Information Security Commons^™

A Fully Distributed Hierarchical Attribute-Based Encryption Scheme, Ali Mohammad, Javad Mohajeri, Ximeng Liu, Ximeng Liu

Research Collection School Of Computing and Information Systems

With the development of cloud computing, many enterprises have been interested in outsourcing their data to cloud servers to decrease IT costs and rise capabilities of provided services. To afford confidentiality and fine-grained data access control, attribute-based encryption (ABE) was proposed and used in several cloud storage systems. However, scalability and flexibility in key delegation and user revocation mechanisms are primary issues in ABE systems. In this paper, we introduce the concept of a fully distributed revocable ciphertext-policy hierarchical ABE (FDR-CP-HABE) and design the first FDR-CP-HABE scheme. Our scheme offers a high level of flexibility and scalability in the key …

Cyber Security’S Influence On Modern Society, Nicholas Vallarelli

Honors College Theses

The world of cyber security is evolving every day, and cyber-criminals are trying to take advantage of it to gain as much money and power as possible. As the Internet continues to grow, more people around the world join the Internet. The purpose of this is to see how much of an importance cyber security has and how cyber-criminals are able to utilize the cyberworld for their own personal gain. Research has been done on how the cyberworld got where it is today. Additionally, individual research has been done in an effort to learn how to hack. A hack lab …

A Lightweight Privacy-Preserving Cnn Feature Extraction Framework For Mobile Sensing, Kai Huang, Ximeng Liu, Shaojing Fu, Deke Guo, Ming Xu

Research Collection School Of Computing and Information Systems

The proliferation of various mobile devices equipped with cameras results in an exponential growth of the amount of images. Recent advances in the deep learning with convolutional neural networks (CNN) have made CNN feature extraction become an effective way to process these images. However, it is still a challenging task to deploy the CNN model on the mobile sensors, which are typically resource-constrained in terms of the storage space, the computing capacity, and the battery life. Although cloud computing has become a popular solution, data security and response latency are always the key issues. Therefore, in this paper, we propose …

The Future Of Work Now: Cyber Threat Attribution At Fireeye, Thomas H. Davenport, Steven M. Miller

Research Collection School Of Computing and Information Systems

One of the most frequently-used phrases at business events these days is “the future of work.” It’s increasingly clear that artificial intelligence and other new technologies will bring substantial changes in work tasks and business processes. But while these changes are predicted for the future, they’re already present in many organizations for many different jobs. The job and incumbent described below is an example of this phenomenon. It’s a clear example of an existing job that’s been transformed by AI and related tools.

Mitigating Real-Time Relay Phishing Attacks Against Mobile Push Notification Based Two-Factor Authentication Systems, Casey Silver

Masters Theses, 2020-current

This paper explores how existing push notification based two-factor authentication systems are susceptible to real-time man-in-the-middle relay attacks and proposes a system for mitigating such attacks. A fully functional reference system of the proposed mitigation was built and compared to an existing push notification two-factor authentication system while undergoing a real-time man-in-the-middle relay attack. The reference systems used cloud infrastructure for hosting, an Apple iPhone as the notification receiver, and Apple’s push notification service to send notifications. A publicly available tool for conducting real-time man-in-the-middle relay attacks was used to conduct the attacks. The results of the tests were recorded …

Knot Flow Classification And Its Applications In Vehicular Ad-Hoc Networks (Vanet), David Schmidt

Electronic Theses and Dissertations

Intrusion detection systems (IDSs) play a crucial role in the identification and mitigation for attacks on host systems. Of these systems, vehicular ad hoc networks (VANETs) are difficult to protect due to the dynamic nature of their clients and their necessity for constant interaction with their respective cyber-physical systems. Currently, there is a need for a VANET-specific IDS that meets this criterion. To this end, a spline-based intrusion detection system has been pioneered as a solution. By combining clustering with spline-based general linear model classification, this knot flow classification method (KFC) allows for robust intrusion detection to occur. Due its …

Vzwam Web-Based Lookup, Ruben Claudio

Masters Theses & Doctoral Dissertations

This web-based lookup will allow V employees to find territory sales rep much faster. It will simplify the process and eliminate manual processes.

At the moment, a combination of multiple manual processes is needed to find territory sales reps. The company’s CRM does not allow to find rep sales quickly. When an in-house sales representative is talking to a prospect, this sales rep has to go through a few series of steps to find an outside or territory sales rep --which is usually needed to schedule in-person meetings, that results in delays while doing transactions with the prospects. Besides, because …

A Blockchain Approach For Negotiating Trust In Iot, Skailer Knezevic

Theses and Dissertations

“The internet is no longer a web that we connect to. Instead, its a computerized, networked, and interconnected world that we live in. This is the future, and what were calling the Internet of Things.”- Bruce Schneier, 2019 The Internet of Things is becoming a big part of our lives. Every year there are more devices with the capability to connect on the internet and communicate with each other. Today there are over 400 million IoT devices in the world, and this number is predicted to grow to 1.5 billion devices by 2022 [14]. It is becoming more difficult to …

Dynamic Fraud Detection Via Sequential Modeling, Panpan Zheng

Graduate Theses and Dissertations

The impacts of information revolution are omnipresent from life to work. The web services have signicantly changed our living styles in daily life, such as Facebook for communication and Wikipedia for knowledge acquirement. Besides, varieties of information systems, such as data management system and management information system, make us work more eciently. However, it is usually a double-edged sword. With the popularity of web services, relevant security issues are arising, such as fake news on Facebook and vandalism on Wikipedia, which denitely impose severe security threats to OSNs and their legitimate participants. Likewise, oce automation incurs another challenging security issue, …

Data Breach Consequences And Responses: A Multi-Method Investigation Of Stakeholders, Hamid Reza Nikkhah

Graduate Theses and Dissertations

The role of information in today’s economy is essential as organizations that can effectively store and leverage information about their stakeholders can gain an advantage in their markets. The extensive digitization of business information can make organizations vulnerable to data breaches. A data breach is the unauthorized access to sensitive, protected, or confidential data resulting in the compromise of information security. Data breaches affect not only the breached organization but also various related stakeholders. After a data breach, stakeholders of the breached organizations show negative behaviors, which causes the breached organizations to face financial and non-financial costs. As such, the …

Pmkt: Privacy-Preserving Multi-Party Knowledge Transfer For Financial Market Forecasting, Zhuoran Ma, Jianfeng Ma, Yinbin Miao, Kim-Kwang Raymond Choo, Ximeng Liu, Xiangyu Wang, Tengfei Yang

Research Collection School Of Computing and Information Systems

While decision-making task is critical in knowledge transfer, particularly from multi-source domains, existing knowledge transfer approaches are not generally designed to be privacy preserving. This has potential legal and financial implications, particularly in sensitive applications such as financial market forecasting. Therefore, in this paper, we propose a Privacy-preserving Multi-party Knowledge Transfer system (PMKT), based on decision trees, for financial market forecasting. Specifically, in PMKT, we leverage a cryptographic-based model sharing technique to securely outsource knowledge reflected in decision trees of multiple parties, and design a secure computation mechanism to facilitate privacy-preserving knowledge transfer. An encrypted user-submitted request from the target …

Storage Management Strategy In Mobile Phones For Photo Crowdsensing, En Wang, Zhengdao Qu, Xinyao Liang, Xiangyu Meng, Yongjian Yang, Dawei Li, Weibin Meng

Department of Computer Science Faculty Scholarship and Creative Works

In mobile crowdsensing, some users jointly finish a sensing task through the sensors equipped in their intelligent terminals. In particular, the photo crowdsensing based on Mobile Edge Computing (MEC) collects pictures for some specific targets or events and uploads them to nearby edge servers, which leads to richer data content and more efficient data storage compared with the common mobile crowdsensing; hence, it has attracted an important amount of attention recently. However, the mobile users prefer uploading the photos through Wifi APs (PoIs) rather than cellular networks. Therefore, photos stored in mobile phones are exchanged among users, in order to …

Teaching Data Carving Using The Real World Problem Of Text Message Extraction From Unstructured Mobile Device Data Dumps, Gary D. Cantrell, Joan Runs Through

Journal of Digital Forensics, Security and Law

Data carving is a technique used in data recovery to isolate and extract files based on file content without any file system guidance. It is an important part of data recovery and digital forensics, but it is also useful in teaching computer science students about file structure and binary encoding of information especially within a digital forensics program. This work demonstrates how the authors teach data carving using a real world problem they encounter in digital forensics evidence processing involving the extracting of text messages from unstructured small device binary extractions. The authors have used this problem for instruction in …

Cyber-Security Risks Of Fedwire, Mark J. Bilger

Journal of Digital Forensics, Security and Law

This paper will review the risks associated with the Federal Reserve's Fedwire network as a key resource necessary for the efficient function of the American financial system. It will examine the business model of the Fedwire system of real-time interbank transfers, the network characteristics of Fedwire, and the possibility of a successful attack on Fedwire and its potential impact on the U.S. financial system.

Mitigating Safety Concerns And Profit/Production Losses For Chemical Process Control Systems Under Cyberattacks Via Design/Control Methods, Helen Durand, Matthew Wegener

Chemical Engineering and Materials Science Faculty Research Publications

One of the challenges for chemical processes today, from a safety and profit standpoint, is the potential that cyberattacks could be performed on components of process control systems. Safety issues could be catastrophic; however, because the nonlinear systems definition of a cyberattack has similarities to a nonlinear systems definition of faults, many processes have already been instrumented to handle various problematic input conditions. Also challenging is the question of how to design a system that is resilient to attacks attempting to impact the production volumes or profits of a company. In this work, we explore a process/equipment design framework for …

Distributed Denial Of Service Attack Detection, Travis Blue

Master of Science in Information Technology Theses

Distributed Denial of Service (DDoS) attacks on web applications has been a persistent threat. Successful attacks can lead to inaccessible service to legitimate users in time and loss of business reputation. Most research effort on DDoS focused on network layer attacks. Existing approaches on application layer DDoS attack mitigation have limitations such as the lack of detection ability for low rate DDoS and not being able to detect attacks targeting resource files. In this work, we propose DDoS attack detection using concepts from information retrieval and machine learning. We include two popular concepts from information retrieval: Term Frequency (TF)-Inverse Document …

A Comprehensive Cybersecurity Policy For The United States Government According To Cyberattacks And Exploits In The 21st Century, Diana Hallisey

Honors Program Contracts

Adversaries launch cyberattacks or cyber-exploits with contrasting intentions and desired outcomes. A cyberattack is a malicious attempt by a state, third party, or individual to disrupt a computer’s network; whereas, a cyber-exploit is an action that uncovers and steals “confidential” information from a computer’s data. 1 Within this research paper, the main adversary of such cyberattacks and/or exploits will be the nation-state. The victims of these cyberattacks will range from multinational corporations, such as Sony, to nuclear programs in Iran. This essay will focus on four motivations behind such cyberattacks: (1) private sector hacking (the theft of intellectual property) (2) …

Searchbreaches.Me, Ajay Shah, Harshal Patel, Eric Gargiulo

Petersheim Academic Exposition

No abstract provided.

Cybersecurity (Cs 3550): Lecture 11: Identity & Access Management, Michael Whiteman, Nyc Tech-In-Residence Corps

Open Educational Resources

Lecture for the course: CIS 3550: Cybersecurity - "11: Identity & Access Management" delivered at Baruch College in Spring 2020 by Michael Whiteman as part of the Tech-in-Residence Corps program.

Applications Of Machine Learning To Threat Intelligence, Intrusion Detection And Malware, Charity Barker

Senior Honors Theses

Artificial Intelligence (AI) and Machine Learning (ML) are emerging technologies with applications to many fields. This paper is a survey of use cases of ML for threat intelligence, intrusion detection, and malware analysis and detection. Threat intelligence, especially attack attribution, can benefit from the use of ML classification. False positives from rule-based intrusion detection systems can be reduced with the use of ML models. Malware analysis and classification can be made easier by developing ML frameworks to distill similarities between the malicious programs. Adversarial machine learning will also be discussed, because while ML can be used to solve problems or …