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NASA NTRS1989

Stopping computer crimes

Two new books about intrusions and computer viruses remind us that attacks against our computers on networks are the actions of human beings. Cliff Stoll's book about the hacker who spent a year, beginning in Aug. 1986, attempting to use the Lawrence Berkeley Computer as a stepping-stone for access to military secrets is a spy thriller that illustrates the weaknesses of our password systems and the difficulties in compiling evidence against a hacker engaged in espionage. Pamela Kane's book about viruses that attack IBM PC's shows that viruses are the modern version of the old problem of a Trojan horse attack. It discusses the most famous viruses and their countermeasures, and it comes with a floppy disk of utility programs that will disinfect your PC and thwart future attack.

Denning, Peter J.↗

NASA NTRS2004

The Office of Inspector General (OIG)

The NASA Office of Inspector General is the Federal Law Enforcement Agency at NASA which conducts criminal and regulatory investigations in which NASA is a victim. The OIG prevents and detects crime, fiaud, waste and abuse and assists NASA management in promoting economy, efficiency, and effectiveness in its programs and operations. Investigations (OI) and the Office of Audits (OA). The investigations side deals with criminal Investigations, administrative investigations, and civil investigations. The Audits side deals with inspections and assessments as well as the Auditing of NASA Programs and Activities. Our mission at the OIG is to conduct and supervise independent and objective audits and investigations relating to agency programs and operations; to promote economy, effectiveness and efficiency within the agency; to prevent and detect crime, fraud, waste and abuse in agency programs and operations; to review and make recommendations regarding existing and proposed legislation and regulations relating to agency programs and operations. We are also responsible for keeping the agency head and the Congress fully and currently informed of problems in agency programs and operations. deal with False Claims, False Statements, Conspiracy, Theft, Computer Crime, Mail Fraud, the Procurement Integrity Act, the Anti-Kickback Act, as well as noncompliance with NASA Management Instructions, the Federal Acquisition Regulations (FAR), and the Code of Federal Regulations (CFR). Most of the casework that is dealt with in our office is generated through gum shoe work or cases that we generate on our own. These cases can come from Law Enforcement Referrals, GIDEP Reports, EPlMS (NASA Quality System), Defense Contract Audit Agency, Newspaper Articles, and Confidential Information. In many cases, confidentiality is the biggest factor to informants coming forward. We are able to maintain confidentiality because the 01 is independent of NASA Management and doesn t report to the Center Directors, therefore the informant s mangers and supervisors are unaware of the informants actions. The only time when an informant s confidentiality may be compromised is when it is needed in a Court of Law and is released through a Judicial Court Order. During my tenure here at the NASA OIG/OI at Glenn Research Center, I have been involved in many different tasks. They have ranged from updating Suspected Unapproved Parts case files to independently interviewing NASA employees to turn up general background information. The 01 has the duty of informing NASA aeronautical safety managers of potential Nonconforming products. My mission is to compile a database of Nonconformance reports for distribution. The background information that I turn up from my interviews is then used to determine NASA s susceptibility to acceptance of unapproved parts. The IG organization is divided up into two separate disciplines, the Office of 01 investigations primarily focus on violations of Federal laws. Some of these violations

Macisco, Christopher A.↗

DOE OSTI2020

SHARP-Net: Platform for Self-Healing and Attack Resilient PMU Networks

Synchrophasor technology plays a pivotal role in developing the next generation of wide-area monitoring, protection, and control in the smart grid environment. As technology and communications infrastructures evolve, however, so do the attack surfaces in the synchrophasor network that can be exploited by advanced persistent threat (APT) actors to affect power system stability and reliability. In this paper, we propose a novel platform for developing a self-healing and attack-resilient PMU network (SHARP-Net) by instituting a state-of-the-art intrusion detection system (IDS) with an intrusion mitigation system (IMS) and an alert management system (AMS). In particular, the proposed platform detects anomalies during cyberattacks on phasor data concentrators (PDCs) based on the rules defined in the IDS, then the generated alerts are published to the IMS through the AMS. The proposed IMS proceeds to take automated corrective responses to mitigate cyberattacks by reconfiguring the synchrophasor network to isolate the compromised PDCs, and it orchestrates new PDCs to prevent the future propagation of attacks. Further, the IMS restores the system's observability by reconnecting the new PDCs to make the grid attack-resilient. In this work, the SHARP-Net platform is developed by using Python-based libraries, minimega's software-defined network, and virtual machine orchestration. We implement and validate the proposed SHARP-Net architecture by testing a PMU network in the smart grid environment. SHARP-Net showed promising performance in detecting cyberattacks and mitigating them through the network reconfiguration.

computer architecture↗

NASA NTRS1994

How Captain Amerika uses neural networks to fight crime

Artificial neural network models can make amazing computations. These models are explained along with their application in problems associated with fighting crime. Specific problems addressed are identification of people using face recognition, speaker identification, and fingerprint and handwriting analysis (biometric authentication).

Rogers, Steven K.↗

DOE OSTI2021

Incorporating space and time into random forest models for analyzing geospatial patterns of drug-related crime incidents in a major U.S. metropolitan area

The opioid crisis has hit American cities hard, and research on spatial and temporal patterns of drug-related activities including detecting and predicting clusters of crime incidents involving particular types of drugs is useful for distinguishing hot zones where drugs are present that in turn can further provide a basis for assessing and providing related treatment services. In this study, we investigated spatiotemporal patterns of more than 52,000 reported incidents of drug-related crime at block group granularity in Chicago, IL between 2016 and 2019. We applied a space-time analysis framework and machine learning approaches to build a model using training data that identified whether certain locations and built environment and sociodemographic factors were correlated with drug-related crime incident patterns, and establish the top contributing factors that underlaid the trends. Space and time, together with multiple driving factors, were incorporated into a random forest model to analyze these changing patterns. We accommodated both spatial and temporal autocorrelation in the model learning process to assist with capturing the changes over time and tested the capabilities of the space-time random forest model by predicting drug-related activity hot zones. Overall, we focused particularly on crime incidents that involved heroin and synthetic drugs as these have been key drug types that have highly impacted cities during the opioid crisis in the U.S.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2002

Crime scene investigations using portable, non-destructive space exploration technology

The National Institute of Justice (NIJ) and the National Aeronautics and Space Administration's (NASAs) Goddard Space Flight Center (GSFC) have teamed up to explore the use of NASA developed technologies to help criminal justice agencies and professionals solve crimes. The objective of the program is to produce instruments and communication networks that have application within both NASA's space program and NIJ programs with state and local forensic laboratories. A working group of NASA scientists and law enforcement professionals has been established to develop and implement a feasibility demonstration program. Specifically, the group has focused its efforts on identifying gunpowder and primer residue, blood, and semen at crime scenes. Non-destructive elemental composition identification methods are carried out using portable X-ray fluorescence (XRF) systems. These systems are similar to those being developed for planetary exploration programs. A breadboard model of a portable XRF system has been constructed for these tests using room temperature silicon and cadmium-zinc telluride (CZT) detectors. Preliminary tests have been completed with gunshot residue (GSR), blood-spatter and semen samples. Many of the element composition lines have been identified. Studies to determine the minimum detectable limits needed for the analyses of GSR, blood and semen in the crime scene environment have been initiated and preliminary results obtained. Furthermore, a database made up of the inorganic composition of GSR is being developed. Using data obtained from the open literature of the elemental composition of barium (Ba) and antimony (Sb) in handswipes of GSR, we believe that there may be a unique GSR signature based on the Sb to Ba ratio.

Firearms↗

DOE OSTI2023

Multivariate regression modelling for gender prediction using volatile organic compounds from hand odor profiles via HS-SPME-GC-MS

The efficacy of using human volatile organic compounds (VOCs) as a form of forensic evidence has been well demonstrated with canines for crime scene response, suspect identification, and location checking. Although the use of human scent evidence in the field is well established, the laboratory evaluation of human VOC profiles has been limited. This study used Headspace-Solid Phase Microextraction-Gas Chromatography-Mass Spectrometry (HS-SPME-GC-MS) to analyze human hand odor samples collected from 60 individuals (30 Females and 30 Males). The human volatiles collected from the palm surfaces of each subject were interpreted for classification and prediction of gender. The volatile organic compound (VOC) signatures from subjects’ hand odor profiles were evaluated with supervised dimensional reduction techniques: Partial Least Squares-Discriminant Analysis (PLS-DA), Orthogonal-Projections to Latent Structures Discriminant Analysis (OPLS-DA), and Linear Discriminant Analysis (LDA). The PLS-DA 2D model demonstrated clustering amongst male and female subjects. The addition of a third component to the PLS-DA model revealed clustering and minimal separation of male and female subjects in the 3D PLS-DA model. The OPLS-DA model displayed discrimination and clustering amongst gender groups with leave one out cross validation (LOOCV) and 95% confidence regions surrounding clustered groups without overlap. The LDA had a 96.67% accuracy rate for female and male subjects. The culminating knowledge establishes a working model for the prediction of donor class characteristics using human scent hand odor profiles.

59 BASIC BIOLOGICAL SCIENCES↗