Digital Commons Network^™

Illicit Activity Detection In Large-Scale Dark And Opaque Web Social Networks, Dhara Shah, T. G. Harrison, Christopher B. Freas, David Maimon, Robert W. Harrison

EBCS Articles

Many online chat applications live in a grey area between the legitimate web and the dark net. The Telegram network in particular can aid criminal activities. Telegram hosts “chats” which consist of varied conversations and advertisements. These chats take place among automated “bots” and human users. Classifying legitimate activity from illegitimate activity can aid law enforcement in finding criminals. Social network analysis of Telegram chats presents a difficult problem. Users can change their username or create new accounts. Users involved in criminal activity often do this to obscure their identity. This makes establishing the unique identity behind a given username …

Examining The Crime Prevention Claims Of Crime Prevention Through Environmental Design On System-Trespassing Behaviors: A Randomized Experiment, Daren Fisher, David Maimon, Tamar Berenblum

EBCS Articles

Crime prevention through environmental design (CPTED) is a non-punitive method for reducing crime through the design of the built environment. The relevance of CPTED strategies however is less clear in the context of computing environments. Building upon prior research indicating that computing environments may change computer users’ behaviors, this study tests the effectiveness of CPTED based approaches in mitigating system trespassing events. Findings from this randomized controlled field trial demonstrate that specific CPTED strategies can mitigate hacking events by: reducing the number of concurrent activities on the target computer, attenuating the number of commands typed in the attacked computer, and …

Improving Grading And Feedback Of Programming Assignments Using Version Control: An Experience Report, Jillian Morgan, Michael Weeks

Computer Science Technical Reports

Leaving meaningful, actionable feedback that students will read and, most importantly, follow-up on, is essential for strengthening their programming skills. In addition, being capable with version control platforms, such as git, is a desired skill in industry. Could a marriage between the two, leaving meaningful feedback for student submissions in a version control system, lead them to be better programmers while improving the time and quality of instructors’ feedback? This experience report describes how we used GitHub Classroom for programming assignment submission and assessment in CS2. We provide examples of typical feedback using various assessment mechanisms, describe the process of …

The Restrictive Deterrent Effect Of Warning Messages Sent To Active Romance Fraudsters: An Experimental Approach, Fangzhou Wang, C. Jordan Howell, David Maimon, Scott Jacques

EBCS Articles

Victims of romance fraud experience both a financial and emotional burden. Although multiple studies have offered insight into the correlates of perpetration and victimization, no known study has examined if, and how, romance fraud can be curtailed. The current study uses a randomized experimental design to test the restrictive deterrent effect of warning messages sent to romance fraudsters via email. We find that active romance fraudsters who receive a deterrence message, instead of non-deterrence messages, respond at a lower rate; and, among those who respond, use fewer words and have a lower probability of seeking reply without denying wrongdoing. The …

Situational Awareness And Public Wi-Fi Users' Self-Protective Behaviors, David Maimon, C. Jordan Howell, Scott Jacques, Robert Perkins

EBCS Articles

Accessing public Wi-Fi networks can be as dangerous as it is convenient. People who access a public Wi-Fi network should engage in self-protective behaviors to keep their data safe from malicious actors on the same network as well as persons looking over their shoulder, literally and proverbially. Using two independent research designs, we examined under what circumstances were people more likely to access an unsecured Wi-Fi network and engage in risky behavior on these networks. Findings from the first study, based on survey data, reveal that people who are more situationally aware are less likely to access personal accounts on …

Deterrence In Cyberspace: An Interdisciplinary Review Of The Empirical Literature, David Maimon

EBCS Articles

The popularity of the deterrence perspective across multiple scientific disciplines has sparked a lively debate regarding its relevance in influencing both offenders and targets in cyberspace. Unfortunately, due to the invisible borders between academic disciplines, most of the published literature on deterrence in cyberspace is confined within unique scientific disciplines. This chapter therefore provides an interdisciplinary review of the issue of deterrence in cyberspace. It begins with a short overview of the deterrence perspective, presenting the ongoing debates concerning the relevance of deterrence pillars in influencing cybercriminals’ and cyberattackers’ operations in cyberspace. It then reviews the existing scientific evidence assessing …

Attacking And Securing Beacon-Enabled 802.15.4 Networks, Sang Shin Jung, Marco Valero, Anu G. Bourgeois, Raheem Beyah

EBCS Articles

The IEEE 802.15.4 standard has attracted timecritical applications in wireless sensor networks because of its beacon-enabled mode and guaranteed timeslots (GTSs). However, the GTS management scheme’s security mechanisms still leave the 802.15.4 medium access control vulnerable to attacks. Further, the existing techniques in the literature for securing 802.15.4 networks either focus on nonbeacon-enabled 802.15.4 networks or cannot defend against insider attacks for beacon-enabled 802.15.4 networks. In this paper, we illustrate this by demonstrating attacks on the availability and integrity of the beaconenabled 802.15.4 network. To confirm the validity of the attacks, we implement the attacks using Tmote Sky motes for …

Finding Connected-Dense-Connected Subgraphs And Variants Is Np-Hard, Dhara Shah, Sushil Prasad, Yubao Wu

Computer Science Technical Reports

Finding Connected-Dense-Connected (CDC) subgraphs from Triple Networks is NP-Hard. finding One-Connected-Dense (OCD) sub- graphs from Triple Networks is also NP-Hard. We present formal proofs of these theorems hereby.

Finding Densest Subgraph In A Bi-Partite Graph, Dhara Shah, Sushil Prasad, Danial Aghajarian

Computer Science Technical Reports

Finding the densest subgraph in a bi-partite graph is a polynomial time problem. Also, each bi-partite graph has a densest connected subgraph. In this paper, we first prove that each bi-partite graph has a densest connected subgraph. This proof is different than that of an undirected graph, since our definition of the density is different. We then provide a max-flow min-cut algorithm for finding a densest subgraph of a bi-partite graph and prove te correctness of this binary search algorithm.

An Evidence Based Cybersecurity Approach To Risk Management: Risk Management And "Market For Lemons", David Maimon

EBCS Presentations

No abstract provided.

Website Defacement And Routine Activities: Considering The Importance Of Hackers’ Valuations Of Potential Targets, C. Jordan Howell, George W. Burruss, David Maimon, Shradha Sahani

EBCS Articles

Although a relatively simple form of hacking, website defacement can have severe consequences both for the websites that are attacked and the reputation of their owners. However, criminological research has yet to fully explore the causes and correlates of website defacement. We consider whether variables derived from routine activity theory can be applied to understanding website defacement. Specifically, using a sample of websites that were targeted by hackers in 2017 across the world, we examine the relationship between a country’s structural characteristics and the frequency of website defacement reported for the country. We find that website defacements are less likely …

Digital First: The Ontological Reversal And New Challenges For Is Research, Richard L. Baskerville, Michael D. Myers, Youngjin Yoo

EBCS Articles

The classical view of an information system is that it represents and reflects physical reality. We suggest this classical view is increasingly obsolete: digital technologies are now creating and shaping physical reality. We call this phenomenon the ontological reversal. The ontological reversal is where the digital version is created first, and the physical version second (if needed). This ontological reversal challenges us to think about the role of humans and technology in society. It also challenges us to think about our role as IS scholars in this digital world and what it means for our research agendas.

Online Deception And Situations Conducive To The Progression Of Non-Payment Fraud, David Maimon, Mateus Rennó Santos, Youngsam Park

EBCS Articles

Adopting the criminal event perspective, we explore how online fraudsters make use of urgency cues in their interactions with potential victims throughout the progression of an online nonpayment fraud attempt. Integrating claims from the ‘Interpersonal-Deception Theory’ with situational explanations of crime, we investigate whether fraudsters’ presentations of verbal cues of urgency during the early stages of a criminal event are followed by a consistent presentation of verbal and non-verbal urgency cues. To answer this question, we posted a large number of ‘for-sale’ advertisements over a classified-ad website and interacted with online fraudsters and legitimate users who responded to our ads …

Ssl/Tls Certificates And Their Prevalence On The Dark Web (First Report), David Maimon, Yubao Wu, Michael Mcguire, Nicholas Stubler, Zijie Qui

EBCS Reports

As organizations focus on the digital transformation of their businesses, the importance of encryption as the cornerstone of security and privacy is increasingly vital. In 2018, over 70 percent of internet traffic was encrypted. Experts believe that this figure is expected to rise to 80 percent in 2019 (Google, 2019). Secure Sockets Layer (SSL, an older standard) and Transport Layer Security (TLS, a newer standard) certificates are essential to encryption because they authorize all encrypted communication between machines. SSL/TLS certificates are instrumental in protecting privacy and improving security, providing each machine with a unique machine identity. They control the flow …

Predicting Opioid Epidemic By Using Twitter Data, Yubao Wu, Pavel Skums, Alex Zelikovsky, David Campo Rendon, Xueting Liao

EBCS Proceedings

Opioid crisis was declared as a public health emergency in 2017 by the President of USA. According to the Centers for Disease Control and Prevention, more than 91 Americans die every day from an opioid overdose. Nearly $4B is provided to address the opioid epidemic in the 2018 spending bill and help fulfill the President’s Opioid Initiative.

How to monitor and predict the opioid epidemic accurately and in real time? The traditional methods mainly use the hospital data and usually have a lag of several years. Even though they are accurate, the long lag period prevents us from monitoring and …

High Performance Attack Estimation In Large-Scale Network Flows, Christopher B. Freas, Robert W. Harrison, Yuan Long

EBCS Proceedings

Network based attacks are the major threat to security on the Internet. The volume of traffic and the high variability of the attacks place threat detection squarely in the domain of big data. Conventional approaches are mostly based on signatures. While these are relatively inexpensive computationally, they are inflexible and insensitive to small variations in the attack vector. Therefore we explored the use of machine learning techniques on real flow data. We found that benign traffic could be identified with high accuracy.

Continuous Restricted Boltzmann Machines, Robert W. Harrison

EBCS Articles

Restricted Boltzmann machines are a generative neural network. They summarize their input data to build a probabilistic model that can then be used to reconstruct missing data or to classify new data. Unlike discrete Boltzmann machines, where the data are mapped to the space of integers or bitstrings, continuous Boltzmann machines directly use floating point numbers and therefore represent the data with higher fidelity. The primary limitation in using Boltzmann machines for big-data problems is the efficiency of the training algorithm. This paper describes an efficient deterministic algorithm for training continuous machines.

Smart Signalling For Bicycles Using User Riding Behavior, Nishant Tushar Sinha

Georgia State Undergraduate Research Conference

No abstract provided.

Re-Thinking Online Offenders’ Skram: Individual Traits And Situational Motivations As Additional Risk Factors For Predicting Cyber Attacks, David Maimon, Steve Hinton, Olga Babko-Malaya, Rebecca Cathey

EBCS Proceedings

Cyber security experts in the U.S. and around the globe assess potential threats to their organizations by evaluating potential attackers’ skills, knowledge, resources, access to the target organization and motivation to offend (i.e. SKRAM). Unfortunately, this model fails to incorporate insights regarding online offenders’ traits and the conditions surrounding the development of online criminal event. Drawing on contemporary criminological models, we present a theoretical rationale for revising the SKRAM model. The revised model suggests that in addition to the classical SKRAM components, both individual attributes and certain offline and online circumstances fuel cyber attackers’ motivation to offend, and increase the …

On The Relevance Of Social Media Platforms In Predicting The Volume And Patterns Of Web Defacement Attacks, David Maimon, Andrew Fukuda, Steve Hinton, Olga Babko-Malaya, Rebecca Cathey

EBCS Proceedings

Social media platforms are commonly employed by law enforcement agencies for collecting Open Source Intelligence (OSNIT) on criminals, and assessing the risk they pose to the environment the live in. However, since no prior research has investigated the relationships between hackers’ use of social media platforms and their likelihood to generate cyber-attacks, this practice is less common among Information Technology Teams. Addressing this empirical gap, we draw on the social learning theory and estimate the relationships between hackers’ use of Facebook, Twitter, and YouTube and the frequency of web defacement attacks they generate in different times (weekdays vs. weekends) and …

Designing A Storage Efficient And Faster Heliophysics Events Knowledgebase (Hek), Andre Kenneth Chase Randall, Soukaina Filali, Ahmet Küçük, Shah Hamdi

Georgia State Undergraduate Research Conference

No abstract provided.

A Novel Computational Approach For Reducing False Positives In Text Data Mining, Noah Yasarturk

Georgia State Undergraduate Research Conference

No abstract provided.

Exploring Machine Learning Procedures Via Game Design, Andre Kenneth Chase Randall

Georgia State Undergraduate Research Conference

No abstract provided.

Learning From The Offenders' Perspective On Crime Prevention, Scott Jacques, Elizabeth Bonomo

EBCS Articles

Criminals have a firsthand perspective on why and how to commit crime. In this chapter, we outline and illustrate five ways that offender-based research can be used to inform understanding of crime prevention, more specifically situational crime prevention: namely, (1) by directly determining what works to reduce crime; (2) generating findings that are suggestive of what prevention measures to invent and employ; (3) refining understanding of why a given prevention method reduces crime; (4) figuring out how offenders get around particular prevention measures; and, (5) gathering information on not only the positive but also the unintended, negative outcomes of prevention …

Rechecking The Centrality-Lethality Rule In The Scope Of Protein Subcellular Localization Interaction Networks, Xiaoqing Peng, Jianxin Wang, Jun Wang, Fangxiang Wu, Yi Pan

Computer Science Faculty Publications

Essential proteins are indispensable for living organisms to maintain life activities and play important roles in the studies of pathology, synthetic biology, and drug design. Therefore, besides experiment methods, many computational methods are proposed to identify essential proteins. Based on the centrality-lethality rule, various centrality methods are employed to predict essential proteins in a Protein-protein Interaction Network (PIN). However, neglecting the temporal and spatial features of protein-protein interactions, the centrality scores calculated by centrality methods are not effective enough for measuring the essentiality of proteins in a PIN. Moreover, many methods, which overfit with the features of essential proteins for …

Distributed Power-Line Outage Detection Based On Wide Area Measurement System, Liang Zhao, Wen-Zhan Song

Computer Science Faculty Publications

In modern power grids, the fast and reliable detection of power-line outages is an important functionality, which prevents cascading failures and facilitates an accurate state estimation to monitor the real-time conditions of the grids. However, most of the existing approaches for outage detection suffer from two drawbacks, namely: (i) high computational complexity; and (ii) relying on a centralized means of implementation. The high computational complexity limits the practical usage of outage detection only for the case of single-line or double-line outages. Meanwhile, the centralized means of implementation raises security and privacy issues. Considering these drawbacks, the present paper proposes a …

Accurate Viral Population Assembly From Ultra-Deep Sequencing Data, Serghei Mangul, Nicholas C. Wu, Nicholas Mancuso, Alexander Zelikovskiy, Ren Sun, Eleazar Eskin

Computer Science Faculty Publications

Motivation: Next-generation sequencing technologies sequence viruses with ultra-deep coverage, thus promising to revolutionize our understanding of the underlying diversity of viral populations. While the sequencing coverage is high enough that even rare viral variants are sequenced, the presence of sequencing errors makes it difficult to distinguish between rare variants and sequencing errors. Results: In this article, we present a method to overcome the limitations of sequencing technologies and assemble a diverse viral population that allows for the detection of previously undiscovered rare variants. The proposed method consists of a high-fidelity sequencing protocol and an accurate viral population assembly method, referred …

Cloud Computing For Detecting High-Order Genome-Wide Epistatic Interaction Via Dynamic Clustering, Xuan Guo, Yu Meng, Ning Yu, Yi Pan

Computer Science Faculty Publications

Backgroud: Taking the advan tage of high-throughput single nucleotide polymorphism (SNP) genotyping technology, large genome-wide association studies (GWASs) have been considered to hold promise for unravelling complex relationships between genotype and phenotype. At present, traditional single-locus-based methods are insufficient to detect interactions consisting of multiple-locus, which are broadly existing in complex traits. In addition, statistic tests for high order epistatic interactions with more than 2 SNPs propose computational and analytical challenges because the computation increases exponentially as the cardinality of SNPs combinations gets larger. Results: In this paper, we provide a simple, fast and powerful method using dynamic clustering and …

Identifying Dynamic Protein Complexes Based On Gene Expression Profiles And Ppi Networks, Min Li, Weijie Chen, Jianxin Wang, Fang-Xiang Wu, Yi Pan

Computer Science Faculty Publications

Identification of protein complexes fromprotein-protein interaction networks has become a key problem for understanding cellular life in postgenomic era. Many computational methods have been proposed for identifying protein complexes. Up to now, the existing computational methods are mostly applied on static PPI networks. However, proteins and their interactions are dynamic in reality. Identifying dynamic protein complexes is more meaningful and challenging. In this paper, a novel algorithm, named DPC, is proposed to identify dynamic protein complexes by integrating PPI data and gene expression profiles. According to Core-Attachment assumption, these proteins which are always active in the molecular cycle are regarded …

A Novel Algorithm For Detecting Protein Complexes With The Breadth First Search, Xiwei Tang, Jianxin Wang, Min Li, Yiming He, Yi Pan

Computer Science Faculty Publications

Most biological processes are carried out by protein complexes. A substantial number of false positives of the protein-protein interaction (PPI) data can compromise the utility of the datasets for complexes reconstruction. In order to reduce the impact of such discrepancies, a number of data integration and affinity scoring schemes have been devised. The methods encode the reliabilities (confidence) of physical interactions between pairs of proteins. The challenge now is to identify novel and meaningful protein complexes fromthe weighted PPI network. To address this problem, a novel protein complex mining algorithm ClusterBFS (Cluster with Breadth-First Search) is proposed. Based on the …