous with nefarious and illicit content which manifests itself in underground marketplaces containing illegal goods such as drugs, stolen credit cards, stolen user credentials, child pornography, and more (Kohen, 2017). Dark web marketplaces contribute both to illegal drug usage …
