The Role of Artificial Intelligence in Criminal Investigation: Digital Evidence as a Model

Algerian Journal of Legal and Political Sciences Vol: 63, N°:03, Year:2026, pp: 360-372 360 The Role of Artificial Intelligence in Criminal Investigation: Digital Evidence as a Model The Role of Artificial Intelligence in Criminal Investigation: Digital Evidence as a Model - األدلة الرقمية نموذجا - دور الذكاء االصطناعي في التحقيقات الجنائية HEMIS Maamar * University of Djillali Bounaama, Khemis Miliana (Algeria) Civil Status System Laboratory [email protected] Date of Submission 02-04-2026 Date of Final Acceptance 12-09-2026 Date of Publication September 2026 ـــــــــــــــــــــــــ ـــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــ ـــــــــــــــــــ * Corresponding Author: HEMIS Maamar Abstract: The rapid development of artificial intelligence has brought about a qualitative transformation in criminal investigations, particularly with regard to digital evidence. Its technologies enable investigative authorities to analyze vast amounts of electronic data with high speed and accuracy. Artificial intelligence assists in detecting hidden criminal patterns and systematically linking digital facts and events. It also contributes to the analysis of images and videos and the tracking of suspicious online activities. Moreover, it has become an effective tool in combating complex cybercrimes. However, reliance on artificial intelligence raises legal issues concerning the evidentiary value of digital evidence. In addition, it poses ethical challenges related to the protection of personal data. This necessitates the establishment of a clear legal framework that ensures investigative efficiency while safeguarding fundamental rights and freedoms. Keywords : Artificial Intelligence, Criminal Investigations, Digital Evidence, Cybercrime, Digital Forensic Analysis, Evidentiary Value. م ل خص : أدى التطور المتسارع للذكاء االصطناعي إلى إحداث نقلة نوعية في مجال التحقيقات الجنائية، اوال سيما في ما يتعلق باألدلة الرقمية، إذ تُمكّن تقنياته الجهات المختصة من تحليل كميات ضخمة من االبيانات اإللكترونية بسرعة ودقة عاليتين، ويساعد الذكاء االصطناعي في كشف األنماط اإلجرامية الخفية اوربط الوقائع الرقمية ببعضها البعض بشكل منهجي، كما يساهم في تحليل الصو ر والفيديوهات وتتبّع ااألنشطة اإللكترونية المشبوهة، ويُعد أداة فعّالة في مواجهة الجرائم السيبرانية المعقّدة، غير أن االعتماد عليه ايثير إشكاالت اقانونية اتتعلق بحجية األدلة الرقمية . اإضافة اإلى اتحديات أخالقية مرتبطة ابحماية المعطيات الشخصية، مما يستلزم وضع إطار ق اانوني اواضح يضمن فعالية التحقيق مع احترام الحقوق والحريات األساسية . الكلمات المفتاحية : الذكاء ااالصطناعي، التحقيقات الجنائية، ااألدلة الرقمية، الجرائم السيبرانية، االتحليل الجنائي الرقمي، حجية الدليل اإللكتروني .

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HEMIS Maamar 361 The Role of Artificial Intelligence in Criminal Investigation: Digital Evidence as a Model Introduction: اااااThe rapid technological development has led to a qualitative shift in criminal justice mechanisms, especially with the emergence of Artificial Intelligence (AI), which has become a pivotal element in collecting and analyzing evidence. Therefore, criminal investigation no longer relies solely on human expertise but now depends on intelligent systems capable of processing enormous amounts of digital information, deciphering complex codes, and extracting precise criminal indicators. ااااThe contemporary world is witnessing rapid technological transformations that have imposed themselves on various areas of life, including criminal justice, which increasingly relies on Artificial Intelligence (AI) in data and evidence analysis. The latter has become an effective tool in crime detection and offender tracking, particularly amid the growing prevalence of cybercrimes that rely on the digital space either as a means or as an environment for committing the crime 1 اااااAmong the most prominent applications of AI in this field is the analysis of digital evidence extracted from electronic devices or information networks, which today represents a major focus in modern criminal investigations. ااااThis new reality raises the question of the extent to which AI can develop criminal investigation methodologies and the legal and ethical challenges it poses, particularly regarding the legitimacy of digital evidence and protection of individual privacy. ااااThis research aims to achieve several scientific and practical objectives, most notably: 1. Analyzing the role of AI in developing criminal investigation methods. 2. Clarifying the concept of digital evidence and its importance in modern criminal proof. 3. Demonstrating AI applications in digital evidence analysis and how they are employed in crime detection. 4. Monitoring the legal and ethical challenges posed by AI technologies in the criminal field. 5. Proposing a balanced legal and ethical framework that ensures the benefit from technology without harming human rights. ااااIn this context, the importance of this topic stems from its addressing of the interaction between criminal law and the digital revolution, which represents a major challenge for legal systems worldwide. • From a scientific perspective: The research contributes to enriching legal studies related to AI, especially in the field of evidence and investigation. • From a practical perspective: It provides modern insights for investigators and experts on how to employ intelligent systems to analyze digital evidence more effectively. • From a legislative perspective: It helps formulate proposals to update national laws in line with technological developments while ensuring respect for fundamental rights. ااااااااThis research relied on the descriptive-analytical methodology, through:

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HEMIS Maamar 362 The Role of Artificial Intelligence in Criminal Investigation: Digital Evidence as a Model • Accurate description of the concept of AI and its applications in criminal investigation. • Analysis of legal texts, jurisprudential references, and relevant international materials. • The comparative method when necessary, to compare some international experiences (such as French and American) in using AI in digital evidence analysis. • The inductive method was also adopted to infer results from practical applications and case studies. The main research problem is summarized in the central question: To what extent has AI contributed to developing criminal investigation methodology through digital evidence analysis, and what are the resulting legal and ethical challenges? Section I: The Conceptual Framework of AI and Criminal Investigation ااااThis chapter is a fundamental theoretical introduction to understanding the relationship between AI and criminal investigation. It aims to clarify the basic concepts associated with both, including the nature of AI and its legal applications, then defining traditional and digital criminal investigation as a basis for understanding the new role of intelligent technologies in this field. A) The Concept of AI in the Criminal Field ااااAI is defined as: “the ability of technical systems to perform tasks that usually require human intelligence, such as understanding, learning, and decision-making.” ا 2 ااااThis concept is among the most comprehensive in the digital revolution era, as it encompasses a wide spectrum of applications that simulate human thinking methods and rely on data, algorithms, and machine learning. ااااIn the criminal field, AI refers to: “the use of intelligent software and algorithms to analyze criminal data, extract patterns or indicators that contribute to crime detection or prediction.” ااااIts applications include multiple areas, such as: • Facial recognition systems. • Analysis of digital texts and communications. • Monitoring information networks. • Examining digital evidence and extracting elements of investigative value. ااااThe importance of these technologies lies in their ability to process huge amounts of data faster than humans, while maintaining high accuracy and objectivity in analysis 3 ااااAI allows analyzing massive information rapidly, enhancing the precision of investigation and accelerating the achievement of results. اااااResearchers confirm that integrating AI into investigative agencies’ work is considered a “qualitative transformation in modern criminal justice”, as the role of technology has shifted from

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HEMIS Maamar 363 The Role of Artificial Intelligence in Criminal Investigation: Digital Evidence as a Model simple technical assistance to participation in “analytical decision-making” in criminal processes, through reading patterns and inferring relationships between facts and individuals. ااااThe significance of AI in the criminal field stems from its ability to enhance investigative accuracy, accelerate investigation pace, and improve the ability to detect criminal activities, especially amid the massive expansion and diversity of cybercrime. ااااHowever, its use remains conditional on respecting legal safeguards, particularly concerning privacy protection and algorithmic transparency, to prevent infringement on individual rights or deviation from justice. B) Criminal Investigation in the Digital Environment ااااCriminal investigation is defined as: “a systematic process aimed at collecting, analyzing, interpreting, and presenting evidence before the judiciary.” 4 ااااInvestigation is one of the fundamental pillars of the criminal justice system, as it embodies the stage in which judicial truth is established by following a strict scientific methodology that combines respect for the legal guarantees of litigants with effective identification of the perpetrator. ااااWith deep transformations imposed by modern technology, crime is no longer confined to physical space but has gradually moved into the digital environment, occurring via information networks, smart devices, or platforms and data-driven systems. ااااThis shift to cyberspace has created a complex environment characterized by speed, encryption, and transboundary nature, forcing criminal justice agencies to reconsider traditional investigation methods and develop advanced technological capabilities to face cybercrime 5 ااااFrom this context, the concept of Digital Forensics emerged, defined as: “a set of technical and legal procedures aimed at examining electronic devices, information systems, and digital data to extract legally admissible evidence that can be presented before the judiciary.” 6 ااااThis type of investigation relies on specialized techniques capable of recovering deleted data, analyzing system logs, tracing digital fingerprints, and identifying the source of cyber-attacks, while maintaining the integrity of digital evidence to ensure judicial acceptance. ااااInvestigating digital crimes is not only technical but also requires deep legal understanding, due to the peculiarities of digital evidence and its susceptibility to rapid alteration or destruction. Hence, it is imperative for legislators and judicial authorities to develop laws and procedures compatible with the nature of such evidence, regarding collection, preservation, and presentation before the judiciary, ensuring a balance between protecting individual rights and effective crime fighting in a rapidly evolving digital world. ااااDigital criminal investigation differs from traditional investigation in that it deals with “intangible evidence” easily copied or destroyed, such as emails, encrypted files, browsing histories, and

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HEMIS Maamar 364 The Role of Artificial Intelligence in Criminal Investigation: Digital Evidence as a Model metadata. Therefore, precise techniques are required to ensure evidence integrity and prevent tampering. ااااIn this context, AI systems have become pivotal in analyzing such evidence, providing automatic classification, pattern recognition, and user behavior prediction, giving them a central position in the future of digital criminal investigations 7 Section II: Artificial Intelligence as a Tool for Digital Evidence Analysis ااااAI is considered one of the most prominent tools that have transformed criminal investigation methods in the digital era. It enables investigators to analyze massive amounts of data with speed and accuracy surpassing human capabilities. Its various applications have turned digital evidence from static data into effective criminal indicators that help detect crimes and identify perpetrators. ااااTo understand this role, it is necessary first to identify the nature of digital evidence that can be analyzed and then clarify how AI contributes to processing it. A) Types of Digital Evidence that Can Be Analyzed ااااThe digital environment has witnessed a significant expansion in the volume of data generated daily from various devices and information platforms, making digital evidence a core component of modern criminal investigations. ااااDigital evidence refers to any information extracted from an electronic device or system that can help uncover a crime, identify perpetrators, or reconstruct events. ااااSuch evidence is intangible and highly mutable, requiring precise procedures for collection, analysis, and preservation. ااااDigital evidence includes any electronically stored or transmitted information that can be used to prove a factual or legal event. Its main types are as follows: 1- Computer Data Includes information stored in desktop and laptop computers, such as: o Text files, images, and documents o Deleted files recoverable through forensic methods o System logs o Login and usage recordsاا8 These data are one of the most important sources of digital criminal evidence because they preserve technical traces that help determine the time and nature of the criminal activity.

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HEMIS Maamar 365 The Role of Artificial Intelligence in Criminal Investigation: Digital Evidence as a Model 2 - Smartphones and Mobile Devices Data Smartphones contain large amounts of personal and professional data, including: o Text messages and app-based conversations o Call logs and contact lists o Photos and videos o GPS location data o Installed applications and related files 9 These data are highly valuable in cases involving communication, hacking, cyber harassment, or criminal coordination. 3 - Network-Based Evidence Evidence generated from data traffic through local and global networks, including: a. Server logs b. Network traffic c. Firewall logs d. Router and switch logsا10 Such evidence is used to detect cyber-attacks, hacking attempts, or trace digital communications. 4 - Multimedia Evidence Includes: a. Digital images b. Video clips c. Audio recordings This evidence requires specialized analysis focusing on authenticity verification and detecting any manipulation, using tools such as Image Forensics or Audio Forensics 11 5 - Social Media Evidence Platforms like Facebook, Instagram, WhatsApp, and Telegram generate huge amounts of data used in investigations, such as: a. Messages and conversations b. Interactions and posts c. Login records and user locations This evidence is particularly important in cases of blackmail, online fraud, and defamation.

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HEMIS Maamar 366 The Role of Artificial Intelligence in Criminal Investigation: Digital Evidence as a Model 6 - Cloud-Based Evidence Includes information stored on remote servers, such as: a. Shared files b. Backups c. Cloud system logs Accessing such evidence is sometimes difficult due to differing jurisdictions and multiple service providers worldwide ا12 7 - Internet of Things (IoT) Evidence With the proliferation of smart devices, evidence can be extracted from: a. Smart home cameras b. Fitness trackers c. Home automation devices d. Sensors Such data contribute to reconstructing events or accurately locating individuals. B) The Role of AI in Analyzing Digital Evidence ااااAI has triggered a real revolution in digital forensic analysis, being used to detect patterns, identify suspicious behaviors, and classify data according to its criminal significance. Its practical applications include : 13 1 - Machine Learning ااااThis technique trains systems on massive datasets to autonomously detect criminal patterns and relationships. ااااIt is especially used in analyzing hacking behavior, online fraud, and predicting repeated cybercrimes 14 2 - Image and Audio Recognition ااااComputer vision and audio processing algorithms are used to analyze surveillance footage and audio recordings, enabling precise recognition of suspects’ faces and voices 15 ااااThis technology is also employed to detect tampered or digitally altered scenes and images.

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HEMIS Maamar 367 The Role of Artificial Intelligence in Criminal Investigation: Digital Evidence as a Model 3 - Text and Communication Analysis ااااAI systems utilize Natural Language Processing (NLP) to analyze conversations and emails to determine criminal intent or suspicious relationships between communicating parties. This analysis is crucial in cases of cyberterrorism, blackmail, and online incitementا16 - Text Content Analysis اااFocuses on processing digital texts to identify: • Keywords with criminal significance • Encoded or indirect phrases • Linguistic style that may indicate the author’s identity • Indicators of threats, blackmail, or incitement • Repetition patterns or distinctive vocabulary of a person or group اااAI techniques such as NLP help convert texts into analyzable statistical or semantic data. - Digital Communication Analysis اااExamines metadata and communication structure, such as: • Message timestamps • Conversation duration • Sender and recipient identity • Device type • Message location (if available) ا ااThis data helps track information flow, identify involved parties, or establish connections between suspects and victims or criminal networks 17 - Email Forensics Involves examining: • Sender and recipient addresses • IP addresses • Email headers • Attachments • Suspicious links Essential in cases of online fraud, phishing, and targeted cyberattacks 18 - Voice and Audio Message Analysis With frequent use of voice messages in apps, analysis includes:

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HEMIS Maamar 368 The Role of Artificial Intelligence in Criminal Investigation: Digital Evidence as a Model • Voice characteristics • Speaker tone • Message content • Verifying authenticity and ensuring no alterations - Contextual and Behavioral Analysis Digital investigation considers not only words but also: • Writing style (Stylometry) • Typing speed • Common mistakes • Linguistic tendencies • Social context of the conversation These elements help determine whether a message is authentic, written by the original author, or fabricated, enhancing its legal admissibility 19 4 - Criminal Network Analysis AI techniques rely on Social Network Analysis (SNA) to uncover hidden links between perpetrators by tracing digital communications and identifying the most influential nodes in criminal networks. These applications are effective tools for dismantling cyber gangs and transnational organized crime 20 ااااAI’s role in digital evidence analysis now extends beyond technical aspects to support decision- making in investigations by providing accurate probabilistic conclusions that guide investigators toward realistic paths. ااااCriminal network analysis is defined as: “a set of techniques used to uncover the internal structure of criminal groups by studying links between individuals and determining the degree of influence and connectivity among them.” It is particularly used in cases involving: • Organized crime • Terrorism and its financing • Drugs • Human trafficking • Complex cybercrimes 21 اااThe analysis relies on social and mathematical sciences, especially SNA, and uses diverse data, including:

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HEMIS Maamar 369 The Role of Artificial Intelligence in Criminal Investigation: Digital Evidence as a Model • Call Detail Records (CDR) • Emails and digital chats • Social media metadata • App communication logs • Geographical data of communicants • Electronic financial transfers • Closed group chat activities 22 ااااThus, AI has transformed digital evidence analysis from limited human effort to an intelligent system capable of detection, inference, and prediction. Yet, its use poses legal challenges concerning evidence legitimacy and the limits of machine authority in judicial procedures. Section Ⅲ : Legal and Ethical Challenges in Using AI with Digital Evidence ااااDespite AI’s immense benefits in criminal investigation and digital evidence analysis, its deployment raises numerous complex legal and ethical issues, particularly regarding evidence legitimacy, privacy protection, and algorithmic error responsibility. ااااThis chapter highlights the main challenges across three sections: A) Legitimacy of Automatically Extracted Evidence ا اااA central question arises regarding the judicial admissibility of digital evidence produced by AI systems, especially since such evidence is extracted through complex technical processes difficult for judges or defense attorneys to fully verify. ا ااSome scholars argue that this evidence may lack a proper chain of custody, as in traditional criminal procedures, ensuring evidence integrity from collection to presentation before the judiciary. ا ااAnother issue concerns the possibility of judicial oversight of algorithms. Many codes are privately owned, creating a “black box” in interpreting technical results, threatening transparency and limiting the right to challenge scientific evidence. B) Privacy and Individual Rights Protection ا اااProtecting personal data is among the most prominent legal and ethical challenges in using AI with digital evidence. With the expansion of digital monitoring, algorithms can collect and analyze vast amounts of sensitive data without explicit consent, potentially violating procedural legality and privacy protection under national laws and international conventions 23 اااThis challenge intensifies without specialized legal frameworks regulating AI usage in investigations, data collection limits, storage, retention periods, and ultimately necessitates national legislation aligned with European and international standards 24

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HEMIS Maamar 370 The Role of Artificial Intelligence in Criminal Investigation: Digital Evidence as a Model C) Algorithmic Bias and Legal Responsibility ااااOne of the most serious challenges is algorithmic bias, as AI systems rely on previously trained data that may contain human errors or biases, resulting in unfair outcomes, such as false suspicion or skewed behavior evaluation. اااStudies have shown that algorithms may exhibit discriminatory tendencies when analyzing criminal data, particularly regarding gender, ethnicity, or social affiliation. ااااLegal responsibility is also debated: if a technical error occurs or an inaccurate result is issued, who is accountable—the programmer, the security authority using it, or AI itself? This issue remains controversial and reveals the urgent need to redefine legal responsibility concepts in the era of comprehensive digital transformation 25 Conclusion: ااااThis research has shown that AI is no longer a mere supporting technology but a core pillar in developing contemporary criminal investigation tools and methods, particularly amid widespread cybercrime and its complexity. ااااConceptual and applied analysis demonstrates AI’s pivotal role in digital evidence analysis, thanks to its ability to process large datasets, detect hidden patterns, and accelerate results that previously required arduous human effort. ااااKey conclusions include: 1. AI represents a qualitative leap in criminal justice, enhancing accuracy and efficiency, especially in complex cybercrimes. 2. Digital evidence has become a major component of criminal proof, and AI analysis is an effective tool to identify perpetrators and track activities. 3. Legal challenges, particularly evidence legitimacy, privacy protection, and algorithmic bias, pose obstacles to balanced and responsible AI use. 4. Current legal frameworks in most countries are insufficient to handle automatically extracted evidence or technical liability cases. ااا اPractical and legislative recommendations: 1. Update criminal and procedural laws to include clear provisions on AI-extracted digital evidence and criteria for judicial acceptance. 2. Establish independent national bodies for technical and judicial oversight of intelligent systems in the criminal field to ensure transparency. 3. Enhance training programs for investigators, judges, and experts in AI and cybersecurity for precise understanding of digital evidence and analysis methods. 4. Establish ethical standards and professional guidelines defining AI usage limits in investigations while protecting individual privacy and fundamental rights.

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HEMIS Maamar 371 The Role of Artificial Intelligence in Criminal Investigation: Digital Evidence as a Model 5. Promote scientific research and international cooperation in criminal AI to exchange expertise and develop more precise and fair analytical tools. ااااIn conclusion, the future of criminal investigation is heading toward integrating AI as a core actor in criminal justice systems, with successful integration contingent on balancing technical efficiency and legal-human safeguards, which form the essence of justice Citations: -------------------------------------------------- 1 . ع ابدااللطيفاسامي،االذكاءااالصطناعياوالتحقيقاتاالجنائيةاالرقمية،امجلةاالقانوناوالتكنولوجيا،االعددا 5 ا،ا 2023 ا،اصا 12 ا 2. Russell Stuart J, & Norvig Peter, Artificial Intelligence: A Modern Approach (4th ed.). Pearson, 2021, p 5 3 . اعبدااللطيف،اساميا،االذكاءااالصطناعياوالتحقيقاتاالجنائيةاالرقمية،امجلةاالقانوناوالتكنولوجيا،االعددا 5 ا،ا 2023 ا.،اصا 14 ا 4. Mike Maguire ,Criminal Investigation. Oxford University Press,2018, p. 33 5. ¹ Casey Eoghan Patrick, Digital Evidence and Computer Crime: Forensic Science, Computers, and the Internet , 4th edn, Academic Press 2019, P 12. 6. International Organization for Standardization. (2015). ISO/IEC 27043:2015 — Information technology—Security techniques—Incident investigation principles and processes, 2015 7. Casey Eoghan Patrick, Digital Evidence and Computer Crime: Forensic Science, Computers, and the Internet ,4th edn, Academic Press, 2019, P 425. 8. Casey, Eoghan Patrick, Digital Evidence and Computer Crime: Forensic Science, Computers, and the Internet , 4th edn, Academic Press 2019, P 78. 9. Casey Eoghan Patrick, Digital Evidence and Computer Crime: Forensic Science, Computers, and the Internet , 4th edn, Academic Press 2019, P 112. 10. International Organization for Standardization, ISO/IEC 27043:2015 — Information technology—Security techniques—Incident investigation principles and processes (2015) , P 23. 11. Casey Eoghan Patrick, Digital Evidence and Computer Crime: Forensic Science, Computers, and the Internet , 4th edn, Academic Press 2019, P 210. 12. United Nations Office on Drugs and Crime (UNODC), AI and Criminal Justice Systems , Vienna ,2021, P 48. 13. Casey Eoghan Patrick, Digital Evidence and Computer Crime: Forensic Science, Computers, and the Internet , 4th edn, Academic Press, 2019, P 425. 14. Chen Chao Liu, Wei Zhang Xin, et al., ‘Machine Learning in Digital Forensics’ (2020) 8 IEEE Access, p. 12 15. Goodfellow, I, Bengio, Y, & Courville, A ,Deep Learning, MIT Press, 2016, p. 218 16 . عبداالمنعماكمال،ااألدلةااإللكترونيةافياظلاالذكاءااالصطناعي،اداراالنهضةاالعربية،االقاهرة،ا 2022 ،اصا 33 ا 17. Casey Eoghan Patrick, Digital Evidence and Computer Crime: Forensic Science, Computers, and the Internet , 4th edn, Academic Press 2019, P 332. 18. ¹ Casey Eoghan Patrick, Digital Evidence and Computer Crime: Forensic Science, Computers, and the Internet , 4th edn, Academic Press 2019, P 310. 19. Casey Eoghan, Digital Evidence and Computer Crime: Forensic Science, Computers, and the Internet (4th ed.). Communication Analysis, Text Evidence, Messaging Artifacts , Academic Press, 2019, pp. 423–438 20. UNODC, AI and Criminal Justice Systems, United Nations Office on Drugs and Crime, Vienna, 2021, p 64

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HEMIS Maamar 372 The Role of Artificial Intelligence in Criminal Investigation: Digital Evidence as a Model 21. Álvarez-Hamelin José Ignacio, Criminal Networks and Network Analysis , Routledge, 2018, pp 45–63. 22. Borgatti Stephen P, Everett Martin G, Johnson Jeffrey C, Analyzing Social Networks 2nd edn, SAGE Publications, 2018, pp. 97–130. 23. Marr Bernard, Artificial Intelligence and the Law , Forbes Publications, 2022, p. 55. 24. European Data Protection Board, Guidelines on AI and Data Protection, Brussels, 2021 25 . اأبواطالباحسن،االمسؤوليةاالقانونيةاعناأخطاءاالذكاءااالصطناعي،امجلةاالحقوق،اجامعةاالكويت،االمجلدا 47 ا،االعددا 2 ا،ا 2023 ،اصا 77 Bibliography : A- Books: 1. Russell Stuart J., Norvig, Peter, Artificial Intelligence: A Modern Approach , 4th edn, Pearson, 2021 2. Maguire Mike, Criminal Investigation , Oxford University Press, 2018 3. International Organization for Standardization, ISO/IEC 27043:2015 — Information Technology—Security Techniques—Incident Investigation Principles and Processes (2015). 4. Chen Chao Liu, Wei Zhang Xin, et al., ‘Machine Learning in Digital Forensics’ (2020) 8 IEEE Access. 5. United Nations Office on Drugs and Crime (UNODC), AI and Criminal Justice Systems, Vienna ,2021 6. Marr Bernard, Artificial Intelligence and the Law , Forbes Publications, 2022 7 . عبداالمنعماكمال،ااألدلةااإللكترونيةافياظلاالذكاءااالصطناعي،اداراالنهضةاالعربية،االقاهرة،ا 2022 . B- Articles: 8. Goodfellow Ian J, Bengio Yoshua, Courville Aaron, Deep Learning, MIT Press, 2016 9. Casey Eoghan Patrick, Digital Evidence and Computer Crime: Forensic Science, Computers, and the Internet, 4th edn, Academic Press, ‘Communication Analysis, Text Evidence, and Messaging Artifacts’,2019, pp. 423–438. 10. Álvarez-Hamelin José Ignacio, Criminal Networks and Network Analysis, Routledge, 2018, pp 45–63. 11. Borgatti Stephen P, Everett Martin G, Johnson Jeffrey C, Analyzing Social Networks 2nd edn, SAGE Publications, 2018, pp. 97–130. 12. European Data Protection Board, Guidelines on AI and Data Protection (Brussels 2021). 13 . عبدااللطيفاسامي،االذكاءااالصطناعياوالتحقيقاتاالجنائيةاالرقمية،امجلةاالقانوناوالتكنولوجيا،االعددا 5 ،ا 2023 . 14 . اأبواطالباحسن،ا االمسؤوليةاالقانونيةاعناأخطاءاالذكاءااالصطناعي،امجلةاالحقوق،اجامعةاالكويت،االمجلدا 47 ا،االعددا 2 ا،ا 2023 .

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