Assessment of the Integrity of Burglaries’/Housebreakings’ Modus Operandi Data-Ecosystem and Criminal Profiling using MOs

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Assessment of the Integrity of Burglaries’/Housebreakings’ Modus Operandi Data-Ecosystem and Criminal Profiling using MOs

1. Research Topic:

Assessment of the Integrity of the Burglaries’/Housebreakings’ MO (Modus Operandi) Data-Ecosystem and Criminal Profiling using MOs Relevant Features; A Blockchain Technology and Machine Learning Approach.

2. Introduction:

Modus Operandi records are very important in criminal profiling. When investigators perform criminal profiling, they are principally finding a way to demonstrate that, the same offender has committed two or more crimes via comparison of the criminal’s modes of operation. This task is of importance in the absence of a confession, eyewitness testimonies or other forensic evidence such as fibers, fingerprints or DNA19. In these cases, normally the police officers rely on behavioral information to link crimes with an assumption in mind that there will typically be a high degree of similarity between what an offender does in one crime and he or she does in another, though studies have unveiled that linking decisions are often based on limited, subjective impressions of the investigating officers, that the profiling results might often differ from one officer to another, based on their experience and memorization of the crimes history.

2.1. Background to the study.

As long as economic hardship & unemployment exist and poverty seems to be dominant among the citizens while the gap between the rich and poor is becoming wider, then people with deviant behaviors must prevail and thus crimes are inevitable in a human society. For the case of crimes related to residential burglary and house breaking, “there are three ways of detecting the perpetrator of a crime: first, his recognition by an eye-witness; second, in case of theft, the tracing to him of stolen property; and third, the traces which he leaves behind .i.e. Mode of Operation also known as Modus Operandi can lead to catch the perpetrator.”, According to Fosdick11. Having all those three approaches for uncovering the perpetrator of a crime; in most cases people (eye-witnesses) become reluctant to cooperate with the police force in avoidance of disturbances during the investigation process, hence that leaves the investigators with an option of making use of the Modus Operandi (MO) of the criminals to conduct investigations.

2.2. Problem statement.

In Tanzania, the Criminal Investigation Department (CID) office is responsible for carrying out criminal profiling by using the MO records. Having no automated electronic information system to keep records, linking a crime to a particular offender is not a trivial task, especially when the investigators are relying on the crime records that are stored in piles of papers.

The lack of efficiency in looking through past crime records and improper means of processing those data (MO records) are major causes which can be attributed to resulting in a low success rate of identifying the culprits in most of the forensic investigations conducted.

This exposes a need for improvement in this process. In addition, there are other several drawbacks of the current record keeping system. This includes;

Risks and anarchy of handling paper-based records, that hinders security and accessibility of the records when dealing with a huge mass of data, thus lowers throughput of the investigating team.
Incomplete record filling at local police station. In most cases, police officers tend to catch some criminal records in a very concise manner and that leads to the ambiguity of the Modus Operandi or sometimes keeping less informative records.
Growing size list of Modus Operandi for classification. Knowing that crimes are part and parcel of the human society, the Modus Operandi is not static, it is dynamically growing over time. Hence, we need some new techniques for processing these records.
Lack of efficiency in scanning through archives manually. As investigators deal with a huge pile of paper records, it becomes cumbersome to scrutinize the records efficiently so as to come up with a helpful pattern from the data.
Dependability of cognitive capacity (memory) of the investigator to keep the past history in mind.

2.3. Purpose of the study.

To propound a design for MO data ecosystem that resides on the Blockchain platform.

At the end of this research I am looking forward to come up with a suggested architecture on how we can effectively use blockchain systems to assure integrity and availability of the Modus Operandi that will lower efforts when investigators profiling the criminals.

2.4. Specific objectives.

To explore information flow mechanisms between peers in blockchain systems.
To observe the perceived level of integrity with a current method and explore on how we can facilitate the integrity of Modus Operandi data ecosystem in the blockchain systems.
To explore on how Machine Learning can improve the criminal profiling task.
To examine challenges encountered by investigators during profiling.
To structure a template form for capturing some pertinent and informative features of the criminal’s Modus Operandi.

2.5. Research questions.

How can data flow from one peer to another without the need for an intermediary?
What is the perceived level of integrity with the current manual system of collecting and archiving MO records and what should be done to ensure the integrity of the whole data ecosystem?
What is the significance of employing Machine Learning in analyzing the cumulative MO records for offender profiling?
What are the challenges that hinder effective criminal profiling?
What are the substantial features to be included in the MO-form for it be informative?

2.6. Scope of the study.

The study will specifically focus on the Modus Operandi (MO) records related to residential burglaries and housebreaking which are predominant in the metropolis areas. Moreover, I will also explore around the Public and Private blockchains as well as some algorithms in Supervised and Unsupervised Machine Learning models for effective classification of the criminals based on the MO features.

3. Literature review.

According to Fosdick R. [12], “there are three ways of detecting an offender of a crime: first, his recognition by an eye-witness (using portrait parle techniques); second, in case of theft, the tracing to him of stolen property; and third, the traces which he leaves behind .i.e. Mode of Operation also known as Modus Operandi can lead to catch the perpetrator.” A criminal’s MO behavior is functional in nature and it generally serves the purposes for the offender either to protect identity, to ensure success or to facilitate escape [19]. L.W. Atcherley, Chief Constable of the West Riding of Yorkshire Constabulary, developed what became known as Modus Operandi system around the late 19th century [10]. He had introduced ten headings namely; Class of the person or property attacked Means, Object, Time, Style, Tale, Pal, Trademark, and Transport. These MO attributes were introduced for the use of investigating officers, each relating to a phase of the method employed by the criminal in the perpetration of his crime. Similar to this August Vollmer introduced another set of MO attribute which he pointed could be used to define a criminals MO. According to his findings he proposed ten MO prime divisions namely; Crime, Person or property attacked, how attacked, with what attacked or means attacked, Time of attack, Object of attack, by whom attacked, Nationality of attackers, Number of attackers and Individual characteristics of attack or trademark [10]. These primary divisions are found divided into as many points as necessary until those specific methods of operation are accurately described. These sub points were given numbers and the combinations of primary division with any of these points were represented using a coding mechanism. In another research done by Oatley, Zeleznikow and Ewart [20] they have identified the MO features in a much more detailed manner where they have given a number of groups as MO features and sub variables relevant to them. According to the literature found [10] [20],extracting MO features can be either done in a generalized manner without considering a particular crime type where certain key points are given to be investigated and noted at the crime scene or criminal record, or on the other hand extraction of MO features can be done according to crime type using an MO system where MO primary divisions are divided into as many points as necessary until those specific methods of operation are accurately described.

3.1. Research gap.

It is a fact that our Police forces in our region are still handling the Modus Operandi records manually, this impedes their effectiveness in performing investigations; therefore, I consider the status quo as a knowledge gap to be acutely researched by employing the current technologies for improvement of the situation.

Blockchain technology being one of the new technologies; since its inception in 2009, it has obtained much success in its use-cases including the ones of electronic currencies and researchers in the area are foreseeing its potential of disrupting other industries and therefore I feel that it is one of a very good and apt areas to research in the dawn of industrialization 4.0.

However, knowing that the MO records are replicating exponentially and we don’t yet have an ICT based system on hand to handle these data and we need to analyze on how we can make use of all these populating data. Therefore, we need some data analytics and learning skills to extract some useful features from the MO records and process them so that we can get some vital insights for criminal profiling.

Having all these novel technologies in a study, I am excited to research on how we can leverage them in the forensics investigations.

4. Definition of key terms.

Modus Operandi Modus Operandi, or method of operation, is really a term that refers to the habits, techniques and peculiarities of behavior of a criminal. All criminals have a modus operandi, and enough of them have distinctive methods of operation to justify the classification of crimes by like characteristics. The modus operandi of a criminal is his ‘signature “. Hazelwood and Warren (2004) emphasized that “the term modus operandi is used to encapsulate all of the behaviors that are requisite to a particular oﬀender successfully perpetrating a crime.” It encompasses all behaviors initiated by the oﬀender to procure a victim and complete the criminal acts without being identified or apprehended.
Criminal Profiling Criminal profiling, also known as Offender profiling, is an investigative strategy used by law enforcement agencies to identify likely suspects and has been used by investigators to link cases that may have been committed by the same perpetrator.
Machine Learning Arthur Samuel (1959, p. 210) defined ML as: “The field of study that gives computers the ability to learn without being explicitly programmed.” Later on, Tom Mitchell (1997, p. 2) provided a more formal definition: “A computer program is said to learn from experience E with respect to some task T and some performance measure P, if its performance on T, as measured by P, improves with experience E.”
Blockchain Simply put, a blockchain as a distributed ledger that provides a way for information to be recorded and shared by a community. In this community, each member maintains his or her own copy of the information and all members must validate any updates collectively. The information could represent transactions, contracts, assets, identities, or practically anything else that can be described in digital form. Entries are permanent, transparent, and searchable, which makes it possible for community members to view transaction histories in their entirety. Each update is a new “block” added to the end of a “chain.” A protocol manages how new edits or entries are initiated, validated, recorded, and distributed. With blockchain, cryptology replaces third-party intermediaries as the keeper of trust, with all blockchain participants running complex algorithms to certify the integrity of the whole.

5. Methodology.

5.1. Research Approach.

This study will apply pragmatism paradigm which include the application of mixed approach of both qualitative and quantitative methods. Pragmatism approach is the most practical and flexible approach which involves using more than one method or technique to solve a problem at hand (Grover, 2015). The chosen approach will be very apposite for it provides a researcher the freedom to select satisfactory techniques to accomplish the goal.

5.2. Research Design.

Research design essentially indicate various approaches to be used in solving research problem and help to perform the chosen task easily and in systematic way (Rajasekar et al., 2013). A case study design will be employed to obtain comprehensive results for this study. Grover (2015) explains that case study provides an in-depth study of a particular research problem because it covers the holistic and meaningful features of events. In this study the case study design will help the researcher to reveal the unknown phenomena of the problem being investigated.

5.3. Study Area.

This study will be carried out in some selected police stations in the metropolitan areas, specifically in Dar es Salaam (Kinondoni, Temeke & Ilala), Kagera, Pwani and in Morogoro Municipal, where burglary case reports are predominant. The police stations in these areas take care of Modus Operandi records concerning house breaking from different suburbs of the city and hence guarantee the study to obtain the prime and pertinent information.

5.4. Population of the Study

This study intends to reach a number of respondents in the police force particularly in the Criminal Investigation Department (CID) office, including the in-charge police officers who are responsible for recording and archiving criminal records in the police stations. Also, the records management staffs will be involved since they are the key workers in handling records of all reported crimes. Similarly, the records beneficiaries (investigators) will be involved in the study for they are main consumers of the filed criminal records.

5.5. Sampling Design.

Sampling Technique. In this study, I am going to employ the purposive sampling technique. Purposive sampling is a sampling technique in which the items of the sample are selected deliberately by the researcher (Etikan et al., 2016). I have resolved to avail this method for it gives the researcher a freedom to decide on the choice of best participants who will provide accurate and reliable data.
Sample Size. The determination of sample size is vital in research because it determine the time and funding to accomplish the study (Amugube, 2014). The sample size for this study will be drawn from various police stations in six different Municipal Councils to find out on how they handle the MO records. Kothari and Garg (2014), comments that the adequate representative sample should be at least 10%, thus this study will use 10% of the police stations in each Municipal Council. The distribution of respondents is summarized in the below table:

Population Type

Sample Size

Chosen

Respondent size 10%

Sampling Technique
Data Collection Instrument
Investigators
Purposive Sampling

Interview

Police Officers (in duty)
Purposive Sampling