Information Security Commons^™

Transcriptase–Light: A Polymorphic Virus Construction Kit, Saurabh Borwankar

Master's Projects

Many websites use JavaScript to display dynamic and interactive content. Hence, attackers are developing JavaScript–based malware. In this paper, we focus on Transcriptase JavaScript malware.

The high–level and dynamic nature of the JavaScript language helps malware writers to create polymorphic and metamorphic malware using obfuscation techniques. These types of malware change their internal structure on each infection, making them difficult to detect with traditional methods. These types of malware can be detected using machine learning methods.

This project creates Transcriptase–Light, a new polymorphic construction kit. We perform an experiment with the Transcriptase–Light against a hidden Markov model. Our experiment shows …

Dynamic Information Flow Analysis In Ruby, Vigneshwari Chandrasekaran

Master's Projects

With the rapid increase in usage of the internet and online applications, there is a huge demand for applications to handle data privacy and integrity. Applications are already complex with business logic; adding the data safety logic would make them more complicated. The more complex the code becomes, the more possibilities it opens for security-critical bugs. To solve this conundrum, we can push this data safety handling feature to the language level rather than the application level. With a secure language, developers can write their application without having to worry about data security.

This project introduces dynamic information flow analysis …

Image Spam Detection, Aneri Chavda

Master's Projects

Email is one of the most common forms of digital communication. Spam can be de ned as unsolicited bulk email, while image spam includes spam text embedded inside images. Image spam is used by spammers so as to evade text-based spam lters and hence it poses a threat to email based communication. In this research, we analyze image spam detection methods based on various combinations of image processing and machine learning techniques.

Analysis Of Periodicity In Botnets, Prathiba Nagarajan

Master's Projects

A botnet consists of a network of infected computers which are controlled re- motely via a command and control (C&C) server. A typical botnet requires frequent communication between the C&C server and the infected nodes. Previous approaches to detecting botnets have employed various machine learning techniques, based on features extracted from network tra c. In this research, we carefully analyze the pe- riodicity of tra c as a means for detecting a variety of botnets by applying machine learning to publicly available datasets.

Towards Real-Time Volatile Memory Forensics: Frameworks, Methods, And Analysis, Joseph T. Sylve

LSU New Orleans Theses and Dissertations

Memory forensics (or memory analysis) is a relatively new approach to digital forensics that deals exclusively with the acquisition and analysis of volatile system memory. Because each function performed by an operating system must utilize system memory, analysis of this memory can often lead to a treasure trove of useful information for forensic analysts and incident responders. Today’s forensic investigators are often subject to large case backlogs, and incident responders must be able to quickly identify the source and cause of security breaches. In both these cases time is a critical factor. Unfortunately, today’s memory analysis tools can take many …

Development Of Peer Instruction Material For A Cybersecurity Curriculum, William Johnson

LSU New Orleans Theses and Dissertations

Cybersecurity classes focus on building practical skills alongside the development of the open mindset that is essential to tackle the dynamic cybersecurity landscape. Unfortunately, traditional lecture-style teaching is insufficient for this task. Peer instruction is a non-traditional, active learning approach that has proven to be effective in computer science courses. The challenge in adopting peer instruction is the development of conceptual questions. This thesis presents a methodology for developing peer instruction questions for cybersecurity courses, consisting of four stages: concept identification, concept trigger, question presentation, and development. The thesis analyzes 279 questions developed over two years for three cybersecurity courses: …

Malware Analysis And Privacy Policy Enforcement Techniques For Android Applications, Aisha Ibrahim Ali-Gombe

LSU New Orleans Theses and Dissertations

The rapid increase in mobile malware and deployment of over-privileged applications over the years has been of great concern to the security community. Encroaching on user’s privacy, mobile applications (apps) increasingly exploit various sensitive data on mobile devices. The information gathered by these applications is sufficient to uniquely and accurately profile users and can cause tremendous personal and financial damage.

On Android specifically, the security and privacy holes in the operating system and framework code has created a whole new dynamic for malware and privacy exploitation. This research work seeks to develop novel analysis techniques that monitor Android applications for …

Downstream Competence Challenges And Legal/Ethical Risks In Digital Forensics, Michael M. Losavio, Antonio Losavio

Annual ADFSL Conference on Digital Forensics, Security and Law

Forensic practice is an inherently human-mediated system, from processing and collection of evidence to presentation and judgment. This requires attention to human factors and risks which can lead to incorrect judgments and unjust punishments.

For digital forensics, such challenges are magnified by the relative newness of the discipline and the use of electronic evidence in forensic proceedings. Traditional legal protections, rules of procedure and ethics rules mitigate these challenges. Application of those traditions better ensures forensic findings are reliable. This has significant consequences where findings may impact a person's liberty or property, a person's life or even the political direction …

Detecting Deception In Asynchronous Text, Fletcher Glancy

Annual ADFSL Conference on Digital Forensics, Security and Law

Glancy and Yadav (2010) developed a computational fraud detection model (CFDM) that successfully detected financial reporting fraud in the text of the management’s discussion and analysis (MDA) portion of annual filings with the United States Securities and Exchange Commission (SEC). This work extends the use of the CFDM to additional genres, demonstrates the generalizability of the CFDM and the use of text mining for quantitatively detecting deception in asynchronous text. It also demonstrates that writers committing fraud use words differently from truth tellers.

Understanding Deleted File Decay On Removable Media Using Differential Analysis, James H. Jones Jr, Anurag Srivastava, Josh Mosier, Connor Anderson, Seth Buenafe

Annual ADFSL Conference on Digital Forensics, Security and Law

Digital content created by picture recording devices is often stored internally on the source device, on either embedded or removable media. Such storage media is typically limited in capacity and meant primarily for interim storage of the most recent image files, and these devices are frequently configured to delete older files as necessary to make room for new files. When investigations involve such devices and media, it is sometimes these older deleted files that would be of interest. It is an established fact that deleted file content may persist in part or in its entirety after deletion, and identifying the …

Development Of A Professional Code Of Ethics In Digital Forensics, Kathryn C. Seigfried-Spellar, Marcus Rogers, Danielle M. Crimmins 2184089

Annual ADFSL Conference on Digital Forensics, Security and Law

Academics, government officials, and practitioners suggest the field of digital forensics is in need of a professional code of ethics. In response to this need, the authors developed and proposed a professional code of ethics in digital forensics. The current paper will discuss the process of developing the professional code of ethics, which included four sets of revisions based on feedback and suggestions provided by members of the digital forensic community. The final version of the Professional Code of Ethics in Digital Forensics includes eight statements, and we hope this is a step toward unifying the field of digital forensics …

Fast Filtering Of Known Png Files Using Early File Features, Sean Mckeown, Gordon Russell, Petra Leimich

Annual ADFSL Conference on Digital Forensics, Security and Law

A common task in digital forensics investigations is to identify known contraband images. This is typically achieved by calculating a cryptographic digest, using hashing algorithms such as SHA256, for each image on a given media, comparing individual digests with a database of known contraband. However, the large capacities of modern storage media, and increased time pressure on forensics examiners, necessitates that more efficient processing mechanisms be developed. This work describes a technique for creating signatures for images of the PNG format which only requires a tiny fraction of the file to effectively distinguish between a large number of images. Highly …

Detect Kernel-Mode Rootkits Via Real Time Logging & Controlling Memory Access, Satoshi Tanda, Irvin Homem, Igor Korkin

Annual ADFSL Conference on Digital Forensics, Security and Law

Modern malware and spyware platforms attack existing antivirus solutions and even Microsoft PatchGuard. To protect users and business systems new technologies developed by Intel and AMD CPUs may be applied. To deal with the new malware we propose monitoring and controlling access to the memory in real time using Intel VT-x with EPT. We have checked this concept by developing MemoryMonRWX, which is a bare-metal hypervisor. MemoryMonRWX is able to track and trap all types of memory access: read, write, and execute. MemoryMonRWX also has the following competitive advantages: fine-grained analysis, support of multi-core CPUs and 64-bit Windows 10. MemoryMonRWX …

Harnessing Predictive Models For Assisting Network Forensic Investigations Of Dns Tunnels, Irvin Homem, Panagiotis Papapetrou

Annual ADFSL Conference on Digital Forensics, Security and Law

In recent times, DNS tunneling techniques have been used for malicious purposes, however network security mechanisms struggle to detect them. Network forensic analysis has been proven effective, but is slow and effort intensive as Network Forensics Analysis Tools struggle to deal with undocumented or new network tunneling techniques. In this paper, we present a machine learning approach, based on feature subsets of network traffic evidence, to aid forensic analysis through automating the inference of protocols carried within DNS tunneling techniques. We explore four network protocols, namely, HTTP, HTTPS, FTP, and POP3. Three features are extracted from the DNS tunneled traffic: …

An Accidental Discovery Of Iot Botnets And A Method For Investigating Them With A Custom Lua Dissector, Max Gannon, Gary Warner, Arsh Arora

Annual ADFSL Conference on Digital Forensics, Security and Law

This paper presents a case study that occurred while observing peer-to-peer network communications on a botnet monitoring station and shares how tools were developed to discover what ultimately was identified as Mirai and many related IoT DDOS Botnets. The paper explains how researchers developed a customized protocol dissector in Wireshark using the Lua coding language, and how this enabled them to quickly identify new DDOS variants over a five month period of study.

Kelihos Botnet: A Never-Ending Saga, Arsh Arora, Max Gannon, Gary Warner

Annual ADFSL Conference on Digital Forensics, Security and Law

This paper investigates the recent behavior of the Kelihos botnet, a spam-sending botnet that accounts for many millions of emails sent each day. The paper demonstrates how a team of students are able to perform a longitudinal malware study, making significant observations and contributions to the understanding of a major botnet using tools and techniques taught in the classroom. From this perspective the paper has two objectives: encouragement and observation. First, by providing insight into the methodology and tools used by student researchers to document and understand a botnet, the paper strives to embolden other academic programs to follow a …

Lightweight Data Aggregation Scheme Against Internal Attackers In Smart Grid Using Elliptic Curve Cryptography, Debiao He, Sherali Zeadally, Huaqun Wang, Qin Liu

Information Science Faculty Publications

Recent advances of Internet and microelectronics technologies have led to the concept of smart grid which has been a widespread concern for industry, governments, and academia. The openness of communications in the smart grid environment makes the system vulnerable to different types of attacks. The implementation of secure communication and the protection of consumers’ privacy have become challenging issues. The data aggregation scheme is an important technique for preserving consumers’ privacy because it can stop the leakage of a specific consumer’s data. To satisfy the security requirements of practical applications, a lot of data aggregation schemes were presented over the …

Ispy: Threats To Individual And Institutional Privacy In The Digital World, Lori Andrews

All Faculty Scholarship

What type of information is collected, who is viewing it, and what law librarians can do to protect their patrons and institutions.

Mining Software Repositories For Automatic Software Bug Management From Bug Triaging To Patch Backporting, Yuan Tian

Dissertations and Theses Collection

Software systems are often released with bugs due to system complexity and inadequate testing. Bug resolving process plays an important role in development and evolution of software systems because developers could collect a considerable number of bugs from users and testers daily. For instance, during September 2015, the Eclipse project received approximately 2,500 bug reports, averaging 80 new reports each day. To help developers effectively address and manage bugs, bug tracking systems such as Bugzilla and JIRA are adopted to manage the life cycle of a bug through bug report. Since most of the information related to bugs are stored …

Umass Memorial Healthcare Information System Job Ladder, Matthew Simoncini, Vamsi Kavuru, Antariksh Nanda, Tahaseen Mahaboob Basha, Vikram Patil

School of Professional Studies

The capstone project report emphasizes the importance of a job ladder and the need of an hour to implement it at UMASS Memorial health care. The scope of this project is to create a well-established job ladder at UMASS with pre-defined standards on job levels related to Information Technology department that would facilitate in hiring, developing and promoting employees at various stages.