Information Security Commons^™

Crowdbc: A Blockchain-Based Decentralized Framework For Crowdsourcing, Ming Li, Jian Weng, Anjia Yang, Wei Lu, Yue Zhang, Lin Hou, Jiannan Liu, Yang Xiang, Robert H. Deng

Research Collection School Of Computing and Information Systems

Crowdsourcing systems which utilize the human intelligence to solve complex tasks have gained considerable interest and adoption in recent years. However, the majority of existing crowdsourcing systems rely on central servers, which are subject to the weaknesses of traditional trust-based model, such as single point of failure. They are also vulnerable to distributed denial of service (DDoS) and Sybil attacks due to malicious users involvement. In addition, high service fees from the crowdsourcing platform may hinder the development of crowdsourcing. How to address these potential issues has both research and substantial value. In this paper, we conceptualize a blockchain-based decentralized …

Key-Insulated And Privacy-Preserving Signature Scheme With Publicly Derived Public Key, Zhen Liu, Guomin Yang, Duncan S. Wong, Khoa Nguyen, Huaxiong Wang

Research Collection School Of Computing and Information Systems

Since the introduction of Bitcoin in 2008, cryptocurrency has been undergoing a quick and explosive development. At the same time, privacy protection, one of the key merits of cryptocurrency, has attracted much attention by the community. A deterministic wallet algorithm and a stealth address algorithm have been widely adopted in the community, due to their virtues on functionality and privacy protection, which come from a key derivation mechanism that an arbitrary number of derived keys can be generated from a master key. However, these algorithms suffer a vulnerability. In particular, when a minor fault happens (say, one derived key is …

Lightweight Privacy-Preserving Ensemble Classification For Face Recognition, Zhuo Ma, Yang Liu, Ximeng Liu, Jianfeng Ma, Kui Ren

Research Collection School Of Computing and Information Systems

The development of machine learning technology and visual sensors is promoting the wider applications of face recognition into our daily life. However, if the face features in the servers are abused by the adversary, our privacy and wealth can be faced with great threat. Many security experts have pointed out that, by 3-D-printing technology, the adversary can utilize the leaked face feature data to masquerade others and break the E-bank accounts. Therefore, in this paper, we propose a lightweight privacy-preserving adaptive boosting (AdaBoost) classification framework for face recognition (POR) based on the additive secret sharing and edge computing. First, we …

The Performance Cost Of Security, Lucy R. Bowen

Master's Theses

Historically, performance has been the most important feature when optimizing computer hardware. Modern processors are so highly optimized that every cycle of computation time matters. However, this practice of optimizing for performance at all costs has been called into question by new microarchitectural attacks, e.g. Meltdown and Spectre. Microarchitectural attacks exploit the effects of microarchitectural components or optimizations in order to leak data to an attacker. These attacks have caused processor manufacturers to introduce performance impacting mitigations in both software and silicon.

To investigate the performance impact of the various mitigations, a test suite of forty-seven different tests was created. …

Hacking The Extended Mind: The Security Implications Of The New Metaphysics, Robin L. Zebrowski

Computer Ethics - Philosophical Enquiry (CEPE) Proceedings

Computer security expert Paul Syverson has argued that there is a computer security equivalent of gaslighting: where a clever adversary could convince some system that some component that is not really a part of the system is in fact a part of the system. If non-biological items from our environments (or even pieces of our environments themselves) can be part of our minds (the standard Extended Mind hypothesis, EM), they are therefore part of our selves, and therefore subject to Syverson’s worry about boundary in a way that has not been explored before. If some version of EM holds, then …

What To Do When Privacy Is Gone, James Brusseau

Computer Ethics - Philosophical Enquiry (CEPE) Proceedings

Today’s ethics of privacy is largely dedicated to defending personal information from big data technologies. This essay goes in the other direction. It considers the struggle to be lost, and explores two strategies for living after privacy is gone. First, total exposure embraces privacy’s decline, and then contributes to the process with transparency. All personal information is shared without reservation. The resulting ethics is explored through a big data version of Robert Nozick’s Experience Machine thought experiment. Second, transient existence responds to privacy’s loss by ceaselessly generating new personal identities, which translates into constantly producing temporarily unviolated private information. The …

Responding To Some Challenges Posed By The Re-Identification Of Anonymized Personal Data, Herman T. Tavani, Frances S. Grodzinsky

Computer Ethics - Philosophical Enquiry (CEPE) Proceedings

In this paper, we examine a cluster of ethical controversies generated by the re-identification of anonymized personal data in the context of big data analytics, with particular attention to the implications for personal privacy. Our paper is organized into two main parts. Part One examines some ethical problems involving re-identification of personally identifiable information (PII) in large data sets. Part Two begins with a brief description of Moor and Weckert’s Dynamic Ethics (DE) and Nissenbaum’s Contextual Integrity (CI) Frameworks. We then investigate whether these frameworks, used together, can provide us with a more robust scheme for analyzing privacy concerns that …

Difference Between Algorithmic Processing And The Process Of Lifeworld (Lebenswelt), Domenico Schneider

Computer Ethics - Philosophical Enquiry (CEPE) Proceedings

The following article compares the temporality of the life-world with the digital processing. The temporality of the life-world is determined to be stretched and spontaneous. The temporality of the digital is given by discrete step-by-step points of time. Most ethical issues can be traced back to a mismatch of these two ways of processing. This creates a foundation for the ethics of the digital processing. Methodologically, phenomenological considerations are merged with media-philosophical considerations in the article.

Information Privacy: Not Just Gdpr, Danilo Bruschi

Computer Ethics - Philosophical Enquiry (CEPE) Proceedings

The "information rush" which is characterizing the current phase of the information age calls for actions aimed at enforcing the citizens' right to privacy. Since the entire information life-cycle (collection, manipulation, storing) is now carried out by digital technologies, most of such actions consists of the adoption of severe measures (both organizational and technological) aimed at improving the security of computer systems, as in the case of the EU General Data Protection Regulation. Usually, data processors which comply with these requirements are exempted by any other duty. Unfortunately recent trends in the computer attack field show that even the adoption …

Keeping Anonymity At The Consumer Behavior On The Internet: Proof Of Sacrifice, Sachio Horie

Computer Ethics - Philosophical Enquiry (CEPE) Proceedings

The evolution of the Internet and AI technology has made it possible for the government and the businesses to keep track of their personal lives. GAFA continues to collect information unintended by the individuals. It is a threat that our privacy is violated in this way. In order to solute such problems, it is important to consider a mechanism that enables us to be peaceful lives while protecting privacy in the Internet society.

This paper focuses on the consumption behavior on the Internet and addresses anonymity. We consider some network protocols that enable sustainable consensus by combining anonymity methods such …

Legal And Technical Issues For Text And Data Mining In Greece, Maria Kanellopoulou - Botti, Marinos Papadopoulos, Christos Zampakolas, Paraskevi Ganatsiou

Computer Ethics - Philosophical Enquiry (CEPE) Proceedings

Web harvesting and archiving pertains to the processes of collecting from the web and archiving of works that reside on the Web. Web harvesting and archiving is one of the most attractive applications for libraries which plan ahead for their future operation. When works retrieved from the Web are turned into archived and documented material to be found in a library, the amount of works that can be found in said library can be far greater than the number of works harvested from the Web. The proposed participation in the 2019 CEPE Conference aims at presenting certain issues related to …

The Right To Human Intervention: Law, Ethics And Artificial Intelligence, Maria Kanellopoulou - Botti, Fereniki Panagopoulou, Maria Nikita, Anastasia Michailaki

Computer Ethics - Philosophical Enquiry (CEPE) Proceedings

The paper analyses the new right of human intervention in use of information technology, automatization processes and advanced algorithms in individual decision-making activities. Art. 22 of the new General Data Protection Regulation (GDPR) provides that the data subject has the right not to be subject to a fully automated decision on matters of legal importance to her interests, hence the data subject has a right to human intervention in this kind of decisions.

On The Responsibility For Uses Of Downstream Software, Marty J. Wolf, Keith W. Miller, Frances S. Grodzinsky

Computer Ethics - Philosophical Enquiry (CEPE) Proceedings

In this paper we explore an issue that is different from whether developers are responsible for the direct impact of the software they write. We examine, instead, in what ways, and to what degree, developers are responsible for the way their software is used “downstream.” We review some key scholarship analyzing responsibility in computing ethics, including some recent work by Floridi. We use an adaptation of a mechanism developed by Floridi to argue that there are features of software that can be used as guides to better distinguish situations where a software developer might share in responsibility for the software’s …

Sql Injection Detection Using Machine Learning, Sonali Mishra

Master's Projects

Sharing information over the Internet over multiple platforms and web-applications has become a quite common phenomenon in the recent times. The web-based applications that accept critical information from users store this information in databases. These applications and the databases connected to them are susceptible to all kinds of information security threats due to being accessible through the Internet. The threats include attacks such as Cross Side Scripting (CSS), Denial of Service Attack (DoS0, and Structured Query Language (SQL) Injection attacks. SQL Injection attacks fall under the top ten vulnerabilities when we talk about web-based applications. Through this kind of attack, …

Intelligent Log Analysis For Anomaly Detection, Steven Yen

Master's Projects

Computer logs are a rich source of information that can be analyzed to detect various issues. The large volumes of logs limit the effectiveness of manual approaches to log analysis. The earliest automated log analysis tools take a rule-based approach, which can only detect known issues with existing rules. On the other hand, anomaly detection approaches can detect new or unknown issues. This is achieved by looking for unusual behavior different from the norm, often utilizing machine learning (ML) or deep learning (DL) models. In this project, we evaluated various ML and DL techniques used for log anomaly detection. We …

Breaking Audio Captcha Using Machine Learning/Deep Learning And Related Defense Mechanism, Heemany Shekhar

Master's Projects

CAPTCHA is a web-based authentication method used by websites to distinguish between humans (valid users) and bots(attackers). Audio captcha is an accessible captcha meant for the visually disabled section of users such as color-blind, blind, near-sighted users. In this project, I analyzed the security of audio captchas from attacks that employ machine learning and deep learning models. Audio captchas of varying lengths (5, 7 and 10) and varying background noise (no noise, medium noise or high noise) were analyzed. I found that audio captchas with no background noise or medium background noise were easily attacked with 99% - 100% accuracy. …

Measuring Malware Evolution Using Support Vector Machines, Mayuri Wadkar

Master's Projects

Malware is software that is designed to do harm to computer systems. Malware often evolves over a period of time as malware developers add new features and fix bugs. Thus, malware samples from the same family from different time periods can exhibit significantly different behavior. Differences between malware samples within a single family can originate from various code modifications designed to evade signature-based detection or changes that are made to alter the functionality of the malware itself. In this research, we apply feature ranking based on linear support vector machine (SVM) weights to identify, quantify, and track changes within malware …

Malware Analysis On Pdf, Shubham Shashishekhar Pachpute

Master's Projects

Cyber-attacks are growing day by day and attackers are finding new techniques to cause harm to their target by spreading worms and malware. In the world of innovations and new technologies coming out every day, it creates a possibility of attacking a system and exploiting the vulnerabilities present in the system. One of the methods used for the spread of malware is the Portable Document Format (PDF) files. Due to the flexible nature of these files, it is becoming a sweet spot for the attackers to embed the malware easily into the PDF files. In this report, we are going …

Contract Builder Ethereum Application, Colin M. Fowler

Master's Projects

Developments in Blockchain, smart contract, and decentralized application (“dApps”) technology have enabled new types of software that can improve efficiency within law firms by increasing speed at which attorneys may draft and execute contracts. Smart contracts and dApps are self-executing software that reside on a blockchain. Custom smart contracts can be built in a modular manner in order to emulate contracts that are commonly generated and executed in law firms. Such contracts include those for the transfer of services, goods, and title. This article explores exactly how implementations of smart contracts for law firms may look.

Javascript Metamorphic Malware Detection Using Machine Learning Techniques, Aakash Wadhwani

Master's Projects

Various factors like defects in the operating system, email attachments from unknown sources, downloading and installing a software from non-trusted sites make computers vulnerable to malware attacks. Current antivirus techniques lack the ability to detect metamorphic viruses, which vary the internal structure of the original malware code across various versions, but still have the exact same behavior throughout. Antivirus software typically relies on signature detection for identifying a virus, but code morphing evades signature detection quite effectively.

JavaScript is used to generate metamorphic malware by changing the code’s Abstract Syntax Tree without changing the actual functionality, making it very difficult …